Paper Title
IIDPS for Data Mining and Forensic Technique

Computer system uses login patterns as user IDs and password for user authentication. The weakest points of computer security is to share their login patterns with co-workers to assist co-tasks. When an internal attack is done with the existing valid user, the suspicious activity from the unsecured zone is identified by invasion detection systems and firewalls. Some studies demanded for analyzing system calls(SCs) to identify commands with the SCs generated commands with the help of this commands user can detect accurately. Therefore a new system is proposed that provides security and also detects inside attacks by using Data mining and Forensic techniques at SC level. The proposed approach IIDPS uses usage habits to keep track of personal profiles for forensic features to determine authenticated user in the account holder, all the patterns are composed in the account holder’s personal profile. The IIDPS shows the user recognition accuracy is 94.29%, where as the response time less than 0.45 sec. This helps to overcome the system from insider attacks effectively and virtuously. Keywords - Data Mining, Insider Attack, Intrusion Detection and Protection, System Call (SC), Users’ Behaviors.