Total views : 232

Detection and Mitigation of Attacks in Cluster based Wireless Sensor Networks using Rule based IDS

Affiliations

  • Department of Electronics and Communication Engineering, SRM University, Kattankulathur, Chennai - 603203,Tamil Nadu, India

Abstract


Objectives: Wireless Sensor Network (WSN) is made up of numerous small nodes; the node senses the happenings in its surroundings and reports the changes to a base station. Most of the sensor nodes are battery operated and their lifetime is less. Methods/Statistical Analysis: The WSN is operated in an open environment, it is prone to misuse. The misuse can either internal or external. External attackers can be prevented by using encryption techniques whereas the internal attackers being a compromised node in the network are hard to prevent. To avoid any further damage by the internal attackers an Intrusion Detection System (IDS) is developed. Rule based detection methodology is adapted to detect the misuse in the network. Findings: Using rule based detection methodology the following attacks such as black hole attack, selective forwarding attack, hello flood attack and replay attack are detected and mitigated. All the mentioned attacks occur in the network layer and its intention is to alter the data communication path. In a network of N nodes, M clusters are formed with each cluster having a cluster head. One node in each cluster has the IDS and monitors the cluster members before the communication starts. Once the attackers are detected within each cluster, the routing protocol is changed accordingly such that the affected cluster heads will not take part in the communication process. Application/Improvements: In existing IDS the attacks are only detected and by using some encryption they are prevented before an attack can happen. In this method the attacks are mitigated prior to the actual data transmission.

Keywords

Black Hole Attack, Clustered Wireless Sensor Networks, Hello Flood Attack, Intrusion Detection System, Rule based Detection, Selective Forwarding Attack.

Full Text:

 |  (PDF views: 181)

References


  • Akyildiz F, Su W, Sankarasubramaniam Y, Cayirci E. Wireless sensor networks: A survey. Elsevier Science Computer Networks SA. 2002; 38:393-422.
  • Lu G, Xue W. Adaptive weighted fusion algorithm for monitoring system of forest fire based on wireless sensor networks. Conference on Computer Modeling and Simulation; Hainan. 2010. p. 414-7.
  • Alemdar A, Ibnkahla M. Wireless sensor networks: Applications and challenges. IEEE Signal Processing and its Applications. 2007:1-6.
  • Zhou Y, Fang Y. Security wireless sensor networks: A survey. IEEE Communications Survey and Tutorials. 2008:6-28.
  • Stallings W. Cryptography and network security, principles and practice. 5th ed. 2013.
  • Butun I, Morgera SD, Sankar R. A survey of intrusion detection systems in wireless sensor networks. IEEE Communications Surveys and Tutorials; 2014; 16(1):266-82.
  • Venkatraman K, Daniel JV, Murugaboopathi G. Various attacks in wireless sensor network: Survey. IJSCE. 2013 Mar; 3(1):1-4.
  • Sobh TS. Wired and wireless intrusion detection system: Classifications, good characteristics and state-of-the-art. Elsevier J Computer Standards and Interfaces. 2006 Mar; 28(6):670-94.
  • Deshmukh R, Deshmukh R, Sharma M. Rule-based and cluster-based intrusion detection technique for Wireless Sensor Network. International Journal of Computer Science and Mobile Computing. 2013 Jun; 2(6):1-9.
  • Sheela D, Srividhya VR, Begam A, Anjali, Chidanand GM. Detecting black hole attacks in Wireless Sensor Networks using mobile agent. International Conference on Artificial Intelligence and Embedded Systems (ICAIES’2012); Singapore. 2012 Jul 15-16. p. 1-4.
  • Alajmi NM, Elleithy KM. Comparative analysis of selective forwarding attacks over Wireless Sensor Networks. International Journal of Computer Applications. 2015 Feb; 111(14):1-12.
  • Md. Abdullah I, Rahman MM, Roy MC. Detecting sinkhole attacks in Wireless Sensor Network using hop count. I J Computer Network and Information Security. 2015; 3:50-6.
  • Hassoubah RS, Solaiman SM, Abdullah MA. Intrusion detection of hello flood attack in wsns using location verification scheme. International Journal of Computer and Communication Engineering. 2015 Feb 12; p. 1-10.
  • Dharini N, Balakrishnan R, Renold AP. Distributed detection of flooding and gray hole attacks in Wireless Sensor Network. International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM); Chennai, T.N., India; 2015 May 6-8. p. 178-84.
  • Palte RR, Satao R. Aggregated identity-based signature to transmit data securely and efficiently in clustered WSN. International Conference on Computing Communication Control and Automation; Pune, India. 2015 Feb 26-27. P. 138-42.
  • da Silva AP, Martins M, Rocha B, Loureiro A, Ruiz L, Wong HC. Decentralized intrusion detection in Wireless Sensor Networks. Proceedings of 1st ACM International Workshop on Quality of Service and Security in Wireless and Mobile Networks (Q2SWinet ‘05); 2005 Oct.
  • Amudhavel J, Brindha V, Anantharaj B, Karthikeyan P, Bhuvaneswari B, Vasanthi M, Nivetha D, Vinodha D. A survey on intrusion detection system: State of the art review. Indian Journal of Science and Technology. 2016 Mar; 9(11):1-9.

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.