Bridging the AI divide: The evolving arms race between AI-driven cyber attacks and AI-powered cybersecurity defenses

Guy Waizel ()
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Guy Waizel: "Alexandru Ioan Cuza" University of Iasi, Romania

International Conference on Machine Intelligence & Security for Smart Cities (TRUST) Proceedings, 2024, vol. 1, 141-156

Abstract: The rapid advancement of artificial intelligence (AI) has significantly transformed both offensive and defensive dimensions of cybersecurity. This article explores the burgeoning landscape of AI-driven cyber-attacks and the corresponding AI-powered cybersecurity defenses. Through an extensive literature review, we establish a foundational understanding of current AI techniques used in cyber-attacks, such as machine learning-based malware and AI-generated phishing schemes. Concurrently, we examine state-of-the-art AI-driven defense mechanisms, including anomaly detection systems and automated response strategies.To provide concrete examples, we conduct detailed case studies of high-profile cyber incidents where AI played a pivotal role. These case studies illustrate the sophistication and effectiveness of AI-driven attacks and highlight the defensive measures deployed to counteract them. By juxtaposing the capabilities of offensive AI with defensive AI, we reveal a significant gap between the two, underscoring the challenges faced by cybersecurity professionals in keeping pace with rapidly evolving threats.The findings from theresearch underscore the need for continuous innovation and collaboration in the cybersecurity field to enhance AI-powered defenses. By synthesizing insights from academic research, industry practices, and real-world case studies, this article offers a comprehensive view of the current state of the AI cybersecurity arms race. Theanalysis not only illuminates the existing disparity between AI-driven attacks and defenses but also suggests strategic pathways for narrowing this gap, ultimately aiming to bolster global cyber resilience.

Keywords: Ransomware; Stealth techniques; AI techniques; APT; Malware; Cybersecurity (search for similar items in EconPapers)
JEL-codes: O35 (search for similar items in EconPapers)
Date: 2024
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