The Internet of Things (IoT) connects billions of devices, enabling real-time data collection, processing, and communication, but also introduces significant security and privacy challenges. This chapter explores the security vulnerabilities in IoT ecosystems, categorizing threats across hardware, network, and software layers, including Denial of Service (DoS), Man-in-the-Middle (MITM) attacks, malware infections, and advanced microarchitectural exploits like Rowhammer, Spectre, and Meltdown. Additionally, it examines Industrial IoT (IIoT) and Operational Technology (OT) security risks, highlighting the need for AI-driven security solutions such as anomaly detection, predictive maintenance, behavioral analysis, and automated response systems. However, adversaries are also leveraging AI-enhanced cyberattacks, including AI-powered malware, botnets, and data poisoning techniques, necessitating robust security automation and compliance frameworks. The chapter concludes by discussing emerging trends in AI-based IoT security, such as Edge AI, self-adaptive security mechanisms, and regulatory challenges, aiming to enhance the resilience and protection of IoT infrastructures in an increasingly interconnected world.

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AI for IoT and OT Security

  • Dilli Prasad Sharma,
  • Arash Habibi Lashkari,
  • Mahdi Daghmehchi Firoozjaei,
  • Samaneh Mahdavifar,
  • Pulei Xiong

摘要

The Internet of Things (IoT) connects billions of devices, enabling real-time data collection, processing, and communication, but also introduces significant security and privacy challenges. This chapter explores the security vulnerabilities in IoT ecosystems, categorizing threats across hardware, network, and software layers, including Denial of Service (DoS), Man-in-the-Middle (MITM) attacks, malware infections, and advanced microarchitectural exploits like Rowhammer, Spectre, and Meltdown. Additionally, it examines Industrial IoT (IIoT) and Operational Technology (OT) security risks, highlighting the need for AI-driven security solutions such as anomaly detection, predictive maintenance, behavioral analysis, and automated response systems. However, adversaries are also leveraging AI-enhanced cyberattacks, including AI-powered malware, botnets, and data poisoning techniques, necessitating robust security automation and compliance frameworks. The chapter concludes by discussing emerging trends in AI-based IoT security, such as Edge AI, self-adaptive security mechanisms, and regulatory challenges, aiming to enhance the resilience and protection of IoT infrastructures in an increasingly interconnected world.