Automation of Dynamic Multi-Layer Signature based Intrusion Detection System with Pattern Similarity and Recognition

Every computer on the Internet is a potential target for a new attack at any moment nowadays. Network intrusion Detection System (NIDS) is one of the fundamental components to monitor and analyze the traffic to find out any possible attacks in the network. Intrusion Detection based on the application requires exploration of network packet payload data. A special model is required for each services while, every service has different behavior. This paper aims on network packet payload data and it will improve suspicion and recognize signature based attack patterns using pattern matching strategy distantly more accurate than approaches that consider only header information. This paper focuses on developing a multi-layered design known to be a Dynamic Multi-layered Signature Pattern Similarity and Recognition (DMSP-SR). The concept of DMSP-SR is introduced for payload data intrusion that would verify the packets, cluster the packets, measuring pattern similarity and recognize the intrusion signature pattern to diminish these attacks. This is a Multi-layered framework design would enhance the overall performance of the signature based intrusion detection system with the set of attack patterns. The performance analysis shows that the proposed framework can improve the accuracy by increasing the detection rate and effectiveness by reducing the false positive rate and increase true positive rate of identifying payload intrusion compared to the existing systems.