CONDITIONAL RANDOM FIELDS BASED REAL-TIME INTRUSION DETECTION FRAMEWORK

Intrusion detection systems are now an essential component in the all kinds of network even including wireless ad hoc network. With the rapid advancement in the network technologies the focus of intrusion detection has shifted from simple signature matching approaches to detecting attacks based on analyzing contextual information that employed in anomaly and hybrid intrusion detection approaches. This paper proposed a layered anomaly intrusion detection framework using Conditional Random Fields to detect a wide variety of attacks. With this framework attacks can be identified and intrusion response can be initiated in real time. Experiments show that the CRF model can detect attacks effectively.