Mutual authentication technique for detection of malicious nodes in wireless sensor networks

  • Authors

    • Inderpreet Singh chandigarh university
    • Rajan Kumar chandigarh university
    2018-08-06
    https://doi.org/10.14419/ijet.v7i2.27.12718
  • WSN, LEACH, Sybil, NS2
  • The wireless sensor network is the decentralized type of network in which sensor nodes can join or leave the network when they want. Due to self configuring nature of network security and energy, consumption is the major issue of the network. The Sybil is the denial of service type of attack in which sensor nodes can change its identification multiple times in the network. In this research work, mutual authentication technique is proposed which detect malicious nodes from the network which is responsible to trigger Sybil attack in the network. The simulation of proposed algorithm is performed in NS2 and results shows that proposed technique performs well in terms of energy and throughput

     

     

  • References

    1. [1] M. Cheffena, “Industrial wireless communications over the millimeter wave spectrum: opportunities and challenges,†IEEE Commun., vol. 54, no. 9, pp. 66–72, 2016.

      [2] K. Zhang, X. Liang, R. Lu, and X. Shen, “Sybil attacks and their defenses in the internet of things,†IEEE J. on Internet of Things, vol. 1, no. 5, pp. 372–383, 2014.

      [3] I. Butun, S. Morgera, and R. Sankar, “A survey of intrusion detection systems in wireless sensor networks,†IEEE Commun. Surveys & Tutorials, vol. 16, no. 1, pp. 266–282, 2014.

      [4] Q. Xiong, Y. Liang, K. Li, and Y. Gong, “An energy-ratio-based approach for detecting pilot spoofing attack in multiple-antenna systems,†IEEE Trans. on Inf. Forens. In addition, Security, vol. 10, no. 5, pp. 932–940, 2015.

      [5] S. Ruj, A. Nayak, and I. Stojmenovic, “Pairwise and triple key distribution in wireless sensor networks with applications,†IEEE Trans. Comput., vol. 62, no. 11, pp. 2224–2237, 2013.

      [6] L. Xiao, L. Greenstein, N. Mandayam, and W. Trappe, “Channel-based detection of sybil attacks in wireless networks,†IEEE Trans. Inf. Forens. Security, vol. 4, no. 3, pp. 492–503, 2009.

      [7] Qihao Li, Kuan Zhang, Michael Cheffena and Xuemin (Sherman) Shen, “Channel-based Sybil Detection in Industrial Wireless Sensor Networks: a Multi-kernel Approachâ€, 2017, IEEE.

      [8] Noor Alsaedi, Fazirulhisyam Hashim, A. Sali, “Energy Trust System for Detecting Sybil Attack in Clustered Wireless Sensor Networksâ€, 2015 IEEE 12th Malaysia International Conference on Communications (MICC).

      [9] Salavat Marian, Popa Mircea, “Sybil Attack Type Detection in Wireless Sensor Networks based on Received Signal Strength Indicator detection schemeâ€, 2015, 10th Jubilee IEEE International Symposium on Applied Computational Intelligence and Informatics

      [10] Sepide Moradi, Meysam Alavi, “A distributed method based on mobile agent to detect Sybil attacks in wireless sensor networksâ€, 2016 Eighth International Conference on Information and Knowledge Technology (IKT).

      [11] Panagiotis Sarigiannidis, Eirini Karapistoli and Anastasios A. Economides, “Analysing Indirect Sybil Attacks in Randomly Deployed Wireless Sensor Networksâ€, 2016 IEEE 27th Annual IEEE International Symposium on Personal.

      [12] Roshan Singh Sachan, Mohammad Wazid, AvitaKatal, D P Singh, R H Goudar, “A Cluster Based Intrusion Detection and Prevention Technique for Misdirection Attack in-side WSNâ€, International conference on Communication and Signal Processing, April 3-5, 2013, India.

      [13] G. Padmavathi, Mrs. D. Shanmugapriya, “A Survey of Attacks, Security Mechan-isms andChallenges in Wireless Sensor Networksâ€, International Journal of Computer Science and Information Security,Vol. 4, No. 1 & 2, 2009.

      [14] Kalpana Sharma and M K Ghose, “Wireless Sensor Networks: An Overview on its Se-curity Threats†IJCA Special Issue on “Mobile Ad-hoc Networksâ€MANETs, 2010.

      [15] LVShaohe, Wang Xiaodong, Zhao Xing," Detecting the Sybil Attack Cooperatively in Wireless Sensor Networks", Computational Intelligence and Security 2008,CIS '08 In-ternational Conference on Volume 1Suzhou,pp.442-446,IEEE 2000.

      [16] Baviskar B.R, Patil V.N," Black hole attacks mitigation and prevention in wireless sensor network", International Journal of Innovative Research in Advanced Engineering (IJIRAE), Volume 1, Issue 4, pp.167-169, May 2014.

      [17] Wang Chun-Hsin and Li Yang-Tang, “Active Black Holes Detection in Ad-Hoc Wire-less Networksâ€, Ubiquitous and Future Networks (ICUFN) 2013 Fifth International Conference on Da Nang, pp.94-99, IEEE, 2013.

      [18] Ahmad Salehi S., M.A. Razzaque, ParisaNaraei, Ali Farrokhtala, “ Detection of sink hole Attack in wireless sensor networksâ€, IEEE International Conference on Space Science and Communication (IconSpace), 1-3 July 2013, Melaka, Malaysia.

      [19] Amitabh Mishra, Ketan Nadkarni, and Animesh Patcha,†Intru-Sion Detection in Wireless Ad Hoc Networksâ€, 2004 Ieee 1536-1284-04.

      [20] Ju young Kim, Ronnie D. Caytiles, Kyung Jung Kim, “A Review of the Vulnerabilities and Attacks for Wireless Sensor Networks†Journal of Security Engineering, 2014.

      [21] Kalpana Sharma and M K Ghose, “Wireless Sensor Networks: An Overview on its Se-curity Threats†IJCA Special Issue on “Mobile Ad-hoc Networksâ€MANETs, 2010.

      [22] M.Santhanalakshmi, T.Anushapriya,LathaMathavan Engineering,†An Effective Hybrid intrusion detection system for large scale wireless sensor networksâ€, 2016.

  • Downloads

  • How to Cite

    Singh, I., & Kumar, R. (2018). Mutual authentication technique for detection of malicious nodes in wireless sensor networks. International Journal of Engineering & Technology, 7(2.27), 118-121. https://doi.org/10.14419/ijet.v7i2.27.12718