A HMM-Based ICS Adaptive Deception Defense Framework

This paper aims to study the application and implementation of deception prevention technology in Industrial control system. With the wide application of Industrial control system and the increase of network connection, the system is facing more and more security challenges. Aiming at these challenges, this paper proposes a deception defense framework based on adaptive Hidden Markov Model (HMM). The framework uses the HMM to model and analyze the normal behavior of industrial control systems and identify potential attacks by monitoring and detecting anomalous behavior in real time. The paper details the methodology and design ideas of the framework and tests it in experiments using attack scenarios such as DDoS attacks, malicious program injection, and fake data injection. Experimental results show that our deception defense framework can effectively detect and defend against these attacks with low false alarm and miss rates. In addition, the paper evaluates and discusses the real-time, efficiency and scalability of the framework. This research is of great significance for the security protection of industrial control systems and provides an innovative and effective defense method for the security of industrial control systems.