Intelligent Automation Using Machine and Deep Learning in Cybersecurity of Industrial IoT

Abstract

Artificial intelligence is making significant changes in industrial internet of things (IIoT). Particularly, machine and deep learning architectures are now used for cybersecurity in smart factories, smart homes, and smart cities. Using advanced mathematical models and algorithms more intelligent protection strategies should be developed. Hacking of IP surveillance camera systems and Closed-Circuit TV (CCTV) vulnerabilities represent typical example where cyber attacks can make severe damage to physical and other Industrial Control Systems (ICS). This chapter analyzes the possibilities to provide better protection of video surveillance systems and communication networks. The authors review solutions related to migrating machine learning based inference towards edge and smart client devices, as well as methods for DDoS (Distributed Denial of Service) intelligent detection, where DDoS attack is recognized as one of the primary concerns in cybersecurity.