期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2018
卷号：7
期号：2
页码：160-167
出版社：Shri Pannalal Research Institute of Technolgy
摘要：In this paper, a Fuzzy based detection system that detects different MANETs attacks is proposed. The proposed system makes use of cluster based architecture to properly organize the nodes in the network. The proposed system use concept of anomaly detection and misuse detection that is based on fuzzy rule sets. The proposed system also makes use of Multilayer Perceptron Neural Network. The Back propagation Neural Network and Feed Forward Neural Network are used to add the results of detection and show the different types of attackers. Advanced Sybil Attack Detection Algorithm is used for the detection of Sybil attack, Wormhole Resistant Hybrid Technique is used for detection of wormhole attack while signal strength and distance is used for detection of hello flood attack. A set of nodes are used for the experimental analysis; 16.54% of the nodes are detected as misbehaving nodes. Hello flood attack is detected at a rate of 98.70%; wormhole attack has a detection rate of 97. 60%; and Sybil attack has a detection rate of 97. 20%.
