Detection of Sinkhole Attack in Wireless Sensor Network

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 381)

Abstract

In this paper, we proposed an efficient rule-based intrusion detection system for identifying sinkhole attacks in Wireless Sensor Networks (WSN). The sensor nodes in network are deployed in various hostile environments. The nature of WSNs is wireless and hence, security is the major challenging issue. Sinkhole attack is the major common internal attack on WSNs. These attacks are performed by creating a malicious node with the highest transmission range to the base station. Then this node broadcast sends fake routing message to all its neighbor nodes. We considered popular link quality-based multi-hop routing protocol named as Mint-Route protocol. To identify sinkhole attack, we have implemented an IDS system which consists of suitable rules. These rules will allow the IDS to detect the malicious node successfully. We demonstrated this method in random dissemination of sensor nodes in WSNs. We experimented to confirm the accuracy of our anticipated method.

Keywords

Wireless sensor networks Security RSSI LQI Intrusion detection system Sinkhole attacks 

References

  1. 1.
    Tumrongwittayapak, C., Varakulsiripunth, R.: Detecting Sinkhole attacks in wireless sensor networks. ICROS-SICE International Joint Conference, pp. 1966–1971 ((2009))Google Scholar
  2. 2.
    Venkatraman, K., Vijay Daniel, J., Murugaboopathi, G.: Various attacks in wireless sensor network: survey. Int. J. Soft Comput. Eng. (IJSCE). 3(1), (2013). ISSN:2231-2307Google Scholar
  3. 3.
    Parwekar, P., Reddy, R.: An efficient fuzzy localization approach in wireless sensor network. Fuzzy Digital Object Identifier, pp. 1–6 (2013).  10.1109/FUZZ-IEEE.2013.6622548Publication
  4. 4.
    Ioannis, K., Tassos, D., Thanassis, G., Marios, M.: Intrusion detection of sinkhole attacks in wireless sensor networks. Algorithmic Aspects Wireless Sensor Networks Lecture Notes Comput. Sci. 4837, 150–161 (2008)Google Scholar
  5. 5.
    Md. Ibrahim, A., Mohammad, M.R., Mukul, C.R.: Detecting sinkhole attacks in wireless sensor network using hop count. I. J. Comput. Network Inform. Secur. 3, 50–56 (2015)Google Scholar
  6. 6.
    Levis, P., Madden, S., Polastre, J., et al.: TinyOS: an operating system for sensor networks. Springer, Berlin Heidelberg (2005)Google Scholar
  7. 7.
    Pahlavan, K., Li, X.: Indoor geo-location science and technology. IEEE Commun. Mag. 40(2), 112–118 (2002)CrossRefGoogle Scholar
  8. 8.
    Umashri, K., Dr. Nalini, N.: Detecting sinkhole attack in wireless sensor networks. Int. J. Scient. Eng. Res. 5, 6, (2014)Google Scholar
  9. 9.
    Junaid, A.C., Usman, T., Mohammed, A.A., Rittenhouse, R.G.: Sinkhole vulnerabilities in wireless sensor networks. Int. J. Security Appl. 8(1), 401–410 (2014)Google Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.Anil Neerukonda Institute of Technology and SciencesVisakhapatnamIndia

Personalised recommendations