Ransomware is a rapidly evolving cyber threat with the potential to cause significant financial and operational disruption across industries. This paper analyzes the 2017 WannaCry attack, which exploited a Microsoft Windows vulnerability to infect over 200,000 systems globally, severely affecting sectors such as healthcare, including the UK’s NHS. The study explores ransomware’s progression from simple attacks to advanced, AI-powered variants. These modern forms use real-time analysis, intelligent target selection, and adaptive evasion techniques to bypass traditional defenses and enhance social engineering tactics. To counter these threats, organizations must adopt proactive strategies, including AI-driven cybersecurity solutions, behavior- based anomaly detection, and targeted employee training. Understanding the AI–ransomware link is essential for building resilient defenses against future cyberattacks.

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The Dual Edge of AI in Cybersecurity: Mitigating Ransomware Threats Through Self-learning Honeypots and Behavioral Analytics

  • Keyur Kurani,
  • Vaibhavi Machchhar

摘要

Ransomware is a rapidly evolving cyber threat with the potential to cause significant financial and operational disruption across industries. This paper analyzes the 2017 WannaCry attack, which exploited a Microsoft Windows vulnerability to infect over 200,000 systems globally, severely affecting sectors such as healthcare, including the UK’s NHS. The study explores ransomware’s progression from simple attacks to advanced, AI-powered variants. These modern forms use real-time analysis, intelligent target selection, and adaptive evasion techniques to bypass traditional defenses and enhance social engineering tactics. To counter these threats, organizations must adopt proactive strategies, including AI-driven cybersecurity solutions, behavior- based anomaly detection, and targeted employee training. Understanding the AI–ransomware link is essential for building resilient defenses against future cyberattacks.