A novel support vector machine based intrusion detection system for mobile ad hoc networks

The performance of mobile ad hoc networks (MANETs) is significantly affected by the malicious nodes. One of the most common attacks in MANETs is denial of service (DoS); a type of intrusion specifically designed to target service integrity and availability of a certain network node. Hence, it is important to use an efficient intrusion detection system (IDS) that detects and removes the malicious nodes in the network to improve the performance by monitoring the network traffic continuously. The main contribution of this paper is the integration of an IDS into MANETs as a reliable and potent solution. A new approach to intrusion detection is developed based on support vector machine algorithm. The proposed IDS can detect the DoS type attacks at a high detection rate with a simple structure and short computing time. It is shown by extensive computer simulation that the proposed IDS improves the reliability of the network significantly by detecting and removing the malicious nodes in the system. The performance of the suggested approach is independent of the network routing protocol. The detection rate of the system is also not effected by node mobility and network size.

[1]  Rajendra V. Boppana,et al.  Mitigating malicious control packet floods in ad hoc networks , 2005, IEEE Wireless Communications and Networking Conference, 2005.

[2]  Christina Lioma,et al.  The tipping point: F-score as a function of the number of retrieved items , 2012, Inf. Process. Manag..

[3]  Asaf Shabtai,et al.  Mitigating Denial of Service Attacks in OLSR Protocol Using Fictitious Nodes , 2016, IEEE Transactions on Mobile Computing.

[4]  Brij B. Gupta,et al.  An Efficient Scheme to Prevent DDoS Flooding Attacks in Mobile Ad-Hoc Network (MANET) , 2014 .

[5]  Michael P. Howarth,et al.  A Survey of MANET Intrusion Detection & Prevention Approaches for Network Layer Attacks , 2013, IEEE Communications Surveys & Tutorials.

[6]  Andrew H. Sung,et al.  Detecting denial of service attacks using support vector machines , 2003, The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ '03..

[7]  Yi Pan,et al.  ZSBT: A Novel Algorithm for Tracing DoS Attackers in MANETs , 2006, EURASIP J. Wirel. Commun. Netw..

[8]  J. Amudhavel,et al.  A Survey on Intrusion Detection System: State of the Art Review , 2016 .

[9]  Ravi Sankar,et al.  A Survey of Intrusion Detection Systems in Wireless Sensor Networks , 2014, IEEE Communications Surveys & Tutorials.

[10]  Dilip Sarkar,et al.  Convergence in the Calculation of the Handoff Arrival Rate: A Log-Time Iterative Algorithm , 2006, EURASIP J. Wirel. Commun. Netw..

[11]  Nei Kato,et al.  A survey of routing attacks in mobile ad hoc networks , 2007, IEEE Wireless Communications.

[12]  A. Kannammal,et al.  An integrated intelligent paradigm to detect DDoS attack in mobile ad hoc networks , 2015, Int. J. Embed. Syst..

[13]  Jianwu Dang,et al.  Improved support vector machine algorithm for heterogeneous data , 2015, Pattern Recognit..

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

[15]  Abdul Hanan Abdullah,et al.  FSM-F: Finite State Machine Based Framework for Denial of Service and Intrusion Detection in MANET , 2016, PloS one.

[16]  Marenglen Biba,et al.  Machine learning for intrusion detection in MANET: a state-of-the-art survey , 2015, Journal of Intelligent Information Systems.

[17]  Saman Taghavi Zargar,et al.  A Survey of Defense Mechanisms Against Distributed Denial of Service (DDoS) Flooding Attacks , 2013, IEEE Communications Surveys & Tutorials.

[18]  Ilango Krishnamurthi,et al.  Enhanced OLSR for defense against DOS attack in ad hoc networks , 2013, Journal of Communications and Networks.

[19]  Sunil Kumar,et al.  Intrusion detection in mobile ad hoc networks: techniques, systems, and future challenges , 2016, Secur. Commun. Networks.

[20]  Roberto Di Pietro,et al.  Security in wireless ad-hoc networks - A survey , 2014, Comput. Commun..

[21]  S. M. Ramesh,et al.  Biologically inspired artificial intrusion detection system for detecting wormhole attack in MANET , 2014, Wirel. Networks.

[22]  G. Akilarasu,et al.  Wormhole-Free Routing and DoS Attack Defense in Wireless Mesh Networks , 2017, Wirel. Networks.

[23]  M. Poongodi,et al.  A Novel Intrusion Detection System Based on Trust Evaluation to Defend Against DDoS Attack in MANET , 2015, Arabian Journal for Science and Engineering.

[24]  Rutvij H. Jhaveri,et al.  DoS Attacks in Mobile Ad Hoc Networks: A Survey , 2012, 2012 Second International Conference on Advanced Computing & Communication Technologies.