Detecting Location-Based Attacks in Wireless Sensor Networks Using Sequential Analysis

REFERENCES

• P. Baronti, et al., “Wireless sensor networks: A survey on the state of the art and the 802.15.4 and ZigBee standards”, Comput. Commun., Vol. 30, no. 7, pp. 1655–95, 2007.
   Web of Science ®Google Scholar
• J. Yick, B. Mukherjee, and D. Ghosal, “Wireless sensor network survey”, Comput. Netw., Vol. 52, no. 12, pp. 2292–330, 2008.
   Web of Science ®Google Scholar
• Y. Yan, et al., “A survey on smart grid communication infrastructures: Motivations, requirements and challenges”, IEEE Commun. Surv. Tutor., Vol. 15, no. 1, pp. 5–20, 2013.
   Web of Science ®Google Scholar
• I. F. Akyildiz, et al., “Wireless sensor networks: A survey”, Comput. Netw., Vol. 38, no. 4, pp. 393–422, 2002.
   Web of Science ®Google Scholar
• A. Maghsoudlou, M. St-Hilaire, and T. Kunz, “A survey on geographic routing protocols for mobile ad hoc networks.” Systems and Computer Engineering, Carleton University, Ottawa, ON, Canada. Technical Report SCE-11-03, Oct. 2011.
   Google Scholar
• A. M. Popescu, et al., “Surveying position based routing protocols for wireless sensor and ad-hoc networks.” Int. J. Commun. Netw. Inf. Security (IJCNIS), Vol. 4, no. 1, pp. 41–67, 2012.
   Google Scholar
• Y. Kim, J.-J. Lee, and A. Helmy, “Impact of location inconsistencies on geographic routing in wireless networks.” in Proceedings of the 6th ACM International Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems, San Diego, CA. ACM, 2003, pp. 124–7.
   Google Scholar
• Y. Wei, and Y. Guan, “Lightweight location verification algorithms for wireless sensor networks.”, IEEE Trans. Parallel Distrib. Syst., Vol. 24, no. 5, pp. 938–50, 2013.
   Web of Science ®Google Scholar
• B. Karp, and H.-T. Kung, “GPSR: Greedy perimeter stateless routing for wireless networks.” In Proceedings of the 6th ACM Annual International Conference on Mobile Computing and Networking, Boston, MA. ACM, 2000, pp. 243–54.
   Google Scholar
• S. Kwon, and N. B. Shroff, “Geographic routing in the presence of location errors.” Comput. Netw., Vol. 50, no. 15, pp. 2902–17, 2006.
   Web of Science ®Google Scholar
• Y. Zhang, et al. “Location-based compromise-tolerant security mechanisms for wireless sensor networks.” IEEE J. Select. Areas Commun., Vol. 24, no. 2, pp. 247–60, 2006.
   Web of Science ®Google Scholar
• D. Liu, P. Ning, and W. K. Du, “Attack-resistant location estimation in sensor networks.” In Proceedings of the 4th International Symposium on Information Processing in Sensor Networks, Los Angeles, CA. IEEE Press, 2005.
   Google Scholar
• Q. Zhang, and X. Zhou, “Efficient distributed location verification in wireless sensor networks.” Frontiers Comput. Sci. China, Vol. 4, no. 1, pp. 123–34, 2010.
   Google Scholar
• J. Long, et al. “Achieving source location privacy and network lifetime maximization through tree-based diversionary routing in wireless sensor networks.”, IEEE Access, Vol. 2, pp. 633–51, 2014.
   Google Scholar
• B. Muthusenthil, et al., “the impact of location based attacks on geographic routing protocols” J. Theor. Appl. Inf. Technol., Vol. 60, no. 2, pp. 189–99, 2014.
   Google Scholar
• W. Z. Khan, et al. “Detection and mitigation of node replication attacks in wireless sensor networks: A survey.” Int. J. Distrib. Sensor Netw., Vol. 2013, pp. 1–22, 2013.
   Google Scholar
• P. R. Vamsi, and K. Kant, “Sybil attack detection using sequential hypothesis testing in wireless sensor networks”, presented at the IEEE International Conference on Signal Propagation and Computer Technology, Ajmer, India, Jul. 12–13, 2014.
   Google Scholar
• P. R. Vamsi, and K. Kant, “A lightweight Sybil attack detection framework for wireless sensor networks”, presented at the 7th International Conference on Contemporary Computing, Noida, India, Aug. 7–9, 2014.
   Google Scholar
• J.-W. Ho, M. Wright, and S. K. Das, “ZoneTrust: Fast zone-based node compromise detection and revocation in wireless sensor networks using Sequential hypothesis testing”, IEEE Trans. Depend. Secure Comput., Vol. 9, no. 4, pp. 494–511, 2012.
   Web of Science ®Google Scholar
• A. Wald, Sequential Analysis, Mineola, NY: Courier Corporation, 1973.
   Google Scholar
• I. Chang, and Y.-C., “Application of sequential probability ratio test to computerized criterion-referenced testing.” Sequential Analysis, Vol. 23, no. 1, pp. 45–61, 2004.
   Google Scholar
• K. Cohen, and Q. Zhao, “Quickest anomaly detection: a case of active hypothesis testing”, IEEE Inf. Theory Appl. Workshop (ITA), San Diego, CA, pp. 1–5, 2014.
   Google Scholar
• T. L. Lai. “Sequential analysis: Some classical problems and new challenges.” Statist. Sinica, Vol. 11, no. 2, pp. 303–50, 2001.
   Web of Science ®Google Scholar
• A. Tartakovsky, I. Nikiforov, and M. Basseville, Sequential Analysis: Hypothesis Testing and Changepoint Detection. USA: CRC Press, 2014.
   Google Scholar
• The network simulator ns-2: http://www.isi.edu/nsnam/ns
   Google Scholar
• GPSR source code available at: http://www.icir.org/bkarp/gpsr/gpsr.html
   Google Scholar
• M. Li, et al. “A regional statistics detection scheme against Sybil attacks in WSNs.” In 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), Melbourne, Australia, Jul. 16–18, 2013.
   Google Scholar
• M. B. Jamâa, et al. “EasyLoc: Plug-and-play rss-based localization in wireless sensor networks”, in Cooperative Robots and Sensor Networks, Anis Koubâa and Abdelmajid Khelil, Eds. Berlin Heidelberg: Springer, 2014, pp. 77–98.
   Google Scholar