A Review of Artificial Intelligence-Enhanced Security Solutions for the Internet of Things
Qingqing Yue, Shanshan Tu, Wenlong Li, Hongchen Li · 2024
The rapid development of the Internet of Things (IoT) is fundamentally transforming various industries, with many IoT systems increasingly driven by artificial intelligence (AI). Advances in AI introduce new changes and breakthroughs in IoT, while the swift progress of IoT technology also presents significant security and privacy challenges. This paper reviews the major security issues and solutions within AI-driven IoT environments, focusing on key management protocols, intrusion detection systems, physical layer authentication, and data encryption. It examines the advantages and limitations of symmetric and asymmetric key management, the roles of network-based and host-based intrusion detection systems, and how physical layer authentication enhances device security through wireless signal characteristics. Additionally, the paper discusses the role of homomorphic encryption and privacy protection technologies, suggesting that integrating these methods represents an effective strategy for addressing IoT security challenges. Future research directions include developing scalable security protocols, advanced threat detection systems, and incorporating AI to enhance the resilience and efficiency of IoT security measures.