An Internal Intrusion Detection and Protection System by Using Data Mining and Forensic Techniques
Abstract— An Internal Intrusion Detection and Protection System by Using Data Mining and Forensic Techniques. Currently, most computer systems use user IDs and passwords as the login patterns to authenticate users. However, many people share their login patterns with coworkers and request these coworkers to assist co-tasks, thereby making the pattern as one of the weakest points of computer security. Insider attackers, the valid users of a system who attack the system internally, are hard to detect since most intrusion detection systems and ﬁrewalls identify and isolate malicious behaviors launched from the outside world of the system only. In addition, some studies claimed that analyzing system calls < Final Year Projects 2016 > SCs generated by commands can identify these commands, with which to accurately detect attacks, and attack patterns are the features of an attack.
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