Enhanced RSA Algorithm for Data Security in the Internet of Things

Enhanced RSA Algorithm for Data Security in the Internet of Things | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Enhanced RSA Algorithm for Data Security in the Internet of Things Bashart Ullah, Abdul Mateen, Adia Khalid, Saeed Ullah, Rubina Adnan, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1896185/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Various devices are linked together through a variety of networks in order to exchange data in the Internet of Things (IoT). Life has changed dramatically as a result of the IoT's quickly developing applications, making it more fanciful and akin to living in a virtual environment. IoT security may be a major concern because it allows access to anything from anywhere at any time. Different mechanisms are used, including encryption, to safeguard the data transmitted by various IoT devices. A straightforward piece of content can be transformed into an intangible one via encryption. Two frequently used methods of encryption are symmetric key and asymmetric key cryptography. Asymmetric cryptography uses two separate keys for encoding and unscrambling messages as opposed to symmetric key cryptography, which uses just one key for both encoding and decoding. To protect IoT data, several public key cryptography techniques are utilized. However, numerous studies have demonstrated that it is incredibly challenging to safeguard data while utilizing the fewest resources from hackers and other cybercriminals. This study presents a concise overview of many existing encryption techniques and highlights their shortcomings. Conjointly presents an improved Rivest–Shamir–Adleman (RSA) algorithm to dodge the limits of diverse factorization assaults by upgrading complications of the factorization handle by utilizing five prime numbers and a fake open key instead of the original key and imposter modulus in its place of the product of five prime numbers. The proposed algorithm generates keys a little more slowly than the other two RSA algorithms (Rivest et al., 1978 ) and (Ivy et al., 2012 ) due to the usage of additional prime numbers and the difficulty of factorization preparation. For encryption and unscrambling, the suggested calculation takes less time than RSA (Ivy et al., 2012 ), but it costs more than RSA (Rivest et al., 1978 ). Since the suggested calculation employs five prime numbers instead of RSA's two prime numbers, it takes longer to encrypt data and decrypt it than RSA (Rivest et al., 1978 ). But since security comes first, the longer encryption and decryption time is acceptable. Security Encryption Decryption Internet of Things Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction And Background The Internet of Things (IoT) is a network of connected items, including computers, robots, mobiles and other devices. All of the devices have some electronic, software, sensor, and network connectivity built in, and they all have unique identifiers that allow them to communicate with one another and send and receive various types of information. The IoT can include any device that is capable of receiving an IP address and using that address to communicate with other items online. These devices are capable of observing their surroundings, gathering information from it, and transmitting it to other items. With the rapid expansion of IoT, life has become increasingly fictitious, similar to living in a virtual environment. IoT's idea of linking everything to the internet results in the production of a large amount of data known as big data. The idea of big data is further divided into its capacity, which refers to how much room is needed for data collection, its rate of data generation, and its assortment. Since IoT offers access to everything from anywhere at any time, security is a significant barrier that need to be enhanced. The IoT has a three-layer architecture: sensing, network, and application layer as seen in Figure. 1.1. The Sensing layer is a physical layer that is connected up with various sensors, including RFID, WSN, GPS, NFC, and cameras etc. These sensors sense and compile a variety of environmental data. In addition, it is responsive for converting data into sophisticated signals that are easily transmitted via a network. The Network layer, also known as the Transport layer, is able to prepare data obtained from the Recognition layer. It is also capable of transferring data to the application layer using various technology advancements, including wired, wireless, and local area networks. The most common transmission mediums include 4G, 5G, Wi-Fi, Bluetooth, and infrared technologies etc. The application layer makes use of the data that was handled by prior layers. It conveys to the client the particular advantages of any program. It describes several applications for the IoT, such as smart grids, smart cities, and wearable health monitoring. Due to their connectedness with one another in IoT, gadgets and other objects provide similar challenges to new clients in terms of authentication [1]. In addition, primary concerns with IoT data security include confidentiality, integrity and authentication. A crucial component of IoT security is data confidentiality, which specifies that only individuals with permission can access the data or information. Data integrity guarantees that the information or data is complete and original throughout its lifecycle, including when it was sent and received, etc. When data or information is transferred between different devices or things, it can be altered. In IoT, there are different devices that communicate with one another. As a result, these devices should be able to authenticate one another in order to ensure that the device providing or accessing sensitive information or data is a legitimate party. One approach of information protection, among many others, is cryptography. The name "cryptography" derives from the Greek words kryptos, which means "hidden," and graphien, which means "to write." By utilizing encryption, a plain text can be transformed into an intangible text. Encryption is used to send data in a format that only the intended receivers can read and understand. There are typically three categories of cryptography, which are Symmetric Key Cryptography, Asymmetric Key Cryptography and hashing. In case of Symmetric Key, only one key is utilized for both encoding and decoding of content by dispatcher and recipient as shown in Figure 1.2. Symmetric key cryptography is faster and simpler if the key exchange between the sender and receiver is secure. Most widely used symmetric key cryptography algorithms are Data Encryption Standard (DES), AES, etc. Asymmetric key cryptography, also known as open key cryptography, encrypts and decrypts data using two keys (public and private) as shown in Figure 1.3. Everyone has access to the open key, but only the message's intended recipient has access to the private key, which is used to decode it. RSA Algorithm, Digital Signature Algorithm and Elliptic Curve Cryptography are common types of asymmetric cryptography. A hash function is a type of cryptographic operation that accepts input (any size) and generates predetermined size output. It is comparable to a scientific condition that takes numbers from input and produces a hash as a result. It operates on two blocks and doesn't require a key. A binary block is used as the input, and the result is a hashing code. Hashing functions comprises of different rounds, mixture of the latest block and the product of previous round is used as an input for a round in hash function, as shown in Figure 1.4. Message Digest 5, Secure Hash Algorithm, and whirlpool are some popular Hash functions. In 2020, there were around 50 billion IoT devices, which demonstrates the importance of this technology in human life. IoT does, however, confront some difficulties, one of which is the privacy and security of the data produced. According to a HP survey, 60% of IoT devices have security flaws, and 70% of IoT devices failed to encrypt data during data transmission. As is common knowledge, there are numerous groups attempting to improve the data security of IoT and a variety of encryption techniques are available. However, there is still a lot of work to be done to enhance the security. The main objectives of the proposed research are: Identification of the flaws in the current IoT data security algorithms. Increase the security of IoT data through improved encryption algorithms. Suggest the optimal encryption technique for the IoT in terms of resource usage. The rest of the article is organized as follows: existing security algorithms in IoT are discussed in Section 2. The suggested enhanced security algorithm is presented in Section 3. Implementation detail and results analysis is covered in Section 4. Section 5 concludes the research with future directions. 2. Related Works The major objective of the following literature study is to bring attention to different issues and shortcomings with the existing encryption and decryption approaches. It also includes the current encryption and decryption algorithms used in the Internet of Things. A methodology of offering a combined approach of data compression and encryption is developed (Rafidha et al., 2017) in order to safeguard data with less bandwidth. Its three processes are encryption, compression, and decryption. The ECC algorithm was used to encrypt and decrypt data, and the Huffman encoding algorithm was used to compress data. The steps involved in the encryption process are: reading the message, converting it to ASCII code, converting ASCII to 7-bit binary values, performing multiplication, selecting an elliptic curve, creating a public key, substituting values, and then converting the message into cipher text. Finally, the cipher text and public key are sent for decryption. A multilayer encryption technique (Vithya et al., 2018) was presented to increase the security of IoT data utilizing encryption to make the data more secure. This technique is based on the Merkle-Hellman Knapsack (MHK) cryptosystem with Elliptic Curve Cryptography. In this model, data from the IoT device will be sent to gateway and transmitted to server. However before sending data to the server, Multilevel encryption technique is applied to make data more secure. The proposed multilevel encryption technique performs encryption in two steps, i.e. given plain text is separated into characters that are converted into equivalent binary values and then encrypted through MHK encryption technique. The second stage further encrypts the decoded text using elliptic curve encryption to increase security. Simulation tests revealed that multilayer encryption improves data security compared to other systems, although it is slower to use when encrypting data. The RSA key generation algorithm (Thangavel et al., 2015), ESRKGS, is a modified and improved scheme based on RSA public key cryptosystem. It uses four prime numbers instead of two prime numbers that increases the security level and not easy to break as compared to the traditional RSA algorithm. This algorithm consists of three steps that include Key Generation, Key Encryption and Key Description. However, there are some limitations in this study such as the proposed algorithm takes more time for key generation, encryption and decryption. A Novel Tiny Symmetric Algorithm (NTSA) suggested (Rajesh et al., 2019) to improve the security of text file transfer across IoT networks by securing data. There are 32 cycles, each of which has two rounds (i.e. total 64 rounds). Each cycle utilizes a unique key that is either a 64 or 128-bit plain key. Although performance is good but it can be further improved by encrypting the compressed file for data transfer in ad hoc, sensor and fog networks. A hybrid model to secure data on IoT devices before the data is sent to the server through a hybrid encryption model was proposed in (Asang et al., 2018). It consists of two main processes, key distribution and data encryption. The ECDH algorithm is used for key distribution, and the AES technique is utilized for data encryption. ECDH generates the secret key known to device and server while AES secure the data before it sent to the server. The main purpose of distinguishing private keys is to prevent unauthorized parties from generating the same secret key to all devices. The main issue with this algorithm is the static private key and public key management. Moreover, this model is still vulnerable to MITM attacks especially when network layer security is poor. A hybrid encryption approach to take a brief overview of RSA algorithm for the security of communication over internet is suggested (Krishna et al., 2019) that comprises of three modules, i.e. password generation, validation, and finally RSA algorithm is used. The data is encrypted and send to the receiver where message is decrypted through private key. The main issue with this approach is that the plaintext is easily recoverable by taking the eth roots of the corresponding integer equation, using the same number to create a public key by two people who receive the same message, and if both encryption keys are correspond, then it is very simple for a third party to decrypt the message. An upgraded RSA algorithm is proposed (Raghunandan et al., 2019) which improves the factorization process complexity by using counterfeit public key exponent type "f" rather than "e" and counterfeit modulus "X" rather than "n" such that the algorithm evade the limitations of Integer factorization attack. It was observed that initially the encryption and decryption time for both algorithms is same. However, the difference between consumed times is increased rapidly for lower bit prime numbers with increase of bit length. The histogram analysis of proposed method shows each letter has equal probability and equally distributed by making attacker difficult to guess the plaintext. Four prime numbers are used in this research that’s why it is more secure than the normal RSA. One major issue with this technique is that when one bit flips in the public key while applying the avalanche effect, it is impossible to decrypt the cipher text in order to recover the original plain text. A secure data transmission mechanism (Deepika et al., 2017) was introduced which improves the security of data during transmission by using AES algorithm. As security risks increases with the number of devices that's why data transmission is more difficult task. The results show that the proposed mechanism is more secure as there are a greater number of rounds with compare to other algorithms and throughput of proposed scheme is high than other algorithms (Without AES). The suggested approach has various drawbacks, such as a longer execution time, which must be addressed. The end-to-end delay of secure data transmission is the other issue that can be resolved in the future. A lightweight combined system (Tenzin et al., 2018) using ECDH key exchange technique for generating keys and setting up connections was proposed that uses digital signature for certification, and AES algorithm for Encryption and Decryption. It works through two main steps, first Key Generation and Exchange where each device generates its own public and private keys, then both devices interchange public keys over public network. After this both devices calculate own secret key S by calculating with own private and public key of another device. Second, authentication is performed using digital signature (ECDSA). The results show that the proposed model provides better security with less cost and faster speed. In future, the proposed model can be implemented in IoT real-time application to check the strength of the proposed hybrid algorithm. A composite cryptographic technique (Kavitha et al., 2019) was presented to deal in more skilful way with different security attacks, to provide more security in IoT health care system. The proposed hybrid cryptographic system named as (AES_DH) HC is a composition of Hessian Curve (HC) cryptography, Diffie Hellman (DH) algorithm and Advance Encryption Standard 128 bits (AES) algorithm. Experimental analysis shows that it requires minimum time to encrypt and decrypt the message as compared to other algorithms. It achieves minimum average data rate and throughput as compared to individual algorithms. From the results it was observed that the proposed algorithm handles different security attacks in much better way. Due to this reason, the proposed algorithm is more secure as compare to other individual algorithms like AES, DH and ECDH etc. A new architecture for determining roles and design permissions‟ protocols in IoT was presented (Novo et al., 2018). The architecture is a distributed access control system for IoT based blockchain technology. A hierarchical structure and distributed trust model was proposed (Dorri et al., 2017) in order to maintain the blockchain security, privacy and make it suitable for the IoT. In another attempt, a light weight blockchain based architecture was suggested (Dorri et al., 2017) to deal with validation delay in IoT network. The proposed technique virtually eliminates the overheads of classic blockchain. It takes benefits from the private immutable ledger and IoTs. In another article (Dorri et al., 2019), optimized the lightweight scalable blockchain for IoT requirements by using the the clustering technique, where IoT devices maintain an overlay network and jointly manage the blockchain of devices. The overlay clusters reduce the overhead and cluster head has the responsibility for managing the public blockchain. A number of encryption techniques, including RSA, AES, DES, Merkle Hellman, and ECC, are available to protect data from unauthorized access. However, each of these methods has some drawbacks related to time, power, and storage requirements (Kalaiselvi, 2015). RSA, also known as a public key algorithm, is a modified encryption method that is widely used throughout the world to provide security through the encryption of data. Although the RSA's security depends on the size of its key, a longer key will provide more protection. The key bulk is determined by the bulk of the prime numbers used in factorization. But the problem is that as the factorization increases the computation cost also increases. AES (Advance Encryption Standard) is a symmetric key algorithm, that works on 4x4 array of 128 bits. Encryption and decryption, consists of four steps that repeat over a certain number of orbits depending on the key size. These steps repeated in the form of rounds and length of key determines number of rounds e.g. ten rounds in case of key with 128 bits, twelve rounds for 192 and so on. Similar to the RSA, AES also have some flaws such as processing overhead, a fixed S-Box, and other issues. Another symmetric key algorithm is data encryption standard (DES) which take a 64-bit block as input for encryption and yield 8-byte block as output. DES uses a 56-bit key due to security issues. In Merkle Hellman, asymmetric key cryptographic algorithm, there will be two distinct keys for encoding and decoding. It is based on subset sum problem in which there are two set of numbers, subset of one set sum to the other set. The primary issue with Merkle Hellman is the super-increasing order, which causes the cryptosystem to become redundant. Elliptic curve cryptography is a deviated key cryptography dependent on the elliptic hypothesis. Key created in ECC is from the elliptic bend condition rather than result of enormous indivisible numbers. The ECC is more effective and secure when compared to other cryptographic methods like RSA, AES, DES, and Merkle Hellman, etc. According to numerous studies, ECC offers a level of security with a 20.5-byte key, whereas other methods require a 128-byte key to provide the same level of security. In addition, there are several problems with ECC that need to be fixed. In order to increase the security of IoT data, the proposed research assessed the available encryption methods and suggests an improved encryption algorithm where the integrity of IoT data will be the primary emphasis. 3. Enhanced Rsa Algorithm For Iot After finding and analyzing above deficiencies which exist in current encryption algorithms, the proposed research will improve the security of IoT data by using improved encryption algorithms in terms of resource consumption. The proposed encryption algorithm will improve and enhance the data security of IoT during transmission of data from one device to other. Before the transmission of data, any external source that will enter in the network will be authenticated using the blockchain. For this purpose, we will use smart contract, the smart contract is a record of computer programs or transactions that seek to automatically process, control or document events and actions that are legally significant under the terms of a contract or agreement. By using the contract external attacks can be minimized in the initial stages. However, secure transmission of the data required high level security measurements. In this regard, the proposed encryption algorithm will be an enhanced form of RSA algorithm which will protect data from different factorization attacks with less execution time as compared to the traditional RSA algorithm. The proposed algorithm working hierarchy is shown in Figure 3.1. In typical RSA sending public key e legitimately help interloper to get d, since „e‟ is co-prime of Ø (n). It is expected to substitute „e‟ for higher security. With the goal that it is hard to track down private key. Proposed System utilizes extra 2 factors in key generation process (f, g) which supplant public key „e‟ and private key „d‟, where „f‟ is the increase of „e‟ and „g‟ is division of „d‟. This calculation conceals the public key „e‟ from the interloper. Furthermore, this calculation likewise utilizes five prime numbers to ascertain modulus „n‟ which will be hard to processing plants Abbreviations and Acronyms. Proposed algorithm comprises of three main parts i.e. Key Generation, Encryption and Decryption. 3.1 Key Generation Perform following steps after assuming five (5) prime numbers i.e. p1, q1, r1, s1, t1, where p1 ≠ q1 ≠ r1 ≠ s1 ≠ t1. Calculate the modulus n by multiplying the prime factors i.e. n = p1xq1xr1xs1x t1. Calculate the Euler Totient φ (n) by using formula φ (n) = (p1-1)x(q1-1)x(r1-1) x(s1-1)x(t1-1). Public key exponent e is calculated using gcd (e, φ (n)) = 1 and it should lie in between 1 < e < φ (n). Find private key exponent d which satisfies the equation (e * d) mod φ (n) =1. Continue the above process if d is not prime otherwise select another e and d. Using equation d mod k = 0, find an integer k which satisfies the equation (d mod k = 0). Find phony public key exponent „f‟ using equation f = e*k. Find phony private key exponent g using equation g = d/k. Obtain phony modulus using equation (e*d) mod φ(X) = 1. 3.2 Encryption Before being sent to the sender, the plain text (PT) will be encrypted using the key pairs (f, X) and the formula CT = (PT)f mod X. 3.3 Decryption When the encoded content (CT) reached, the recipient computes original content (PT) by utilizing private key set (y1, pk) and formula PT = (CT)y1 Mod Z. 3.4 Example: Assume five prime numbers i.e. 2, 3, 5, 7, 11. Compute module N = 2 x 3 x 5 x 7 x 11 = 2310. Calculate Phi (N): Φ (N) = (2-1) x (3-1) x (5-1) x (7-1) x (11-1). Phi (N) = 1 x 2 x 4 x 6 x 10 = 480 Calculate the open key exponent “oe1” Gcd (oe1, 480) =1 & 1<oe1<480. So oe1=47. Calculate private key exponent “pd1”. (oe1 * pd1) mod Phi (N) =1 (47 * pd1) mod 480 = 1, so pd1 = 143. Calculate integer “pk”: 143 mod k = 0, So pk = 11 Calculate fake public key exponent” x1”: x1= oe1 * pk, x1 = 47 * 11, so x1 = 517 Calculate bogus secretive key exponent “y1”: y1 = pd1 / pk, y1 = 143 / 11, so y1 = 13 Find insincere module “Z”: (47 * 143) mod Phi (Z) = 1, So Z = 3361 So, the public key will be (517, 3361) and the private key will be (13, 3361). Let PT = 123 be the plain text for encryption sender will encrypt this plain text in cipher text CT by using formula: CT = (PT)x1 mod Z CT = (123)517 mod 3361 CT = 504 § Receiver will decrypt the plain text PT by using formula: PT = (CT)y1 mod Z. PT = (504)13 mod 3361 PT = 123 4. Implementation And Results The proposed improved RSA algorithm is implemented in C++ using Visual Studio (Professional 2012). The source code of the proposed algorithm is executed on an Intel(R) Core (TM) i3-3217U CPU running at 4.0 GHz, 1.80 GHz, and 4 GB of RAM. The algorithm's output was evaluated in terms of key generation, encryption, and decryption using a variety of inputs. Various inputs were offered to assess the effectiveness of the suggested algorithm. Table 4.1 displays the outcomes of the proposed algorithm's various stages, such as Time to Create Key, Message Encoding, and Decoding Time. The output data for the RSA algorithms created by (Rivest et al., 1978) and (Ivy et al., 2012) are shown in Tables 4.2 and 4.3, respectively. These tables demonstrate that, compared to the other two RSA methods, RSA by (Rivest et al., 1978) and (Ivy et al., 2012), which use two, three, or four prime numbers, respectively, the suggested method requires a little more time to create keys. The increase in key generation time is due to the use of more primes in the key delivery process as well as the presentation of the complexity of factorization handling through the use of a phony open key exponent type of "x1" in place of "oe1" and a phony module of "Z" in place of "N." Figures 8 and 9 show a comparison of the RSA (Rivest et al., 1978) and (Ivy et al., 2012) recommended techniques for encoding and unscrambling data. These figures show that the predicted technique requires less time than RSA (Ivy et al., 2012)) to encode and decode the message, but more time than RSA (By Rivest et al., 1978)). The proposed approach takes longer time to encrypt and decrypt data than the RSA (Rivest et al., 1978) because it uses five prime numbers as compared to two. However, the increased security, which is more crucial than time, makes this increase tolerable. Following tables 4.1-3 show that, for instance, the proposed algorithm takes 0.01495 seconds for encryption and 0.014 seconds for decryption when the length of the primes is 0.064 Kb, whereas RSA (Rivest et al., 1978) takes 0.003 seconds for encryption and also for decryption, which is quicker than the proposed algorithm. On the other hand, RSA (Ivy et al., 2012) takes 0.021 seconds and 0.023 sec for encryption and decryption which is slighter higher than proposed algorithm. Table 1. Performance of Proposed Algorithm (Enhanced RSA Algorithm) Primes Size (in kb) Time in Second Key Creation time Encoding time Decoding time Execution time 0.0125 0.115 0.0013 0.00125 0.1175 0.016 0167 0.00182 0.00134 0.17016 0.032 0.24 0.00273 0.00143 0.24416 0.064 0.393 0.01495 0.014 0.42195 0.128 1.175 0.10423 0.1036 1.38283 Table 2. Performance of RSA (Rivest et al., 1978) Primes Size (in kb) Time in Second Key Creation time Encoding time Decoding time Execution time 0.0125 0.072 0.001 0.001 0.074 0.016 0.092 0.0011 0.0011 0.0942 0.032 0.133 0.001 0.0011 0.1351 0.064 0.352 0.003 0.003 0.358 0.128 0.889 0.021 0.022 0.932 Table 3. Performance of RSA (Ivy et al., 2012) Primes Size (kb) Time in Second Key generation time Encryption time Decryption time Execution time 0.0125 0.110 0.002 0.0017 0.1137 0.016 0.144 0.0025 0.0022 0.1487 0.032 0.216 0.004 0.003 0.223 0.064 0.313 0.021 0.023 0.357 0.128 0.922 0.170 0.169 1.261 The proposed algorithm is more secure than the standard RSA technique. Factorization of modulus "N" is a method for weakening the security of RSA, and although the security of the proposed technique is harder to break than that of standard RSA for two reasons: It uses five prime numbers, which takes longer to factorize the modulus "n" than the standard RSA, which uses only two primes. Another feature that protect the proposed algorithm from factorization attacks is the use of phony exponents and a fictitious module. Therefore, the suggested algorithm is more secure than a normal RSA. 5. Conclusion And Future Work The most important step in protecting customer data from unauthorized parties is the encryption architecture. There are various encryption algorithms available today, but RSA is a very important and widely used one. In this study, we examined the shortcomings of the existing encryption and decryption algorithms. We have suggested an improved version of the RSA algorithm to safeguard data. Two additional features of this approach include the discovery of module "N" using five prime numbers and the disposal of module "N" and open key expounder "oe1" in favor of bogus module "Z" and false open key expounder "x1" in standard RSA. Greater safety would be attained using the "addition of two attributes" technique by reducing the time required for encoding and unscrambling. Here, a minor adjustment to the open key is recommended in order to make use of the Avalanche impact, which can only decode encoded content and cannot retrieve reversed content. The suggested methodology lessens the likelihood of numerical attacks by providing extra protection in exchange for a slight increase in length sophistication. Despite the fact that the proposed methodology uses a protected code framework and a limited level of safety, it is designed to encourage more resistance than the RSA algorithm. The proposed algorithm can be improved by reducing the execution time and enhanced in security for IoT. Declarations Availability of data and material – Not applicable Competing interests – The authors declare no conflict of interest. Funding – Currently, we don’t have any funding. Authors' contributions – Conceptualization, B.U.; methodology, A.M and R.A.; software, B.U. and M.J.; validation, B.U., M.J. and A.M.; investigation, A.K.; resources, A.M.; writing—original draft preparation, A.M., A.K. and S.U.; writing—review and editing, A.M., A.K., R.A..; visualization, S.U; supervision, A.M., A.K; project administration, A.M. and S.U. Consent for publication – All authors have read and agreed to the published version of the manuscript. Acknowledgements – N.A. References Asang, S. Manongga D., Sembiring, I. (2018). Data Security on Internet of Things Device Using Hybrid Encryption Models. International Journal of Computer Science and Information Security, 16(8), 93-103. Deepika K., & Poonam D., (2017). Secure Data Transmission using AES in IoT. International Journal of Application or Innovation in Engineering & Management (IJAIEM), 6(6), 283-289. Dorri, A., Kanhere, S. S., Jurdak, R., & Gauravaram, P. (2017). 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V., Khosravi R., M., (2019). A Secure and Efficient Light weight Symmetric Encryption Scheme for Transfer of Text Files between Embedded IoT Devices. An Article, 1-21. Rivest, R. L., Shamir, A., & Adleman, L. (1978). A method for obtaining digital signatures and public-key cryptosystems. Communications of the ACM, 21(2), 120-126. Surendran, S., Nassef, A., & Beheshti, B. D. (2018). A survey of cryptographic algorithms for IoT devices 2018 IEEE Long Island Systems, Applications and Technology Conference. Tenzin, K. Kirubanand V. B., (2018) A lightweight hybrid encryption technique to secure IoT data transmission. International Journal of Engineering & Technology 7(2.6):236. Thangavel, M., Varalakshmi, P., Murrali, M., & Nithya, K. (2015). An Enhanced and Secured RSA Key Generation Scheme (ESRKGS). Journal of Information Security and Applications, 20, 3–10. Vithya A., Arockiam L., (2018). ARO_EDGE: A Technique to Ensure Data Security in Internet of Things (IoT). 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1896185","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":128332293,"identity":"9588fd1b-f34e-416a-baba-abb0b788debb","order_by":0,"name":"Bashart Ullah","email":"","orcid":"","institution":"Federal Urdu University of Arts Science and Technology - Islamabad Campus","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bashart","middleName":"","lastName":"Ullah","suffix":""},{"id":128332294,"identity":"865bdf0f-67a2-44b4-9b28-b87af40aef39","order_by":1,"name":"Abdul Mateen","email":"data:image/png;base64,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","orcid":"","institution":"Federal Urdu University of Arts Science and Technology - Islamabad Campus","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Abdul","middleName":"","lastName":"Mateen","suffix":""},{"id":128332295,"identity":"f891f5ef-adaf-4847-bf7e-872d091b68bb","order_by":2,"name":"Adia Khalid","email":"","orcid":"","institution":"COMSATS University Islamabad","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Adia","middleName":"","lastName":"Khalid","suffix":""},{"id":128332296,"identity":"9eb3fe23-dd64-4efc-9a47-882a4c5eb2b1","order_by":3,"name":"Saeed Ullah","email":"","orcid":"","institution":"Federal Urdu University of Arts Science and Technology - Islamabad Campus","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Saeed","middleName":"","lastName":"Ullah","suffix":""},{"id":128332297,"identity":"89bbf157-d50c-435a-8eaf-4f934685c9a8","order_by":4,"name":"Rubina Adnan","email":"","orcid":"","institution":"COMSATS University Islamabad","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Rubina","middleName":"","lastName":"Adnan","suffix":""},{"id":128332298,"identity":"6c64e8e8-d902-4234-b190-d88e32c4556b","order_by":5,"name":"Javed Iqbal","email":"","orcid":"","institution":"University of Peshawar","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Javed","middleName":"","lastName":"Iqbal","suffix":""}],"badges":[],"createdAt":"2022-07-26 05:51:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1896185/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1896185/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":25272356,"identity":"ac441f59-08dc-4f49-83a6-e75099790a0c","added_by":"auto","created_at":"2022-08-16 15:57:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":133641,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 1.1 – IoT Layers\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-1896185/v1/b14b43413b697fa86f75dd95.png"},{"id":25272354,"identity":"2645138d-2221-4d17-8424-f8a508178435","added_by":"auto","created_at":"2022-08-16 15:57:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":68192,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 1.2 – Symmetric Key Cryptography\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-1896185/v1/0c692acd203db621c925ccc7.png"},{"id":25272751,"identity":"ddd79c40-11c8-4c80-9c81-73ae5af4d939","added_by":"auto","created_at":"2022-08-16 16:02:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":73356,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 1.3 – Asymmetric Key Cryptography\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-1896185/v1/5e0e3121412734764add9341.png"},{"id":25272350,"identity":"4a04b68f-b115-4460-ad3d-8dd0a2563b11","added_by":"auto","created_at":"2022-08-16 15:57:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":27448,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 1.4 – Hash Function\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-1896185/v1/0258099a65bc1bd498678872.png"},{"id":25272353,"identity":"aa93d422-27b0-435c-9cba-aac73b261111","added_by":"auto","created_at":"2022-08-16 15:57:23","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":78310,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 3.1. Detailed Steps of the Proposed Algorithm\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-1896185/v1/9a6f62d7f9c7a63ab311bfe9.png"},{"id":25272352,"identity":"ca634cf6-2d88-4471-9901-ea08d48ced2b","added_by":"auto","created_at":"2022-08-16 15:57:23","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":70559,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 4.1. Comparison of Encryption Time\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-1896185/v1/77876483521f9d66083c674b.png"},{"id":25272355,"identity":"9bdd6def-f256-4343-b337-ac5c0028e3fa","added_by":"auto","created_at":"2022-08-16 15:57:23","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":66934,"visible":true,"origin":"","legend":"\u003cp\u003eFigure 4.2. Comparison of Decryption Time\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-1896185/v1/5ad744a8945556e7f2d1af01.png"},{"id":26093605,"identity":"707aaafc-fdbc-4ba0-904c-66bd50723576","added_by":"auto","created_at":"2022-09-06 06:39:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":869868,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1896185/v1/7dea1fe8-dd82-4e98-bad6-b60d047ef95d.pdf"}],"financialInterests":"","formattedTitle":"Enhanced RSA Algorithm for Data Security in the Internet of Things","fulltext":[{"header":"1.\tIntroduction And Background","content":"\u003cp\u003eThe Internet of Things (IoT) is a network of connected items, including computers, robots, mobiles and other devices. All of the devices have some electronic, software, sensor, and network connectivity built in, and they all have unique identifiers that allow them to communicate with one another and send and receive various types of information. The IoT can include any device that is capable of receiving an IP address and using that address to communicate with other items online. These devices are capable of observing their surroundings, gathering information from it, and transmitting it to other items. With the rapid expansion of IoT, life has become increasingly fictitious, similar to living in a virtual environment. IoT\u0026apos;s idea of linking everything to the internet results in the production of a large amount of data known as big data. The idea of big data is further divided into its capacity, which refers to how much room is needed for data collection, its rate of data generation, and its assortment. Since IoT offers access to everything from anywhere at any time, security is a significant barrier that need to be enhanced.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe IoT has a three-layer architecture: sensing, network, and application layer as seen in Figure. 1.1. The Sensing layer is a physical layer that is connected up with various sensors, including RFID, WSN, GPS, NFC, and cameras etc. These sensors sense and compile a variety of environmental data. In addition, it is responsive for converting data into sophisticated signals that are easily transmitted via a network. The Network layer, also known as the Transport layer, is able to prepare data obtained from the Recognition layer. It is also capable of transferring data to the application layer using various technology advancements, including wired, wireless, and local area networks. The most common transmission mediums include 4G, 5G, Wi-Fi, Bluetooth, and infrared technologies etc. The application layer makes use of the data that was handled by prior layers. It conveys to the client the particular advantages of any program. It describes several applications for the IoT, such as smart grids, smart cities, and wearable health monitoring.\u003c/p\u003e\n\u003cp\u003eDue to their connectedness with one another in IoT, gadgets and other objects provide similar challenges to new clients in terms of authentication [1]. In addition, primary concerns with IoT data security include confidentiality, integrity and authentication. A crucial component of IoT security is data confidentiality, which specifies that only individuals with permission can access the data or information. Data integrity guarantees that the information or data is complete and original throughout its lifecycle, including when it was sent and received, etc. When data or information is transferred between different devices or things, it can be altered. In IoT, there are different devices that communicate with one another. As a result, these devices should be able to authenticate one another in order to ensure that the device providing or accessing sensitive information or data is a legitimate party.\u003c/p\u003e\n\u003cp\u003eOne approach of information protection, among many others, is cryptography. The name \u0026quot;cryptography\u0026quot; derives from the Greek words kryptos, which means \u0026quot;hidden,\u0026quot; and graphien, which means \u0026quot;to write.\u0026quot; By utilizing encryption, a plain text can be transformed into an intangible text. Encryption is used to send data in a format that only the intended receivers can read and understand. There are typically three categories of cryptography, which are Symmetric Key Cryptography, Asymmetric Key Cryptography and hashing. In case of Symmetric Key, only one key is utilized for both encoding and decoding of content by dispatcher and recipient as shown in Figure 1.2. Symmetric key cryptography is faster and simpler if the key exchange between the sender and receiver is secure. Most widely used symmetric key cryptography algorithms are Data Encryption Standard (DES), AES, etc.\u003c/p\u003e\n\u003cp\u003eAsymmetric key cryptography, also known as open key cryptography, encrypts and decrypts data using two keys (public and private) as shown in Figure 1.3. Everyone has access to the open key, but only the message\u0026apos;s intended recipient has access to the private key, which is used to decode it. RSA Algorithm, Digital Signature Algorithm and Elliptic Curve Cryptography are common types of asymmetric cryptography.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA hash function is a type of cryptographic operation that accepts input (any size) and generates predetermined size output. It is comparable to a scientific condition that takes numbers from input and produces a hash as a result. It operates on two blocks and doesn\u0026apos;t require a key. A binary block is used as the input, and the result is a hashing code. Hashing functions comprises of different rounds, mixture of the latest block and the product of previous round is used as an input for a round in hash function, as shown in Figure 1.4. Message Digest 5, Secure Hash Algorithm, and whirlpool are some popular Hash functions.\u003c/p\u003e\n\u003cp\u003eIn 2020, there were around 50 billion IoT devices, which demonstrates the importance of this technology in human life. IoT does, however, confront some difficulties, one of which is the privacy and security of the data produced. According to a HP survey, 60% of IoT devices have security flaws, and 70% of IoT devices failed to encrypt data during data transmission. As is common knowledge, there are numerous groups attempting to improve the data security of IoT and a variety of encryption techniques are available. However, there is still a lot of work to be done to enhance the security. The main objectives of the proposed research are:\u003c/p\u003e\n\u003cul type=\"square\"\u003e\n \u003cli\u003eIdentification of the flaws in the current IoT data security algorithms.\u003c/li\u003e\n \u003cli\u003eIncrease the security of IoT data through improved encryption algorithms.\u003c/li\u003e\n \u003cli\u003eSuggest the optimal encryption technique for the IoT in terms of resource usage.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe rest of the article is organized as follows: existing security algorithms in IoT are discussed in Section 2. The suggested enhanced security algorithm is presented in Section 3. Implementation detail and results analysis is covered in Section 4. Section 5 concludes the research with future directions.\u003c/p\u003e"},{"header":"2. Related Works","content":"\u003cp\u003eThe major objective of the following literature study is to bring attention to different issues and shortcomings with the existing encryption and decryption approaches. \u0026nbsp;It also includes the current encryption and decryption algorithms used in the Internet of Things.\u003c/p\u003e\n\u003cp\u003eA methodology of offering a combined approach of data compression and encryption is developed (Rafidha et al., 2017) in order to safeguard data with less bandwidth. Its three processes are encryption, compression, and decryption. The ECC algorithm was used to encrypt and decrypt data, and the Huffman encoding algorithm was used to compress data. The steps involved in the encryption process are: reading the message, converting it to ASCII code, converting ASCII to 7-bit binary values, performing multiplication, selecting an elliptic curve, creating a public key, substituting values, and then converting the message into cipher text. Finally, the cipher text and public key are sent for decryption.\u003c/p\u003e\n\u003cp\u003eA multilayer encryption technique (Vithya et al., 2018) was presented to increase the security of IoT data utilizing encryption to make the data more secure. This technique is based on the Merkle-Hellman Knapsack (MHK) cryptosystem with Elliptic Curve Cryptography. In this model, data from the IoT device will be sent to gateway and transmitted to server. However before sending data to the server, Multilevel encryption technique is applied to make data more secure. The proposed multilevel encryption technique performs encryption in two steps, i.e. given plain text is separated into characters that are converted into equivalent binary values and then encrypted through MHK encryption technique. The second stage further encrypts the decoded text using elliptic curve encryption to increase security. Simulation tests revealed that multilayer encryption improves data security compared to other systems, although it is slower to use when encrypting data.\u003c/p\u003e\n\u003cp\u003eThe RSA key generation algorithm (Thangavel et al., 2015), ESRKGS, is a modified and improved scheme based on RSA public key cryptosystem. It uses four prime numbers instead of two prime numbers that increases the security level and not easy to break as compared to the traditional RSA algorithm. This algorithm consists of three steps that include Key Generation, Key Encryption and Key Description. However, there are some limitations in this study such as the proposed algorithm takes more time for key generation, encryption and decryption.\u003c/p\u003e\n\u003cp\u003eA Novel Tiny Symmetric Algorithm (NTSA) suggested (Rajesh et al., 2019) to improve the security of text file transfer across IoT networks by securing data. There are 32 cycles, each of which has two rounds (i.e. total 64 rounds). \u0026nbsp;Each cycle utilizes a unique key that is either a 64 or 128-bit plain key. Although performance is good but it can be further improved by encrypting the compressed file for data transfer in ad hoc, sensor and fog networks.\u003c/p\u003e\n\u003cp\u003eA hybrid model to secure data on IoT devices before the data is sent to the server through a hybrid encryption model was proposed in (Asang et al., 2018). It consists of two main processes, key distribution and data encryption. The ECDH algorithm is used for key distribution, and the AES technique is utilized for data encryption. ECDH generates the secret key known to device and server while AES secure the data before it sent to the server. The main purpose of distinguishing private keys is to prevent unauthorized parties from generating the same secret key to all devices. The main issue with this algorithm is the static private key and public key management. Moreover, this model is still vulnerable to MITM attacks especially when network layer security is poor.\u003c/p\u003e\n\u003cp\u003eA hybrid encryption approach to take a brief overview of RSA algorithm for the security of communication over internet is suggested (Krishna et al., 2019) that comprises of three modules, i.e. password generation, validation, and finally RSA algorithm is used. The data is encrypted and send to the receiver where message is decrypted through private key. The main issue with this approach is that the plaintext is easily recoverable by taking the eth roots of the corresponding integer equation, using the same number to create a public key by two people who receive the same message, and if both encryption keys are correspond, then it is very simple for a third party to decrypt the message.\u003c/p\u003e\n\u003cp\u003eAn upgraded RSA algorithm is proposed (Raghunandan et al., 2019) which improves the factorization process complexity by using counterfeit public key exponent type \u0026quot;f\u0026quot; rather than \u0026quot;e\u0026quot; and counterfeit modulus \u0026quot;X\u0026quot; rather than \u0026quot;n\u0026quot; such that the algorithm evade the limitations of Integer factorization attack. It was observed that initially the encryption and decryption time for both algorithms is same. However, the difference between consumed times is increased rapidly for lower bit prime numbers with increase of bit length. The histogram analysis of proposed method shows each letter has equal probability and equally distributed by making attacker difficult to guess the plaintext. Four prime numbers are used in this research that\u0026rsquo;s why it is more secure than the normal RSA. One major issue with this technique is that when one bit flips in the public key while applying the avalanche effect, it is impossible to decrypt the cipher text in order to recover the original plain text.\u003c/p\u003e\n\u003cp\u003eA secure data transmission mechanism (Deepika et al., 2017) was introduced which improves the security of data during transmission by using AES algorithm. As security risks increases with the number of devices that\u0026apos;s why data transmission is more difficult task. The results show that the proposed mechanism is more secure as there are a greater number of rounds with compare to other algorithms and throughput of proposed scheme is high than other algorithms (Without AES). The suggested approach has various drawbacks, such as a longer execution time, which must be addressed. The end-to-end delay of secure data transmission is the other issue that can be resolved in the future.\u003c/p\u003e\n\u003cp\u003eA lightweight combined system (Tenzin et al., 2018) using ECDH key exchange technique for generating keys and setting up connections was proposed that uses digital signature for certification, and AES algorithm for Encryption and Decryption. It works through two main steps, first Key Generation and Exchange where each device generates its own public and private keys, then both devices interchange public keys over public network. After this both devices calculate own secret key S by calculating with own private and public key of another device. Second, authentication is performed using digital signature (ECDSA). The results show that the proposed model provides better security with less cost and faster speed. In future, the proposed model can be implemented in IoT real-time application to check the strength of the proposed hybrid algorithm.\u003c/p\u003e\n\u003cp\u003eA composite cryptographic technique (Kavitha et al., 2019) was presented to deal in more skilful way with different security attacks, to provide more security in IoT health care system. The proposed hybrid cryptographic system named as (AES_DH) HC is a composition of Hessian Curve (HC) cryptography, Diffie Hellman (DH) algorithm and Advance Encryption Standard 128 bits (AES) algorithm. Experimental analysis shows that it requires minimum time to encrypt and decrypt the message as compared to other algorithms. It achieves minimum average data rate and throughput as compared to individual algorithms. From the results it was observed that the proposed algorithm handles different security attacks in much better way. Due to this reason, the proposed algorithm is more secure as compare to other individual algorithms like AES, DH and ECDH etc.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA new architecture for determining roles and design permissions‟ protocols in IoT was presented (Novo et al., 2018). The architecture is a distributed access control system for IoT based blockchain technology. A hierarchical structure and distributed trust model was proposed (Dorri et al., 2017) in order to maintain the blockchain security, privacy and make it suitable for the IoT. In another attempt, a light weight blockchain based architecture was suggested (Dorri et al., 2017) to deal with validation delay in IoT network. The proposed technique virtually eliminates the overheads of classic blockchain. It takes benefits from the private immutable ledger and IoTs. In another article (Dorri et al., 2019), optimized the lightweight scalable blockchain for IoT requirements by using the the clustering technique, where IoT devices maintain an overlay network and jointly manage the blockchain of devices. The overlay clusters reduce the overhead and cluster head has the responsibility for managing the public blockchain.\u003c/p\u003e\n\u003cp\u003eA number of encryption techniques, including RSA, AES, DES, Merkle Hellman, and ECC, are available to protect data from unauthorized access. However, each of these methods has some drawbacks related to time, power, and storage requirements (Kalaiselvi, 2015). RSA, also known as a public key algorithm, is a modified encryption method that is widely used throughout the world to provide security through the encryption of data. \u0026nbsp;Although the RSA\u0026apos;s security depends on the size of its key, a longer key will provide more protection. The key bulk is determined by the bulk of the prime numbers used in factorization. But the problem is that as the factorization increases the computation cost also increases. AES (Advance Encryption Standard) is a symmetric key algorithm, that works on 4x4 array of 128 bits. Encryption and decryption, consists of four steps that repeat over a certain number of orbits depending on the key size. These steps repeated in the form of rounds and length of key determines number of rounds e.g. ten rounds in case of key with 128 bits, twelve rounds for 192 and so on. Similar to the RSA, AES also have some flaws such as processing overhead, a fixed S-Box, and other issues. Another symmetric key algorithm is data encryption standard (DES) which take a 64-bit block as input for encryption and yield 8-byte block as output. DES uses a 56-bit key due to security issues. In Merkle Hellman, asymmetric key cryptographic algorithm, there will be two distinct keys for encoding and decoding. It is based on subset sum problem in which there are two set of numbers, subset of one set sum to the other set. The primary issue with Merkle Hellman is the super-increasing order, which causes the cryptosystem to become redundant. Elliptic curve cryptography is a deviated key cryptography dependent on the elliptic hypothesis. Key created in ECC is from the elliptic bend condition rather than result of enormous indivisible numbers. The ECC is more effective and secure when compared to other cryptographic methods like RSA, AES, DES, and Merkle Hellman, etc. According to numerous studies, ECC offers a level of security with a 20.5-byte key, whereas other methods require a 128-byte key to provide the same level of security. In addition, there are several problems with ECC that need to be fixed. In order to increase the security of IoT data, the proposed research assessed the available encryption methods and suggests an improved encryption algorithm where the integrity of IoT data will be the primary emphasis.\u003c/p\u003e"},{"header":"3.\tEnhanced Rsa Algorithm For Iot","content":"\u003cp\u003eAfter finding and analyzing above deficiencies which exist in current encryption algorithms, the proposed research will improve the security of IoT data by using improved encryption algorithms in terms of resource consumption. The proposed encryption algorithm will improve and enhance the data security of IoT during transmission of data from one device to other. Before the transmission of data, any external source that will enter in the network will be authenticated using the blockchain. For this purpose, we will use smart contract, the smart contract is a record of computer programs or transactions that seek to automatically process, control or document events and actions that are legally significant under the terms of a contract or agreement. By using the contract external attacks can be minimized in the initial stages. However, secure transmission of the data required high level security measurements. In this regard, the proposed encryption algorithm will be an enhanced form of RSA algorithm which will protect data from different factorization attacks with less execution time as compared to the traditional RSA algorithm. The proposed algorithm working hierarchy is shown in Figure 3.1.\u003c/p\u003e\n\u003cp\u003eIn typical RSA sending public key e legitimately help interloper to get d, since \u0026bdquo;e‟ is co-prime of \u0026Oslash; (n). It is expected to substitute \u0026bdquo;e‟ for higher security. With the goal that it is hard to track down private key. Proposed System utilizes extra 2 factors in key generation process (f, g) which supplant public key \u0026bdquo;e‟ and private key \u0026bdquo;d‟, where \u0026bdquo;f‟ is the increase of \u0026bdquo;e‟ and \u0026bdquo;g‟ is division of \u0026bdquo;d‟. This calculation conceals the public key \u0026bdquo;e‟ from the interloper. Furthermore, this calculation likewise utilizes five prime numbers to ascertain modulus \u0026bdquo;n‟ which will be hard to processing plants Abbreviations and Acronyms. Proposed algorithm comprises of three main parts i.e. Key Generation, Encryption and Decryption.\u003c/p\u003e\n\u003ch2\u003e3.1 Key Generation\u003c/h2\u003e\n\u003cp\u003ePerform following steps after assuming five (5) prime numbers i.e. p1, q1, r1, s1, t1, where p1 \u0026ne; q1 \u0026ne; r1 \u0026ne; s1 \u0026ne; t1.\u0026nbsp;\u003c/p\u003e\n\u003col class=\"decimal_type\" style=\"list-style-type: lower-roman;\"\u003e\n \u003cli\u003eCalculate the modulus n by multiplying the prime factors i.e. n = p1xq1xr1xs1x t1.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCalculate the Euler Totient \u0026phi; (n) by using formula \u0026phi; (n) = (p1-1)x(q1-1)x(r1-1) x(s1-1)x(t1-1).\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ePublic key exponent e is calculated using gcd (e, \u0026phi; (n)) = 1 and it should lie in between 1 \u0026lt; e \u0026lt; \u0026phi; (n).\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eFind private key exponent d which satisfies the equation (e * d) mod \u0026phi; (n) =1.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eContinue the above process if d is not prime otherwise select another e and d.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eUsing equation d mod k = 0, find an integer k which satisfies the equation (d mod k = 0).\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eFind phony public key exponent \u0026bdquo;f‟ using equation f = e*k.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eFind phony private key exponent g using equation g = d/k.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eObtain phony modulus using equation (e*d) mod \u0026phi;(X) = 1.\u003c/li\u003e\n\u003c/ol\u003e\n\u003ch2\u003e3.2 Encryption\u003c/h2\u003e\n\u003cp\u003eBefore being sent to the sender, the plain text (PT) will be encrypted using the key pairs (f, X) and the formula CT = (PT)f mod X.\u003c/p\u003e\n\u003ch2\u003e3.3 Decryption\u003c/h2\u003e\n\u003cp\u003eWhen the encoded content (CT) reached, the recipient computes original content (PT) by utilizing private key set (y1, pk) and formula PT = (CT)y1 Mod Z.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e3.4 Example: Assume five prime numbers i.e. 2, 3, 5, 7, 11.\u0026nbsp;\u003c/h2\u003e\n\u003cul\u003e\n \u003cli\u003eCompute module N = 2 x 3 x 5 x 7 x 11 = 2310.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCalculate Phi (N): \u0026Phi; (N) = (2-1) x (3-1) x (5-1) x (7-1) x (11-1).\u0026nbsp;\u003cbr\u003ePhi (N) = 1 x 2 x 4 x 6 x 10 = 480\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCalculate the open key exponent \u0026ldquo;oe1\u0026rdquo; Gcd (oe1, 480) =1 \u0026amp; 1\u0026lt;oe1\u0026lt;480. So oe1=47.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCalculate private key exponent \u0026ldquo;pd1\u0026rdquo;.\u0026nbsp;\u003cbr\u003e(oe1 * pd1) mod Phi (N) =1\u0026nbsp;\u003cbr\u003e(47 * pd1) mod 480 = 1, so pd1 = 143.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCalculate integer \u0026ldquo;pk\u0026rdquo;: 143 mod k = 0, So pk = 11\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCalculate fake public key exponent\u0026rdquo; x1\u0026rdquo;: x1= oe1 * pk, x1 = 47 * 11, so x1 = 517\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCalculate bogus secretive key exponent \u0026ldquo;y1\u0026rdquo;: y1 = pd1 / pk, y1 = 143 / 11, so y1 = 13\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eFind insincere module \u0026ldquo;Z\u0026rdquo;: (47 * 143) mod Phi (Z) = 1, So Z = 3361\u0026nbsp;\u003cbr\u003eSo, the public key will be (517, 3361) and the private key will be (13, 3361).\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLet PT = 123 be the plain text for encryption sender will encrypt this plain text in cipher text CT by using formula:\u0026nbsp;\u003cbr\u003eCT = (PT)x1 mod Z\u0026nbsp;\u003cbr\u003eCT = (123)517 mod 3361\u0026nbsp;\u003cbr\u003eCT = 504\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u0026sect; Receiver will decrypt the plain text PT by using formula:\u0026nbsp;\u003cbr\u003ePT = (CT)y1 mod Z.\u0026nbsp;\u003cbr\u003ePT = (504)13 mod 3361\u0026nbsp;\u003cbr\u003ePT = 123\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"4.\tImplementation And Results","content":"\u003cp\u003eThe proposed improved RSA algorithm is implemented in C++ using Visual Studio (Professional 2012). The source code of the proposed algorithm is executed on an Intel(R) Core (TM) i3-3217U CPU running at 4.0 GHz, 1.80 GHz, and 4 GB of RAM. The algorithm\u0026apos;s output was evaluated in terms of key generation, encryption, and decryption using a variety of inputs.\u003c/p\u003e\n\u003cp\u003eVarious inputs were offered to assess the effectiveness of the suggested algorithm. Table 4.1 displays the outcomes of the proposed algorithm\u0026apos;s various stages, such as Time to Create Key, Message Encoding, and Decoding Time. The output data for the RSA algorithms created by (Rivest et al., 1978) and (Ivy et al., 2012) are shown in Tables 4.2 and 4.3, respectively. These tables demonstrate that, compared to the other two RSA methods, RSA by (Rivest et al., 1978) and (Ivy et al., 2012), which use two, three, or four prime numbers, respectively, the suggested method requires a little more time to create keys. The increase in key generation time is due to the use of more primes in the key delivery process as well as the presentation of the complexity of factorization handling through the use of a phony open key exponent type of \u0026quot;x1\u0026quot; in place of \u0026quot;oe1\u0026quot; and a phony module of \u0026quot;Z\u0026quot; in place of \u0026quot;N.\u0026quot; Figures 8 and 9 show a comparison of the RSA (Rivest et al., 1978) and (Ivy et al., 2012) recommended techniques for encoding and unscrambling data. These figures show that the predicted technique requires less time than RSA (Ivy et al., 2012)) to encode and decode the message, but more time than RSA (By Rivest et al., 1978)). The proposed approach takes longer time to encrypt and decrypt data than the RSA (Rivest et al., 1978) because it uses five prime numbers as compared to two. However, the increased security, which is more crucial than time, makes this increase tolerable. Following tables 4.1-3 show that, for instance, the proposed algorithm takes 0.01495 seconds for encryption and 0.014 seconds for decryption when the length of the primes is 0.064 Kb, whereas RSA (Rivest et al., 1978) takes 0.003 seconds for encryption and also for decryption, which is quicker than the proposed algorithm. On the other hand, RSA (Ivy et al., 2012) takes 0.021 seconds and 0.023 sec for encryption and decryption which is slighter higher than proposed algorithm.\u003c/p\u003e\n\u003cp\u003eTable 1. Performance of Proposed Algorithm (Enhanced RSA Algorithm)\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"18.655097613882862%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimes Size\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(in kb)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" width=\"81.34490238611714%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime in Second\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"24.8%\"\u003e\n \u003cp\u003e\u003cstrong\u003eKey Creation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003etime\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.6%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEncoding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003etime\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.6%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDecoding\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003etime\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24%\"\u003e\n \u003cp\u003e\u003cstrong\u003eExecution\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003etime\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.655097613882862%\"\u003e\n \u003cp\u003e0.0125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.17353579175705%\"\u003e\n \u003cp\u003e0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824295010845987%\"\u003e\n \u003cp\u003e0.0013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824295010845987%\"\u003e\n \u003cp\u003e0.00125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.522776572668114%\"\u003e\n \u003cp\u003e0.1175\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.655097613882862%\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.17353579175705%\"\u003e\n \u003cp\u003e0167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824295010845987%\"\u003e\n \u003cp\u003e0.00182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824295010845987%\"\u003e\n \u003cp\u003e0.00134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.522776572668114%\"\u003e\n \u003cp\u003e0.17016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.655097613882862%\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.17353579175705%\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824295010845987%\"\u003e\n \u003cp\u003e0.00273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824295010845987%\"\u003e\n \u003cp\u003e0.00143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.522776572668114%\"\u003e\n \u003cp\u003e0.24416\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.655097613882862%\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.17353579175705%\"\u003e\n \u003cp\u003e0.393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824295010845987%\"\u003e\n \u003cp\u003e0.01495\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824295010845987%\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.522776572668114%\"\u003e\n \u003cp\u003e0.42195\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.655097613882862%\"\u003e\n \u003cp\u003e0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.17353579175705%\"\u003e\n \u003cp\u003e1.175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824295010845987%\"\u003e\n \u003cp\u003e0.10423\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.824295010845987%\"\u003e\n \u003cp\u003e0.1036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.522776572668114%\"\u003e\n \u003cp\u003e1.38283\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 2. Performance of RSA (Rivest et al., 1978)\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimes Size\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(in kb)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" width=\"81.81818181818181%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime in Second\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25.396825396825395%\"\u003e\n \u003cp\u003e\u003cstrong\u003eKey Creation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003etime\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.396825396825395%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEncoding\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003etime\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.396825396825395%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDecoding\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003etime\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.80952380952381%\"\u003e\n \u003cp\u003e\u003cstrong\u003eExecution\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003etime\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.181818181818183%\"\u003e\n \u003cp\u003e0.0125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.181818181818183%\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.0011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.0011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\"\u003e\n \u003cp\u003e0.0942\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.181818181818183%\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.0011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\"\u003e\n \u003cp\u003e0.1351\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.181818181818183%\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\"\u003e\n \u003cp\u003e0.358\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.181818181818183%\"\u003e\n \u003cp\u003e0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.889\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\"\u003e\n \u003cp\u003e0.932\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3. Performance of RSA (Ivy et al., 2012)\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"18.181818181818183%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimes Size (kb)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" width=\"81.81818181818181%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime in Second\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.984126984126984%\"\u003e\n \u003cp\u003e\u003cstrong\u003eKey generation time\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.80952380952381%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEncryption\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003etime\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.396825396825395%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDecryption\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003etime\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.80952380952381%\"\u003e\n \u003cp\u003e\u003cstrong\u003eExecution\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003etime\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.181818181818183%\"\u003e\n \u003cp\u003e0.0125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.07792207792208%\"\u003e\n \u003cp\u003e0.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.0017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\"\u003e\n \u003cp\u003e0.1137\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.181818181818183%\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.07792207792208%\"\u003e\n \u003cp\u003e0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\"\u003e\n \u003cp\u003e0.0025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.0022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\"\u003e\n \u003cp\u003e0.1487\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.181818181818183%\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.07792207792208%\"\u003e\n \u003cp\u003e0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\"\u003e\n \u003cp\u003e0.223\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.181818181818183%\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.07792207792208%\"\u003e\n \u003cp\u003e0.313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\"\u003e\n \u003cp\u003e0.357\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.181818181818183%\"\u003e\n \u003cp\u003e0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.07792207792208%\"\u003e\n \u003cp\u003e0.922\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\"\u003e\n \u003cp\u003e0.170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.77922077922078%\"\u003e\n \u003cp\u003e0.169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.48051948051948%\"\u003e\n \u003cp\u003e1.261\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe proposed algorithm is more secure than the standard RSA technique. Factorization of modulus \u0026quot;N\u0026quot; is a method for weakening the security of RSA, and although the security of the proposed technique is harder to break than that of standard RSA for two reasons:\u003c/p\u003e\n\u003col style=\"list-style-type: lower-roman;\"\u003e\n \u003cli\u003eIt uses five prime numbers, which takes longer to factorize the modulus \u0026quot;n\u0026quot; than the standard RSA, which uses only two primes.\u003c/li\u003e\n \u003cli\u003eAnother feature that protect the proposed algorithm from factorization attacks is the use of phony exponents and a fictitious module. Therefore, the suggested algorithm is more secure than a normal RSA.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"5.\tConclusion And Future Work","content":"\u003cp\u003eThe most important step in protecting customer data from unauthorized parties is the encryption architecture. There are various encryption algorithms available today, but RSA is a very important and widely used one. In this study, we examined the shortcomings of the existing encryption and decryption algorithms. We have suggested an improved version of the RSA algorithm to safeguard data. Two additional features of this approach include the discovery of module \u0026quot;N\u0026quot; using five prime numbers and the disposal of module \u0026quot;N\u0026quot; and open key expounder \u0026quot;oe1\u0026quot; in favor of bogus module \u0026quot;Z\u0026quot; and false open key expounder \u0026quot;x1\u0026quot; in standard RSA. Greater safety would be attained using the \u0026quot;addition of two attributes\u0026quot; technique by reducing the time required for encoding and unscrambling. Here, a minor adjustment to the open key is recommended in order to make use of the Avalanche impact, which can only decode encoded content and cannot retrieve reversed content. The suggested methodology lessens the likelihood of numerical attacks by providing extra protection in exchange for a slight increase in length sophistication. Despite the fact that the proposed methodology uses a protected code framework and a limited level of safety, it is designed to encourage more resistance than the RSA algorithm. The proposed algorithm can be improved by reducing the execution time and enhanced in security for IoT.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e \u0026ndash; Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e \u0026ndash; The authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e \u0026ndash; Currently, we don\u0026rsquo;t have any funding. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e \u0026ndash; Conceptualization, B.U.; methodology, A.M and R.A.; software, B.U. and M.J.; validation, B.U., M.J. and A.M.; investigation, A.K.; resources, A.M.; writing\u0026mdash;original draft preparation, A.M., A.K. and S.U.; writing\u0026mdash;review and editing, A.M., A.K., R.A..; visualization, S.U; supervision, A.M., A.K; project administration, A.M. and S.U.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e \u0026ndash; All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e \u0026ndash; N.A.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAsang, S. Manongga D., Sembiring, I. (2018). Data Security on Internet of Things Device Using Hybrid Encryption Models. International Journal of Computer Science and Information Security, 16(8), 93-103.\u003c/li\u003e\n \u003cli\u003eDeepika K., \u0026amp; Poonam D., (2017). Secure Data Transmission using AES in IoT. International Journal of Application or Innovation in Engineering \u0026amp; Management (IJAIEM), 6(6), 283-289.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDorri, A., Kanhere, S. S., Jurdak, R., \u0026amp; Gauravaram, P. (2017). Blockchain for IoT security and privacy: The case study of a smart home. IEEE international conference on pervasive computing and communications workshops, pp. 618-623.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eNovo, O. (2018). Blockchain meets IoT: An architecture for scalable access management in IoT. IEEE Internet of Things Journal, 5(2), 1184-1195.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDorri, A., Kanhere, S. S., \u0026amp; Jurdak, R. (2017). Towards an optimized blockchain for IoT. IEEE/ACM Second International Conference on Internet-of-Things Design and Implementation, pp. 173-178.\u003c/li\u003e\n \u003cli\u003eDorri, A., Kanhere, S. S., Jurdak, R., \u0026amp; Gauravaram, P. (2019). LSB: A Lightweight Scalable Blockchain for IoT security and anonymity. Journal of Parallel and Distributed Computing, 134, 180-197.\u003c/li\u003e\n \u003cli\u003eIvy, B. P. U., Mandiwa, P., \u0026amp; Kumar, M. (2012). A modified RSA cryptosystem based on \u0026lsquo;n\u0026rsquo;prime numbers. International Journal Of Engineering And Computer Science, 1(2), 63-66.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eKavitha, S., Alphonse P. J, A. (2019). A Hybrid Cryptosystem to Enhance Security in IoT Health Care System. I.J. Wireless and Microwave Technologies, 2019, 1, 1-10, DOI: 10.5815/ijwmt.2019.01.01\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eKalaiselvi, K., Kumar, A., (2015). Implementation Issues and Analysis of Cryptographic Algorithms based on different Security Parameters. International Journal of Computer Applications, 23-28.\u003c/li\u003e\n \u003cli\u003eKrishna M., Sivarama k. N., Ravi P., Prakash K., (2019). A Hybrid Approach for Enhancing Security in IOT using RSA Algorithm. Helix the Scientific Explorer, 9(1), 4758-4762.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eRafidha Rehiman, K. A. R., Veni, S., (2017). Compression and Encryption approach for Data Security in Mobile Internet of Things. International Journal of Advanced Research in Computer Engineering \u0026amp; Technology (IJARCET), 6(1), 39-42.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eRaghunandan K R, Ganesh Aithal, Surendra Shetty, (2019). Secure RSA Variant System to Avoid Factorization Attack using Phony Modules and Phony Public Key Exponent. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8(9), 1065-1070.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eRajesh, S. V., Paul, V., Menon, G. V., Khosravi R., M., (2019). A Secure and Efficient Light weight Symmetric Encryption Scheme for Transfer of Text Files between Embedded IoT Devices. An Article, 1-21.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eRivest, R. L., Shamir, A., \u0026amp; Adleman, L. (1978). A method for obtaining digital signatures and public-key cryptosystems. Communications of the ACM, 21(2), 120-126.\u003c/li\u003e\n \u003cli\u003eSurendran, S., Nassef, A., \u0026amp; Beheshti, B. D. (2018). A survey of cryptographic algorithms for IoT devices 2018 IEEE Long Island Systems, Applications and Technology Conference.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eTenzin, K. Kirubanand V. B., (2018) A lightweight hybrid encryption technique to secure IoT data transmission. International Journal of Engineering \u0026amp; Technology\u0026nbsp;7(2.6):236.\u003c/li\u003e\n \u003cli\u003eThangavel, M., Varalakshmi, P., Murrali, M., \u0026amp; Nithya, K. (2015). An Enhanced and Secured RSA Key Generation Scheme (ESRKGS). Journal of Information Security and Applications, 20, 3\u0026ndash;10.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eVithya A., Arockiam L., (2018). ARO_EDGE: A Technique to Ensure Data Security in Internet of Things (IoT). Asian Journal of Computer Science and Technology, 7(2), 52-56.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Security, Encryption, Decryption, Internet of Things","lastPublishedDoi":"10.21203/rs.3.rs-1896185/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1896185/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eVarious devices are linked together through a variety of networks in order to exchange data in the Internet of Things (IoT). Life has changed dramatically as a result of the IoT's quickly developing applications, making it more fanciful and akin to living in a virtual environment. IoT security may be a major concern because it allows access to anything from anywhere at any time. Different mechanisms are used, including encryption, to safeguard the data transmitted by various IoT devices. A straightforward piece of content can be transformed into an intangible one via encryption. Two frequently used methods of encryption are symmetric key and asymmetric key cryptography. Asymmetric cryptography uses two separate keys for encoding and unscrambling messages as opposed to symmetric key cryptography, which uses just one key for both encoding and decoding. To protect IoT data, several public key cryptography techniques are utilized. However, numerous studies have demonstrated that it is incredibly challenging to safeguard data while utilizing the fewest resources from hackers and other cybercriminals.\u003c/p\u003e \u003cp\u003eThis study presents a concise overview of many existing encryption techniques and highlights their shortcomings. Conjointly presents an improved Rivest\u0026ndash;Shamir\u0026ndash;Adleman (RSA) algorithm to dodge the limits of diverse factorization assaults by upgrading complications of the factorization handle by utilizing five prime numbers and a fake open key instead of the original key and imposter modulus in its place of the product of five prime numbers. The proposed algorithm generates keys a little more slowly than the other two RSA algorithms (Rivest et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1978\u003c/span\u003e) and (Ivy et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) due to the usage of additional prime numbers and the difficulty of factorization preparation. For encryption and unscrambling, the suggested calculation takes less time than RSA (Ivy et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), but it costs more than RSA (Rivest et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1978\u003c/span\u003e). Since the suggested calculation employs five prime numbers instead of RSA's two prime numbers, it takes longer to encrypt data and decrypt it than RSA (Rivest et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1978\u003c/span\u003e). But since security comes first, the longer encryption and decryption time is acceptable.\u003c/p\u003e","manuscriptTitle":"Enhanced RSA Algorithm for Data Security in the Internet of Things","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-08-16 15:57:21","doi":"10.21203/rs.3.rs-1896185/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e0cd336f-6373-43bf-8524-40b7bc67b642","owner":[],"postedDate":"August 16th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-09-06T06:38:55+00:00","versionOfRecord":[],"versionCreatedAt":"2022-08-16 15:57:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1896185","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1896185","identity":"rs-1896185","version":["v1"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}