Performance analysis of machine learning algorithms for intrusion detection in MANETs

Mobile Ad-hoc network MANET has become an important technology in recent years and the corresponding security problems are getting more and more attention. In this paper, we apply seven well-known machine learning algorithms to detect intrusions in MANETs. We have generated training data under various simulation parameters. We also propose a new measure method which uses five new features to represent the network traffic. The analysis results show that the multilayer perceptron, logistic regression and Support Vector Machine SVM have the best performance and the logistic regression and SVM also get very little time to train the classification model.

[1]  Jung-Min Park,et al.  An overview of anomaly detection techniques: Existing solutions and latest technological trends , 2007, Comput. Networks.

[2]  Ian H. Witten,et al.  The WEKA data mining software: an update , 2009, SKDD.

[3]  Marjan Kuchaki Rafsanjani,et al.  An Optimal Method for Detecting Internal and External Intrusion in MANET , 2010, FGIT-FGCN.

[4]  J. Jubin,et al.  The DARPA packet radio network protocols , 1987, Proceedings of the IEEE.

[5]  Ricardo Staciarini Puttini,et al.  Security in Ad Hoc Networks: a General Intrusion Detection Architecture Enhancing Trust Based Approaches , 2002, Wireless Information Systems.

[6]  Wenke Lee,et al.  Intrusion Detection Techniques for Mobile Wireless Networks , 2003, Wirel. Networks.

[7]  Robert E. Kahn,et al.  The Organization of Computer Resources into a Packet Radio Network , 1977 .

[8]  Farooq Anjum,et al.  Security for Wireless Ad Hoc Networks , 2007 .

[9]  Seong-Moo Yoo,et al.  Black hole attack in mobile Ad Hoc networks , 2004, ACM-SE 42.

[10]  Philip S. Yu,et al.  Cross-feature analysis for detecting ad-hoc routing anomalies , 2003, 23rd International Conference on Distributed Computing Systems, 2003. Proceedings..

[11]  Christos Dimitrakakis,et al.  Intrusion detection in MANET using classification algorithms: The effects of cost and model selection , 2013, Ad Hoc Networks.

[12]  R. M. Chandrasekaran,et al.  Intrusion detection using neural based hybrid classification methods , 2011, Comput. Networks.

[13]  Shiow-Fen Hwang,et al.  Recent developments and experimental guidelines in mobile ad-hoc networks , 2010, Int. J. Wirel. Mob. Comput..

[14]  Dorothy E. Denning,et al.  An Intrusion-Detection Model , 1987, IEEE Transactions on Software Engineering.

[15]  Krishan Kumar,et al.  QoS routing protocols for mobile ad hoc networks: a survey , 2012, Int. J. Wirel. Mob. Comput..

[16]  Wolfgang Banzhaf,et al.  The use of computational intelligence in intrusion detection systems: A review , 2010, Appl. Soft Comput..

[17]  Ali Movaghar-Rahimabadi,et al.  Intrusion Detection: A Survey , 2008, 2008 Third International Conference on Systems and Networks Communications.

[18]  Lin-Xia Yan.  Research on a multi-agent based group awareness model , 2012, Int. J. Wirel. Mob. Comput..

[19]  Mario Gerla,et al.  GloMoSim: A Scalable Network Simulation Environment , 2002 .

[20]  Wenke Lee,et al.  A cooperative intrusion detection system for ad hoc networks , 2003, SASN '03.

[21]  Bo-Chao Cheng,et al.  A Context Adaptive Intrusion Detection System for MANET , 2011, Comput. Commun..

[22]  J. BURCHFIEL,et al.  Functions and structure of a packet radio station , 1975, AFIPS '75.

[23]  Jaideep Srivastava,et al.  Managing Cyber Threats: Issues, Approaches, and Challenges (Massive Computing) , 2005 .

[24]  Yogesh Chaba,et al.  Performance Analysis of Disable IP Broadcast Technique for Prevention of Flooding-Based DDoS Attack in MANET , 2009, J. Networks.

[25]  Bo Sun.  Intrusion detection in mobile ad hoc networks , 2004 .

[26]  Yang Li,et al.  MAC layer anomaly detection in ad hoc networks , 2005, Proceedings from the Sixth Annual IEEE SMC Information Assurance Workshop.

[27]  V. Anjana Devi,et al.  Agent Based Cross Layer Intrusion Detection System for MANET , 2011 .

[28]  Nathan L. Clarke,et al.  A Two-Tier Intrusion Detection System for Mobile Ad Hoc Networks - A Friend Approach , 2006, ISI.

[29]  Yinhui Li,et al.  An efficient intrusion detection system based on support vector machines and gradually feature removal method , 2012, Expert Syst. Appl..

[30]  Chia-Hsu Kuo,et al.  A routing-profitable MAC protocol for Mobile Ad Hoc Networks , 2010, Int. J. Wirel. Mob. Comput..

[31]  Djamel Djenouri,et al.  On Securing MANET Routing Protocol Against Control Packet Dropping , 2007, IEEE International Conference on Pervasive Services.

[32]  Monika Darji,et al.  Secure Leader Election Algorithm Optimized for Power Saving Using Mobile Agents for Intrusion Detection in MANET , 2012, SNDS.

[33]  Gisung Kim,et al.  A distributed sinkhole detection method using cluster analysis , 2010, Expert Syst. Appl..

[34]  Klaus-Robert Müller,et al.  Visualization of anomaly detection using prediction sensitivity , 2005, Sicherheit.