Real-time implementation of IoT Enabled Cyber Attack Detection System (IoT-E-CADS) in Advanced Metering Infrastructure (AMI) using Machine Learning Technique (MLT)

Real-time implementation of IoT Enabled Cyber Attack Detection System (IoT-E-CADS) in Advanced Metering Infrastructure (AMI) using Machine Learning Technique (MLT) | 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 Article Real-time implementation of IoT Enabled Cyber Attack Detection System (IoT-E-CADS) in Advanced Metering Infrastructure (AMI) using Machine Learning Technique (MLT) Naveeda K, Sithi Shameem Fathima S.M.H. This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3928260/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract The introduction of Internet of Things (IoT) and Smart Energy Meters (SEM) in power grid expects high level cyber security for properly operating the system. This paper proposes an IoT Enabled Cyber Attack Detection System (IoT-E-CADS) in Advanced Metering Infrastructure (AMI) using Machine Learning Technique (MLT). The proposed Bi-level IoT-E-CADS is working in the industry standards for the detection of two types of attacks in the smart grid environment. In the first level, the Isolation Forest machine learning algorithm is used to find the cyber attacks and anomaly detection in real time system. In the second level, Decision Tree machine learning algorithm is used to find the cyber attacks and False Data Injection in a real time system. The designed hardware is implemented and tested at Quantanics Techserv Pvt. Ltd., located in Madurai, Tamil Nadu, India. This company has AMI facility with 10 smart meters, one data concentrator and dedicated server system. The company energy profile and all electrical parameters are monitored and stored using AMI facility. The proposed IoT-E-CADS successfully implemented in this location and detect the manually created two types of cyber attacks. Based on the obtained results, it is observed that the IoT-E-CADS is able to detect cyber threats with the accuracy level of 95% and provides a complete cyber security solutions for secured monitoring unit in commercial environment IoT Enabled Cyber Attact Detection System Internet of Things Advanced metering infrastructure (AMI) smart meters intrusion detection Machine learning IoT Enabled Cyber Attack Detection System (IoT-E-CADS) Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 26 Apr, 2024 Reviews received at journal 14 Apr, 2024 Reviews received at journal 13 Apr, 2024 Reviewers agreed at journal 11 Apr, 2024 Reviewers agreed at journal 29 Mar, 2024 Reviewers agreed at journal 29 Mar, 2024 Reviewers agreed at journal 28 Mar, 2024 Reviewers agreed at journal 12 Mar, 2024 Reviewers invited by journal 12 Mar, 2024 Editor assigned by journal 06 Feb, 2024 Submission checks completed at journal 06 Feb, 2024 First submitted to journal 04 Feb, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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The proposed IoT-E-CADS successfully implemented in this location and detect the manually created two types of cyber attacks. 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