Abstract

Security and privacy of a system is vulnerable, when an intrusion happens. Intrusion Detection System (IDS) takes an important role in network security as it detects various types of attacks in the network. In this paper, the propose Intrusion Detection System using data mining technique: SVM (Support Vector Machine) and PSO (Particle Swarm Optimization). Here, first PSO performed parameter optimization using SVM to get the optimized value of C (cost) and g (gamma parameter). Then PSO performed feature optimization to get optimized feature. Then these parameters and features are given to SVM to get higher accuracy. The experiment is performed by using NSL-KDD dataset.

Keyword

Support Vector Machine (SVM), Particle Swarm Optimization (PSO), Intrusion Detection System (IDS).

Cite this article

.Intrusion Detection System using Support Vector Machine (SVM) and Particle Swarm Optimization (PSO) . International Journal of Advanced Computer Research. 2014;4(16):808-812.

Refference