Securing IoT Services Using Artificial Intelligence in Edge Computing
P. William, Siddhartha Choubey, Abha Choubey, Gurpreet Singh Chhabra · 2024
For IoT applications that demand real-time response, typical cloud computing paradigms relying on transferring all data to the cloud for processing are becoming more unsatisfactory owing to network delays. By shifting data processing from the cloud to edge nodes, a new computing paradigm known as “Edge Computing” (EC) is allowing Internet of Things (IoT) applications that need low latency to get better Quality of Service. The processing and storage resources of distributed ENs are more vulnerable than those of other endpoint devices, such as smartphones or PCs. Significant advances in artificial intelligence (AI) provide new possibilities for tackling security issues in light of the fact that EC’s security and privacy protections have become essential challenges. The tremendous learning capability of AI helps systems to more precisely and effectively detect harmful assaults. Meanwhile, transmitting model parameters rather than raw data mitigates the risk of privacy breaches to a certain extent. The goal of this research is to provide readers a comprehensive picture of AI’s role in EC IoT security. The status of research and several key concepts are covered in the first part of the chapter. Next, the basis for IoT services based on EC is discussed. An investigation of privacy protection and blockchain technology for edge-enabled IoT services using AI follows. Last but not least, the chapter covers the still unsolved issues and challenges related to EC-based IoT services that use AI.