DETECTING SYBIL ATTACKS IN WIRELESS SENSOR NETWORKS USING SEQUENTIAL ANALYSIS

Publications

Share / Export Citation / Email / Print / Text size:

International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering , Engineering, Electrical & Electronic

GET ALERTS

eISSN: 1178-5608

DESCRIPTION

19
Reader(s)
40
Visit(s)
0
Comment(s)
0
Share(s)

VOLUME 9 , ISSUE 2 (June 2016) > List of articles

DETECTING SYBIL ATTACKS IN WIRELESS SENSOR NETWORKS USING SEQUENTIAL ANALYSIS

P. Raghu Vamsi * / Krishna Kant *

Keywords : Sensor networks, Sybil attacks, malicious activities, sequential analysis, received signal strength, false identity, false location information.

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 9, Issue 2, Pages 651-680, DOI: https://doi.org/10.21307/ijssis-2017-889

License : (CC BY-NC-ND 4.0)

Received Date : 03-December-2015 / Accepted: 31-March-2016 / Published Online: 01-June-2016

ARTICLE

ABSTRACT

Wireless Sensor Networks (WSNs) suffer from many security attacks when deployed either in remote or hostile environments. Among possible attacks, the Sybil attack is one of the severe attacks in which malicious nodes report false identities and location information such that the remaining nodes believe that many nodes exist in their vicinity. The current study proposes a method for detecting Sybil attack using sequential analysis. This method works in two stages. First, it collects the evidences by observing neighboring node activities. Further, the collected evidences are consolidated to provide input to the second stage. In the second stage, collected evidences are validated using the sequential probability ratio test to decide whether the neighbor node is Sybil or benign. The proposed method has been evaluated using the network simulator ns-2. Simulation results show that the proposed method is robust in detecting Sybil attacks with very low false positive and false negative rates.

Content not available PDF Share

FIGURES & TABLES

REFERENCES

[1] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “Wireless sensor networks: a survey," Computer networks, vol. 38, no. 4, pp. 393-422, 2002.
[2] C. Karlof and D. Wagner, “Secure routing in wireless sensor networks: Attacks and countermeasures," Ad hoc networks, vol. 1, no. 2, pp. 293-315, 2003.
[3] Q. Zhang, P. Wang, D. S. Reeves, and P. Ning, “Defending against sybil attacks in sensor networks," in Distributed Computing Systems Workshops, 2005. 25th IEEE International Conference on, pp. 185-191, IEEE, 2005.
[4] E. Fadel, V. Gungor, L. Nassef, N. Akkari, M. A. Maik, S. Almasri, and I. F. Akyildiz, “A survey on wireless sensor networks for smart grid," Computer Communications, vol. 71, pp 22-33, November 2015.
[5] Bhattacharjee, D., and R. Bera. "Development of smart detachable wireless sensing system for environmental monitoring." International Journal on Smart Sensing and Intelligent Systems, vol. 7, no. 3, 2014,pp 1239-1253.
[6] Q. Yang, X. Zhu, H. Fu, and X. Che, “Survey of security technologies on wireless sensor networks," Journal of Sensors, Volume 2015, pp 1-9.
[7] A. Wheeler, “Commercial applications of wireless sensor networks using zigbee," IEEE Communications Magazine, vol. 45, no. 4, pp. 70-77, 2007.
[8] El Alami, Hassan, and Abdellah NAJID. "SEFP: A New Routing Approach Using Fuzzy Logic for Clustered Heterogeneous Wireless Sensor Networks", International Journal on Smart Sensing & Intelligent Systems, vol. 8, no. 4, 2015,pp 2286-2306.
[9] J. Wang, G. Yang, Y. Sun, and S. Chen, “Sybil attack detection based on rssi for wireless sensor network," in International Conference on Wireless Communications, Networking and Mobile Computing, pp. 2684- 2687, IEEE, 2007.
[10] N. Sastry, U. Shankar, and D. Wagner, “Secure verification of location claims," in Proceedings of the 2nd ACM workshop on Wireless security, pp. 1-10, ACM, 2003.
[11] U. S. R. K. Dhamodharan and R. Vayanaperumal, “Detecting and preventing sybil attacks in wire-less sensor networks using message authentication and passing method," The Scientific World Journal, vol. 2015, 2015.
[12] R. AMUTHAVALLI and R. BHUVANESWARAN, “Detection and prevention of sybil attack in wireless sensor network employing random password comparison method.," Journal of Theoretical & Applied Information Technology, vol. 67, no. 1, 2014.
[13] W. Wang, D. Pu, and A. Wyglinski, “Detecting sybil nodes in wireless networks with physical layer network coding," in 2010 IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), pp. 21-30, IEEE, 2010.
[14] W. Chang and J. Wu, “A survey of sybil attacks in networks," Temple University, Computer and Information Sciences. Philadelphia: Temple University.
[15] S. Hussain and M. S. Rahman, “Using received signal strength indicator to detect node replacement and replication attacks in wireless sensor networks," in SPIE Defense, Security, and Sensing, pp. 73440G- 73440G, International Society for Optics and Photonics, 2009.
[16] S. Marian and P. Mircea, “Sybil attack type detection in wireless sensor networks based on received signal strength indicator detection scheme," in Applied Computational Intelligence and Informatics (SACI), 2015 IEEE 10th Jubilee International Symposium on, pp. 121-124, IEEE, 2015.
[17] M. Wen, H. Li, Y.-F. Zheng, and K.-F. Chen, “Tdoa-based sybil attack detection scheme for wireless sensor networks," Journal of Shanghai University (English Edition), vol. 12, pp. 66-70, 2008.
[18] Y. Zeng, J. Cao, J. Hong, S. Zhang, and L. Xie, “Secure localization and location verification in wireless sensor networks: a survey," the Journal of Supercomputing, vol. 64, no. 3, pp. 685-701, 2013.
[19] Y. Wei and Y. Guan, “Lightweight location verification algorithms for wireless sensor networks," IEEE Transactions on Parallel and Distributed Systems, vol. 24, no. 5, pp. 938-950, 2013.
[20] D. Mukhopadhyay and I. Saha, “Location veri cation based defense against sybil attack in sensor net-works," in Distributed Computing and Networking, pp. 509-521, Springer, 2006.
[21] H. Shen and X.-G. Ye, “Research on the location attack based on multiple counterfeit identities tech-nology in sensor networks," in 2014 International Conference on Wireless Communication and Sensor Network (WCSN), pp. 193-197, IEEE, 2014.
[22] G. Mao, B. Fidan, and B. D. Anderson, “Wireless sensor network localization techniques," Computer networks, vol. 51, no. 10, pp. 2529-2553, 2007.
[23] G. V. Crosby, L. Hester, and N. Pissinou, “Location-aware, trust-based detection and isolation of com-promised nodes in wireless sensor networks.," IJ Network Security, vol. 12, no. 2, pp. 107-117, 2011.
[24] K.-F. Ssu, W.-T. Wang, and W.-C. Chang, “Detecting sybil attacks in wireless sensor networks using neighboring information," Computer Networks, vol. 53, no. 18, pp. 3042-3056, 2009.
[25] R. Rafeh and M. Khodadadi, “Detecting sybil nodes in wireless sensor networks using two-hop messages," Indian Journal of Science and Technology, vol. 7, no. 9, pp. 1359-1368, 2014.
[26] J.-W. Ho, “Sequential hypothesis testing based approach for replica cluster detection in wireless sensor networks," Journal of Sensor and Actuator Networks, vol. 1, no. 2, pp. 153-165, 2012.
[27] M. Li, Y. Xiong, X. Wu, X. Zhou, Y. Sun, S. Chen, and X. Zhu, “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), pp. 285-291, IEEE, 2013.
[28] G. U. S Sharmila, “Energy and hop based detection of sybil attack for mobile wireless sensor networks," International Journal of Emerging Technology and Advanced Engineering, vol. 4, no. 4, 2014.
[29] S. Golestani Najafabadi, H. R. Naji, and A. Mahani, “Sybil attack detection: Improving security of wsns for smart power grid application," in Smart Grid Conference (SGC), 2013, pp. 273-278, IEEE, 2013.
[30] Y. Liu, D. Bild, R. Dick, Z. M. Mao, and D. Wallach, “The mason test: A defense against sybil attacks in wireless networks without trusted authorities," Indian Journal of Science and Technology, 2014.
[31] J. Newsome, E. Shi, D. Song, and A. Perrig, “The sybil attack in sensor networks: analysis & defenses," in Proceedings of the 3rd international symposium on Information processing in sensor networks, pp. 259- 268, ACM, 2004.
[32] J. R. Douceur, “The sybil attack," in Peer-to-peer Systems, pp. 251-260, Springer, 2002.
[33] N. Abu-Ghazaleh, K.-D. Kang, and K. Liu, “Towards resilient geographic routing in wsns," in Proceedings of the 1st ACM international workshop on Quality of service & security in wireless and mobile networks, pp. 71-78, ACM, 2005.
[34] B. Tian, Y. Yao, L. Shi, S. Shao, Z. Liu, and C. Xu, “A novel sybil attack detection scheme for wire-less sensor network," in 2013 5th IEEE International Conference on Broadband Network & Multimedia Technology (IC-BNMT), pp. 294-297, IEEE, 2013.
[35] A. Vasudeva and M. Sood, “Sybil attack on lowest id clustering algorithm in the mobile ad hoc network," International Journal of Network Security & Its Applications (IJNSA), vol. 4, no. 5, 2012.
[36] M. A. B. Karuppiah and A. R. Prakash, “Sybilsecure: An energy efficient sybil attack detection technique in wireless sensor network," International Journal of Information, vol. 4, no. 3, 2014.
[37] A. Jsoang and R. Ismail, “The beta reputation system," in Proceedings of the 15th bled electronic commerce conference, vol. 5, pp. 2502-2511, 2002.
[38] A. Wald, Sequential analysis. Courier Corporation, 1973.
[39] I. Chang, and Y.-C, “Applications of Sequential Probability Ratio Test to computerized criterion-referenced testing”, Sequential Analysis, vol. 23, no. 1, pp. 45-61, 2004.
[40] K.Cohen, and Q.Zhao, “Quest Anomaly Detection: a case of active hypothesis testing”,IEEE Information Theory Applications workshop (ITA), pp 1-5, 2014.
[41] T.L.Lai, “Sequential analysis: some classical problems and new challenges”, Statist Sinica, Vol. 11, no. 2, pp. 303-350, 2001.
[42] Juliana, M. Roseline, and S. Srinivasan. "SELADG: Secure Energy Efficient Location Aware Data Gathering Approach for Wireless Sensor Networks", International Journal on Smart Sensing & Intelligent Systems, vol. 8, no.3, 2015, pp. 1748-1767
[43] Network simulator ns-2.35, http:// www.isi.edu/nsnam/ns. Accessed: 2015-11-10.
[44] Cc2420 data sheet. http://www.ti.com/product/cc2420. Accessed: 2015-11-10.
[45] Cc2431 data sheet. www.ti.com/cn/lit/gpn/cc2431. Accessed: 2015-11-10.

EXTRA FILES

COMMENTS