|International Journal of Computer Applications
|Foundation of Computer Science (FCS), NY, USA
|Volume 158 - Number 8
|Year of Publication: 2017
|Authors: Aliya Ahmad, Bhanu Pratap Singh Senga
Aliya Ahmad, Bhanu Pratap Singh Senga . Instruction Detection System based on Support Vector Machine using BAT Algorithm. International Journal of Computer Applications. 158, 8 ( Jan 2017), 27-30. DOI=10.5120/ijca2017912843
Now these day Computers becomes vital part of everyday life and hence use of internet becomes more and more. Due to internet, computers are becomes vulnerable of different kinds of security threats. Therefore it is required that we need to have efficient security method in order to avoid leakage of important data or misuse of data. This security method is called as Intrusion Detection System (IDS). Since from last two decades IDS becomes core area of many researchers and many methods are already presented for efficient intrusion detection and classification. Most of methods are out dated as many new attacks generated by hackers. In this project our main aim is to presented scalable and efficient method for intrusion detection and classifications. Evolutionary algorithm has recently been applied to the anomaly based intrusion detection in computer networks. Evolutionary algorithm is a new technique used to solve various problems in the field of information security. To overcome these deficiencies of the IDS, the network system, a new double detection of IDS based on the integration of Evolutionary algorithm BAT and SVM .The BAT-SVM helps us solve the problem and the correlation theory is proposed model solves the problem of the unknown and the rapid development of damaging attacks.