Internal Intrusion Detection and Security System by Using Data Mining and Forensic Techniques

Abstract

Currently, most pc systems use user IDs and passwords because the login patterns to demonstrate users.
However, many people share their login pattern with co employees and request these co employees to help co-tasks, there
by creating the pattern in concert of the weakest points of pc security. Corporate executive attackers, the valid users of a
system UN agency attack the system internally, area unit arduous to observe since most intrusion detection systems and
firewalls establish and isolate malicious behaviours launched from the skin world of the system solely. Additionally,
some studies claimed that analysing supervisor call instruction (SCs) generated by commands will establish these
commands, with that to accurately observe attacks, associated attack patterns area unit the options of an attack.
Therefore, during this paper, a security system, named the inner Intrusion Detection and Protection System (IIDPS), is
planned to observe corporate executive attacks at SC level by victimization data processing and rhetorical techniques.
The IIDPS creates users’ personal profiles to stay track of users’ usage habits as their rhetorical options and determines
whether or not a legitimate login user is that the account holder or not by scrutiny his/her current pc usage behaviors with
the patterns collected within the account holder’s personal profile. The experimental result demonstrate that the IIDPS’s
user identification accuracy is ninety four.29%, whereas the interval is a smaller amount than zero.45 s, implying that it
will stop a protected system from corporate executive attacks effectively and expeditiously.