Advertisement

Wireless Personal Communications

, Volume 101, Issue 2, pp 915–929 | Cite as

An Improved Pillar K-Means Based Protocol for Privacy-Preserving Location Monitoring in Wireless Sensor Network

  • S. M. Soumyasri
  • Rajkiran Ballal
Article
  • 52 Downloads

Abstract

The main criteria affecting the wireless sensor network is the security of data transmission. This paper proposed a security model for preserving the data transmission by enhancing a location monitoring and privacy-preserving protocol in the wireless sensor network. The proposed approach in this paperwork incorporates improved pillar k-means and hybrid location-privacy aware algorithm for increasing the security of wireless sensor network. The sensor network is used by different users, where the network authenticates its user by monitoring and preserving the network from the connected user. The proposed hybrid algorithm reduces the overall cost regarding communication and computational while the quality-aware increases the accuracy of location to the server. The improved pillar k-means algorithm proposed in this work to cluster the sensor nodes into a set of cluster nodes. The clustering process groups the network into nodes and searches the transmission node is monitored and secured. The output of the proposed work is carried out in MatLab platform, and it was compared with existing protocol, and the result shows the proposed IPLPA is the least possible method for preserving security regarding location monitoring and privacy in the wireless sensor network.

Keywords

Improved pillar k-means clustering Location aware algorithm Privacy-aware algorithm Location monitoring Privacy preserving 

Notes

Compliance with Ethical Standards

Conflict of interest

Soumyasri SM and Rajkiran Ballal declares that they has no conflict of interest.

Human and Animal Rights

This article does not contain any studies with human participants or animals performed by any of the authors.

References

  1. 1.
    Tang, D., Li, T., Ren, J., & Wu, J. (2015). Cost-aware secure routing (CASER) protocol design for wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 26(4), 960–973.CrossRefGoogle Scholar
  2. 2.
    Balavalad, K. B., Atageri, A. C., Patil, P. S., & Angadi, B. M. (2014). A privacy-preserving location monitoring system for WSNs with blocking misbehaving users in anonymity networks. Journal of Advances in Computer Networks, 2(4), 248–252.CrossRefGoogle Scholar
  3. 3.
    Sheng, Z., Yang, S., Yu, Y., Vasilakos, A., Mccann, J., & Leung, K. (2013). A survey on the IETF protocol suite for the internet of things: Standards, challenges, and opportunities. IEEE Wireless Communications, 20(6), 91–98.CrossRefGoogle Scholar
  4. 4.
    Jagadha, C., & Umamaheswari, P. (2013). Novel security issues for wireless sensor networks. International Conference on Emerging Trends in Engineering and Techno – Sciences, 7(11), 7–11.Google Scholar
  5. 5.
    Raj, M., Li, N., Liu, D., Wright, M., & Das, S. K. (2014). Using data mules to preserve source location privacy in wireless sensor networks. Pervasive and Mobile Computing, 11, 244–260.CrossRefGoogle Scholar
  6. 6.
    Shi, R., Goswami, M., Gao, J., & Gu, X. (2013). Is random walk truly memory less-traffic analysis and source location privacy under random walks. In Proceedings of IEEE INFOCOM (pp. 3021–3029).Google Scholar
  7. 7.
    Yao, L., Kang, L., Deng, F., Deng, J., & Wu, G. (2013). Protecting source–location privacy based on multirings in wireless sensor networks. Concurrency and Computation: Practice and Experience, 27(15), 3863–3876.CrossRefGoogle Scholar
  8. 8.
    Kamat, P., Zhang, Y., Trappe, W., & Ozturk, C. (2005). Enhancing source location privacy in sensor network routing. In Proceedings of 25th IEEE international conference on distributed computing systems (pp. 599–608).Google Scholar
  9. 9.
    Long, J., Dong, M., Ota, K., & Liu, A. (2014). Achieving source location privacy and network lifetime maximization through tree-based diversionary routing in wireless sensor networks. IEEE Access, 2, 633–651.CrossRefGoogle Scholar
  10. 10.
    Alrajeh, N. A., Khan, S., & Shams, B. (2013). Intrusion detection systems in wireless sensor networks: A review. International Journal of Distributed Sensor Networks, 9(5), 1–7.CrossRefGoogle Scholar
  11. 11.
    George, C. M., & Kumar, M. (2013). Cluster based location privacy in wireless sensor networks against a universal adversary. In Proceedings of IEEE international conference on information communication and embedded systems (ICICES) (pp. 288–293).Google Scholar
  12. 12.
    Sha, K., Gehlot, J., & Greve, R. (2013). Multipath routing techniques in wireless sensor networks: A survey. Wireless Personal Communications, 70(2), 807–829.CrossRefGoogle Scholar
  13. 13.
    Sahingoz, O. K. (2013). Mobile networking with UAVs: Opportunities and challenges. In Proceedings of IEEE international conference on unmanned aircraft systems (ICUAS) (pp. 933–941).Google Scholar
  14. 14.
    Michael, K., & Clarke, R. (2013). Location and tracking of mobile devices: Überveillance stalks the streets. Computer Law & Security Review, 29(3), 216–228.CrossRefGoogle Scholar
  15. 15.
    Sanghvi, N. (2012). Exploring secured location data for preserving in scanning system. International Journal of Advanced Computer and Mathematical Sciences, 3(3), 343–347.Google Scholar
  16. 16.
    Wu, D., Zhang, B., Li, H., & Cheng, X. (2014). Target counting in wireless sensor networks. The art of wireless sensor networks (pp. 235–269). Berlin: Springer.CrossRefGoogle Scholar
  17. 17.
    Fire, M., Goldschmidt, R., & Elovici, Y. (2014). Online social networks: Threats and solutions. IEEE Communications Surveys & Tutorials, 16(4), 2019–2036.CrossRefGoogle Scholar
  18. 18.
    Lee, S., Kim, H., & Lee, S. W. (2013). Security concerns of identity authentication and context privacy preservation in uHealthcare System. In Proceedings of IEEE ACIS international conference on software engineering, artificial intelligence, networking and parallel/distributed computing (SNPD) (pp. 107–112). IEEE.Google Scholar
  19. 19.
    Gymrek, M., McGuire, A. L., Golan, D., Halperin, E., & Erlich, Y. (2013). Identifying personal genomes by surname inference. Science, 339(6117), 321–324.CrossRefGoogle Scholar
  20. 20.
    Pandey, M., & Verma, S. (2014). Privacy provisioning in wireless sensor networks. Wireless Personal Communications, 75(2), 1115–1140.CrossRefGoogle Scholar
  21. 21.
    Chow, Chi.-Yin., Mokbel, M. F., & He, T. (2011). A privacy-preserving location monitoring system for wireless sensor networks. IEEE Transactions on Mobile Computing, 10(1), 94–107.CrossRefGoogle Scholar
  22. 22.
    Ngai, E. C., & Rodhe, I. (2013). On providing location privacy for mobile sinks in wireless sensor networks. Wireless Networks, 19(1), 115–130.CrossRefGoogle Scholar
  23. 23.
    Lu, R., Lin, X., & Shen, X. (2013). SPOC: A secure and privacy-preserving opportunistic computing framework for mobile-healthcare emergency. IEEE Transactions on Parallel and Distributed Systems, 24(3), 614–624.CrossRefGoogle Scholar
  24. 24.
    Usman, A., & Shami, S. H. (2013). Evolution of communication technologies for smart grid applications. Renewable and Sustainable Energy Reviews, 19, 191–199.CrossRefGoogle Scholar
  25. 25.
    Yao, L., Kang, L., Shang, P., & Wu, G. (2013). Protecting the sink location privacy in wireless sensor networks. Personal and Ubiquitous Computing, 17(5), 883–893.CrossRefGoogle Scholar
  26. 26.
    Zhu, Z., & Cao, G. T. (2013). Towards privacy preserving and collusion resistance in a location proof updating system. IEEE Transactions on Mobile Computing, 12(1), 51–64.CrossRefGoogle Scholar
  27. 27.
    Barakbah, A. R., & Kiyoki, Y. (2009). A pillar algorithm for k-means optimization by distance maximization for initial centroid designation. In Proceedings of IEEE symposium on computational intelligence and data mining (pp. 61–68).Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceVisvesvaraya Technological University (VTU)BelagaviIndia
  2. 2.Mangalore Marine College and TechnologyMangaloreIndia

Personalised recommendations