Skip to main content

Advertisement

SpringerLink
Log in

An Energy Aware Trust Based Intrusion Detection System with Adaptive Acknowledgement for Wireless Sensor Network

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Today modern and innovative applications for health care environment based on Wireless Sensor Network (WSN) are being developed in the commercial sector. The emerging sensor networks are rapidly becoming a fundamental part of medical solutions due to increase in accessibility for healthcare professionals/patients and ultimately leading to reduced healthcare costs. Health watch is becoming popular, however securing data becomes critical as privacy issues are a major concern in wireless systems. Finding threats and blocking them without affecting the network is essential without increasing the processing overheads and energy. In this paper, a Trust Based Adaptive Acknowledgment (TRAACK) Intrusion-Detection System for WSN based on number of active successful deliveries, and Kalman filter to predict node trust is proposed. In TRAACK the entire route based trust strength for multi hop sensor networks is reverted to nodes acting as Security Agent. Based on trust value of entire route, Acknowledgement is initiated on select packets to decrease control overhead. It is observed that the packet delivery ratio for the proposed TRAACK method improves even when malicious nodes are present, the proposed technique TRAACK is able to detect malicious nodes and avoid them in the route discovery process. Simulations show improved performance in the presence of malicious nodes without compromise in energy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  1. Yick, J., Mukherjee, B., & Ghosal, D. (2008). Wireless sensor network survey. Computer Networks, 52(12), 2292–2330.

    Article  Google Scholar 

  2. Omogbadegun, Z. O., & Ayo, C. K. (2007). Impact of mobile and wireless technology on healthcare delivery services. In 3G GSM & mobile computing: An emerging growth engine for national development (pp. 164–171).

  3. Viani, F., Oliveri, G., Donelli, M., Lizzi, L., Rocca, P., & Massa, A. (2010, September). WSN-based solutions for security and surveillance. In 2010 European microwave conference (EuMC) (pp. 1762–1765). IEEE.

  4. Sun, F., Zhao, Z., Fang, Z., Du, L., Xu, Z., & Chen, D. (2014). A review of attacks and security protocols for wireless sensor networks. Journal of Networks, 9(5), 1103–1113.

    Article  Google Scholar 

  5. Rezvani, M., Ignjatovic, A., Bertino, E., & Jha, S. (2015). Secure data aggregation technique for wireless sensor networks in the presence of collusion attacks. IEEE Transactions on Dependable and Secure Computing, 12(1), 98–110.

    Article  Google Scholar 

  6. Yu, Y., Li, K., Zhou, W., & Li, P. (2012). Trust mechanisms in wireless sensor networks: Attack analysis and countermeasures. Journal of Network and Computer Applications, 35(3), 867–880.

    Article  Google Scholar 

  7. Shafiei, H., Khonsari, A., Derakhshi, H., & Mousavi, P. (2014). Detection and mitigation of sinkhole attacks in wireless sensor networks. Journal of Computer and System Sciences, 80(3), 644–653.

    Article  MATH  Google Scholar 

  8. Athmani, S., Boubiche, D. E., & Bilami, A. (2013, June). Hierarchical energy efficient intrusion detection system for black hole attacks in WSNs. In 2013 World Congress on Computer and Information Technology (WCCIT) (pp. 1–5). IEEE.

  9. Shi, Y., & Hou, Y. T. (2009). Optimal base station placement in wireless sensor networks. ACM Transactions on Sensor Networks (TOSN), 5(4), 32.

    Article  Google Scholar 

  10. Sun, B., Osborne, L., Xiao, Y., & Guizani, S. (2007). Intrusion detection techniques in mobile ad hoc and wireless sensor networks. IEEE Wireless Communications, 14(5), 56–63.

    Article  Google Scholar 

  11. Scarfone, K., Mell, P. (2007). Guide to intrusion detection and prevention systems (IDPS). Special publication 800-94.

  12. Chenguang, H., & Xuejun, S. (2008). An energy-efficient message passing approach in MAC design for wireless sensor networks. In 4th IEEE international conference on circuits and systems for communications, 2008. ICCSC 2008 (pp. 550–554). IEEE.

  13. Liu, K., Deng, J., Varshney, P. K., & Balakrishnan, K. (2007). An acknowledgment-based approach for the detection of routing misbehavior in MANETs. IEEE Transactions on Mobile Computing, 6(5), 536–550.

    Article  Google Scholar 

  14. Madhavi, S. (2008). An intrusion detection system in mobile adhoc networks. In International conference on information security and assurance, 2008. ISA 2008 (pp. 7–14). IEEE.

  15. Abduvaliyev, A., Pathan, A. S. K., Zhou, J., Roman, R., & Wong, W. C. (2013). On the vital areas of intrusion detection systems in wireless sensor networks. Communications Surveys & Tutorials, IEEE, 15(3), 1223–1237.

    Article  Google Scholar 

  16. Sourour, M., Adel, B., & Tarek, A. (2009). Adaptive IDS alerts correlation according to the traffic type and the attacks properties. In IEEE international advance computing conference, 2009. IACC 2009 (pp. 1653–1658). IEEE.

  17. Bensefia, H., & Ghoualmi, N. (2011). A new approach for adaptive intrusion detection. In 2011 Seventh international conference on computational intelligence and security (CIS) (pp. 983–987). IEEE.

  18. Yi, P., Zhu, T., Zhang, Q., Wu, Y., & Li, J. (2012). Green firewall: An energy-efficient intrusion prevention mechanism in wireless sensor network. In 2012 IEEE global communications conference (GLOBECOM) (pp. 3037–3042). IEEE.

  19. Hsieh, C.-F., Chen, R.-C., & Huang, Y.-F. (2014). Applying an ontology to a patrol intrusion detection system for wireless sensor networks. International Journal of Distributed Sensor Networks, 2014, 14. doi:10.1155/2014/634748.

    Google Scholar 

  20. Chowdhury, C., & Neogy, S. (2011). Mobile agent security based on trust model in MANET. In A. Abraham, J. L. Mauri, J. F. Buford, J. Suzuki & S. M. Thampi (Eds.), Advances in computing and communications (pp. 129–140). Berlin: Springer.

    Google Scholar 

  21. Thachil, F., & Shet, K. C. (2012). A trust based approach for AODV protocol to mitigate black hole attack in MANET. In 2012 international conference on computing sciences (ICCS) (pp. 281–285). IEEE.

  22. Biswas, S., Nag, T., & Neogy, S. (2014). Trust based energy efficient detection and avoidance of black hole attack to ensure secure routing in MANET. In Applications and innovations in mobile computing (AIMoC), 2014 (pp. 157–164). IEEE.

  23. Dave, D., & Dave, P. (2014). An effective black hole attack detection mechanism using permutation based acknowledgement in MANET. In International conference on advances in computing, communications and informatics ICACCI, 2014 (pp. 1690–1696). IEEE.

  24. Manoj, V., Raghavendiran, N., Aaqib, M., & Vijayan, R. (2012). Trust based certificate authority for detection of malicious nodes in MANET. In P. Venkata Krishna, M. Rajasekhara Babu & E. Ariwa (Eds.), Global trends in computing and communication systems (pp. 392–401). Berlin: Springer.

    Google Scholar 

  25. Al-Roubaiey, A., Sheltami, T., Mahmoud, A., Shakshuki, E., & Mouftah, H. (2010). AACK: Adaptive acknowledgment intrusion detection for MANET with node detection enhancement. In 2010 24th IEEE international conference on advanced information networking and applications (AINA) (pp. 634–640). IEEE.

  26. Sheltami, T., Basabaa, A., & Shakshuki, E. (2014). A3ACKs: Adaptive three acknowledgments intrusion detection system for MANETs. Journal of Ambient Intelligence and Humanized Computing, 5(4), 611–620.

    Article  Google Scholar 

  27. Archana, T., & Rajkumar, N. (2014). Enhanced acknowledgement based intrusion detection for MANETs. In 2014 international conference on information communication and embedded systems (ICICES) (pp. 1–5). IEEE.

  28. Zhao, Y. Z., Miao, C., Ma, M., Zhang, J. B., & Leung, C. (2012). A survey and projection on medium access control protocols for wireless sensor networks. ACM Computing Surveys (csuR), 45(1), 7.

    Article  MATH  Google Scholar 

  29. Ye, W., Heidemann, J., & Estrin, D. (2004). Medium access control with coordinated adaptive sleeping for wireless sensor networks. IEEE/ACM Transactions on Networking, 12(3), 493–506.

    Article  Google Scholar 

  30. Pham, H., & Jha, S. (2005). Addressing mobility in wireless sensor media access protocol. International Journal of Distributed Sensor Networks, 1(2), 269–280.

    Article  Google Scholar 

  31. Thangaraj, M., Anuradha, S., & Grace, P. S. (2014). A study of energy model in wsn routing using omnet++. International Journal of Application or Innovation in Engineering & Management (IJAIEM), 3.

  32. Otero, A., Gazca, L., Huerta, M., & Sagbay, G. (2015). A flooding routing algorithm for a wireless sensor network for seismic events. In 2015 international conference on computing systems and telematics (ICCSAT) (pp. 1–6). IEEE.

  33. Somasundaram, K. K., & Baras, J. S. (2009). Performance improvements in distributed estimation and fusion induced by a trusted core. In 12th international conference on information fusion, 2009. FUSION’09 (pp. 1942–1949). IEEE.

  34. Ishmanov, F., Kim, S. W., & Nam, S. Y. (2015). A robust trust establishment scheme for wireless sensor networks. Sensors, 15(3), 7040–7061.

    Article  Google Scholar 

  35. Shakshuki, E. M., Kang, N., & Sheltami, T. R. (2013). EAACK—A secure Intrusion-Detection System for MANETs. IEEE Transactions on Industrial Electronics, 60(3), 1089–1098.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Information Technology, Velalar College of Engineering and Technology, Erode, Tamilnadu, India

    G. Rajeshkumar

  2. Department of Electronics and Communication Engineering, Velalar College of Engineering and Technology, Erode, Tamilnadu, India

    K. R. Valluvan

Authors
  1. G. Rajeshkumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. K. R. Valluvan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to G. Rajeshkumar.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rajeshkumar, G., Valluvan, K.R. An Energy Aware Trust Based Intrusion Detection System with Adaptive Acknowledgement for Wireless Sensor Network. Wireless Pers Commun 94, 1993–2007 (2017). https://doi.org/10.1007/s11277-016-3349-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-016-3349-y

Keywords

Search

Navigation