Artificial Intelligence-Powered Cyber Attacks: Adversarial Machine Learning

Artificial Intelligence-Powered Cyber Attacks: Adversarial Machine Learning | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 3 February 2025 V1 Latest version Share on Artificial Intelligence-Powered Cyber Attacks: Adversarial Machine Learning Author : Anwar Mohammed 0009-0009-9991-5166 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.173862063.39098197/v1 3014 views 1172 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Advances in digital technology and the rise of cyber threats have created an increasingly complex cybersecurity environment. Using more cloud services and connected devices has allowed enterprises to increase the attack surface, growing systems' susceptibility to hacking. The current study aims to investigate artificial intelligence-driven (AI) cyberattacks targeting devices studying enemies. Reviewing adversary machine learning insights reveals critical weaknesses in AI design and the vulnerability of adversary attacks to affect images, leading to misclassification and security threats. Case studies like the Microsoft Tay chatbot tragedy and the Tesla Model S attack proved these vulnerabilities-Apart from how world applications undermine public security and trust in AI systems, the implications for society and the economy happened as emphasis needs to be placed on addressing ethical issues such as bias and privacy when implementing AI in cybersecurity. The study suggests that organizations should adopt adversarial training to increase the robustness of the machine learning model against adversary attacks. Similarly, moral explanation requires multiple approaches. International companies must understand cybersecurity legislation, including EU and UK legislation, to develop effective breach response strategies. The study recommends that organizations adopt a multifaceted approach to enhance defences against adversarial attacks, including updating models with adversarial examples, regularization, developing anomaly detection systems, and addressing bias and privacy concerns. Supplementary Material File (artificial-intelligence-powered-cyber-attacks-adversarial-machine-learning.pdf) Download 1.01 MB Information & Authors Information Version history V1 Version 1 03 February 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords adversarial examples adversarial machine learning artificial intelligence cyberattacks cybersecurity Authors Affiliations Anwar Mohammed 0009-0009-9991-5166 [email protected] Singhania University View all articles by this author Metrics & Citations Metrics Article Usage 3014 views 1172 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Anwar Mohammed. Artificial Intelligence-Powered Cyber Attacks: Adversarial Machine Learning. Authorea . 03 February 2025. DOI: https://doi.org/10.22541/au.173862063.39098197/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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