C.Saranraj, V.Murali
An innovative knowledge-based methodology for terrorist detection by using Web traffic content as the audit information is presented. The proposed methodology learns the typical behavior (‘profile’) of terrorists by applying a data mining algorithm to the textual content of terror-related Web sites. The resulting profile is used by the system to perform real-time detection of users suspected of being engaged in terrorist activities. The Receiver-Operator Characteristic (ROC) analysis shows that this methodology can outperform a command- based intrusion detection system
Data Mining, User Modeling, Terrorist Trend Detection, Anomaly Detection, Activity Monitoring