AI in cyber security: A dual perspective on hacker tactics and defensive strategies
Lawrence Amer
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Lawrence Amer: KPMG Netherlands, The Netherlands
Cyber Security: A Peer-Reviewed Journal, 2025, vol. 8, issue 3, 198-213
Abstract:
The use of artificial intelligence (AI) in cyber security has significantly changed the dynamics of warfare, ushering in an era in the continuous battle between those launching attacks and those defending against them. This paper presents an analysis of the impact of AI on cyber security, examining its role from a defensive standpoint. It begins by investigating how cybercriminals harness AI to enhance their capabilities. Cutting-edge machine learning (ML) algorithms empower the development of targeted and stealth attacks, using tactics ranging from AI-driven social engineering strategies to malware that can evade detection methods, as well as intelligent botnet systems capable of orchestrating complex offensives. Specific instances such as AI-fuelled malware creation tools and adaptive command and control servers are explored to illustrate the changing landscape of cyber threats and show how cyber security experts utilise AI to strengthen defences. AI-empowered intrusion detection systems, anomaly detection based on ML and automated incident response platforms stand at the forefront of contemporary cyber defence measures. These technologies enable threat identification, in-time predictive analytics and rapid responses to emerging security breaches. By juxtaposing these contrasting uses of AI in cyber security, the paper offers a nuanced perspective on the competition within this domain. This paper seeks to provide cyber security experts with knowledge to predict and combat changing threats and to give researchers a basis for creating new AI-driven security solutions. This holistic strategy not only showcases the game-changing impact of AI in cyber security but also emphasises the crucial requirement for ongoing creativity in this swiftly advancing domain.
Keywords: artificial intelligence; cyber security; hackers’ strategies; defensive countermeasures; machine learning; anomaly detection; incident response; malware development (search for similar items in EconPapers)
JEL-codes: M15 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:aza:csj000:y:2025:v:8:i:3:p:198-213
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