Fuzzy Based Intrusion Detection Systems in MANET

Abstract Mobile adhoc network (MANET) is an infrastructure less wireless network and self-organized. During communication mobile adhoc network do not use any proper infrastructure so that MANET initiates request for data transfer, so MANET is vulnerable to various type of attacks such as black hole attack, warm hole attack, gray hole attack. The proposed system is to detect the malicious behavior of node by intrusion detection system with fuzzy logic technique and also to identify the type of attacks. The system is robust enough to detect attacks such as black hole attack and gray hole attack and also able to prevent those kind of attacks by using efficient node blocking mechanism such that the proposed system provides a secure communication between nodes

[1]  Nei Kato,et al.  Detecting Blackhole Attack on AODV-based Mobile Ad Hoc Networks by Dynamic Learning Method , 2007, Int. J. Netw. Secur..

[2]  Peter J. Bentley,et al.  Towards an artificial immune system for network intrusion detection: an investigation of clonal selection with a negative selection operator , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[3]  Michael P. Howarth,et al.  Adaptive intrusion detection & prevention of denial of service attacks in MANETs , 2009, IWCMC.

[4]  Chen Wei,et al.  A Novel Gray Hole Attack Detection Scheme for Mobile Ad-Hoc Networks , 2007, 2007 IFIP International Conference on Network and Parallel Computing Workshops (NPC 2007).

[5]  Stephanie Forrest,et al.  Intrusion Detection Using Sequences of System Calls , 1998, J. Comput. Secur..

[6]  Henk A. van der Vorst,et al.  Computational methods for large eigenvalue problems , 2002 .

[7]  Peter J. Bentley,et al.  An evaluation of negative selection in an artificial immune system for network intrusion detection , 2001 .

[8]  Tao Jiang,et al.  Intrusion detection of in-band wormholes in MANETs using advanced statistical methods , 2008, MILCOM 2008 - 2008 IEEE Military Communications Conference.

[9]  Yih-Chun Hu,et al.  Rushing attacks and defense in wireless ad hoc network routing protocols , 2003, WiSe '03.

[10]  Wang Yunwu Using Fuzzy Expert System Based on Genetic Algorithms for Intrusion Detection System , 2009, 2009 International Forum on Information Technology and Applications.

[11]  Arputharaj Kannan,et al.  Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM , 2012, Comput. Intell. Neurosci..

[12]  Jens Tölle,et al.  Detecting Black Hole Attacks in Tactical MANETs using Topology Graphs , 2007 .

[13]  Mahmut T. Kandemir,et al.  The Sleep Deprivation Attack in Sensor Networks: Analysis and Methods of Defense , 2006, Int. J. Distributed Sens. Networks.

[14]  Susan M. Bridges,et al.  FUZZY DATA MINING AND GENETIC ALGORITHMS APPLIED TO INTRUSION DETECTION , 2002 .

[15]  Andrew H. Sung,et al.  Intrusion detection using neural networks and support vector machines , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).