Ransomware Evolution: How AI is Changing Both Attack and Defence Strategies

Abstract

The proliferation of artificial intelligence (AI) technologies has fundamentally transformed the cybersecurity landscape, particularly in the domain of ransomware attacks and defense mechanisms. This paper examines the evolutionary trajectory of ransomware through the lens of AI integration, analyzing how machine learning algorithms, automated decision-making systems, and neural networks are being weaponized by adversaries while simultaneously empowering defensive capabilities. Through systematic analysis of current literature, attack taxonomies, and defense frameworks, this research identifies critical inflection points where AI technologies have altered the ransomware threat landscape. The study reveals that AI-enhanced ransomware demonstrates increased sophistication in target selection, evasion techniques, and encryption methods, while AI-driven defense systems show promise in predictive threat detection, behavioral analysis, and automated response mechanisms. However, significant asymmetries persist between offensive and defensive capabilities, with attackers often exploiting AI advantages more rapidly than defenders can implement countermeasures. This paper proposes a comprehensive framework for understanding AI's dual role in ransomware evolution and offers strategic recommendations for organizations seeking to leverage AI technologies for enhanced cybersecurity resilience. The findings underscore the urgency of developing adaptive defense strategies that can respond to the accelerating pace of AI-enabled threats while addressing ethical considerations and resource constraints inherent in AI implementation.