Authors :
Harshata Bhargava, Radhe Shyam Panda.
Volume/Issue :
Volume 3 - 2018, Issue 12 - December
Google Scholar :
https://goo.gl/DF9R4u
Scribd :
https://goo.gl/WdMkcY
Thomson Reuters ResearcherID :
https://goo.gl/KTXLC3
Abstract :
Insider attack detection in an enterprise network environment is a critical problem that currently has no promising solution. This paper introduces new idea of use of sequence mining algorithms for distinguishing insider attack in network. According to current work we have discovered that mixes of pattern development with Behavior factors are most appropriate for recognizable proof of insider attack in any network. This paper presents experiments in which execution essentially helped in building an ideally estimated data structure representations of the sequence database that requires the need of Behavior parameters joining in insider attack identification calculations.
Keywords :
Insider Attack, Network Attack, Data Mining Techniques, User Behaviour.
Insider attack detection in an enterprise network environment is a critical problem that currently has no promising solution. This paper introduces new idea of use of sequence mining algorithms for distinguishing insider attack in network. According to current work we have discovered that mixes of pattern development with Behavior factors are most appropriate for recognizable proof of insider attack in any network. This paper presents experiments in which execution essentially helped in building an ideally estimated data structure representations of the sequence database that requires the need of Behavior parameters joining in insider attack identification calculations.
Keywords :
Insider Attack, Network Attack, Data Mining Techniques, User Behaviour.
