Intrusion Detection System based on Fuzzy C Means Clustering and Probabilistic Neural Network

Security is always an important issue especially in the case of computer network which is used to transfer personal/confidential information’s, ecommerce and media sharing. Since the network is closely related to operating its conditions hence a careful observation & analysis of network characteristics could describe the state of the network such as network is under specific attack or operating normally. This paper presents an intrusion detection system based on fuzzy C-means clustering and probabilistic neural network which not only reduces the training time but also increases the detection accuracy. The proposed system is tested using KDD99 dataset and the simulation results shows that by selecting effective characteristics and proper training the detection accuracy rate up to 99% is achievable.