Attack detection and prevention in the Cyber Physical System

This paper proposes cyber-attack detection and prevention of Cyber Physical System. The Chi square detector and Fuzzy logic based attack classifier (FLAC) were used to identify distributed denial of service and False data injection attacks. The fuzzy attributes for selecting the mentioned attacks are activity profiling, average packet rate, change point detection algorithm, cusum algorithm, unexpired session of users, injected incomplete information, reuse of session key. An example scenario has been created using OpNET Simulator. Simulation results depict that the use of Chi-square detector and FLAC are able to detect the mentioned cyber physical attacks with high accuracy. Compared to existing Fuzzy logic based attack detector, the proposed model outperforms the traditional distributed denial of service and false data detector.