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Host Based Internal Intrusion Detection System by using Data Mining and Forensic Technique

Author(s):

Rutuja Shah , BSIOTR; Ashwini Pingle, BSIOTR; Swapnali Tambe, BSIOTR; Madhuri Alhat, BSIOTR; Trupti Dhumal, BSIOTR

Keywords:

ata Mining, Insider Attack, Intrusion Detection And Protection, System Call (SC), Users’ Behaviors

Abstract

A Host Based Internal Intrusion Detection and Protection System by Using Data Mining and Forensic Techniques (IIDPS) play a significant role in computer security. In network surroundings IIDPS find the activities that have an effect on Confidentiality, Integrity and accessibility on network knowledge. Currently, most computer systems use user IDs and passwords because the login patterns to verify users. However, many of us share their login patterns with co-workers and request these coworkers to help co-tasks, thereby creating the pattern united of the weakest points of computer security. Insider attackers, the valid users of a system who attack the system internally, are hard to find since most intrusion detection systems and firewalls establish and isolate malicious behaviors launched from the external world of the system solely. Additionally, some studies claimed that analyzing system calls generated by commands will establish these commands, with that to accurately find attacks, with attack patterns are the options of an attack. Therefore, in this project, a security system, named the Host Based Intrusion Detection System (HIDS), is projected to find Insider attacks at application level by optimizing data processing and rhetorical techniques. The HIDS creates user’s profiles & log file to stay track of user’s usage habits as their rhetorical options and determines whether or not a sound login user is that the account holder or not by scrutinizing his/her current system usage behaviors with the patterns collected within the account holder’s profile & log file. When intrusion is detected then image will be captured by system and then it will send to administrator and then system will automatically shut down as the intrusion is detected.

Other Details

Paper ID: IJSRDV5I20638
Published in: Volume : 5, Issue : 2
Publication Date: 01/05/2017
Page(s): 1162-1165

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