Analyzing attack strategies against rule-based intrusion detection systems
Pooja Parameshwarappa, Zhiyuan Chen, Aryya Gangopadhyay · 2018
Intrusion Detection Systems (IDS) have been widely used to detect cyber attacks in Cyber-Physical Systems (CPS). However, attackers can often adapt their attacking strategies to evade detection. Many commercial IDS are rule-based systems. This paper analyzes the possible attacking strategies against a widely used rule-based IDS, Snort, using hyper graph model and clustering. We present initial results and discuss some techniques to prevent such attacks.