Intrusion Detection based on K-Means Clustering and Ant Colony Optimization: A Survey
Chetan Gupta, Amit Sinhal, Rachana Kamble · International Journal of Computer Applications · 2013
Identifying intrusions is the process called intrusion detection.In simple manner the act of comprising a system is called intrusion.An intrusion detection system (IDS) inspects all inbound and outbound activity and identifies suspicious patterns that may indicate a system attack from someone attempting to compromise a system.If we think of the current scenario then several new intrusion that cannot be prevented by the previous algorithm, IDS is introduced to detect possible violations of a security policy by monitoring system activities and response in all times for betterment.If we uncover the counterfeit marque in a circumspect bulletin climate, an affirmation seat is initiated to prophesy or lessen the damage to the system.As a result it is a keen intrigue.In this dissertation we survey several aspects with the traditional techniques of intrusion detection we elaborate our proposed work.We also come with some future suggestions, which can provide a better way in this direction.For the above survey we also discuss K-Means and Ant Colony optimization (ACO).