Evaluation of Range-Free Localization Algorithms Against Node Compromise Attack

Abstract

 Different range-free algorithms are proposed for location estimation in Wireless Sensor Networks. In these algorithms, the network is assumed to have no error and false data. This article attempts to evaluate and compare the effect of malicious data produced by node compromised attacks in some of the range-free algorithms: DV-hop, LSVM, and NN. The false data may be produced by the malicious anchor nodes or compromised sensor nodes. The resistance of these algorithms against node compromise attacks is compared. The results show that although DV-hop has less localization error compared to the two other algorithms in a normal condition, in the case of attacks LSVM has less localization error. Further, in this research work, a new criterion is proposed for studying and comparing the border problem issue in the localization algorithms. Using the simulation results from various algorithms, the outcomes have been used for comparison, where it can be considered that LSVM has better performance in the border problem compared with the other studied algorithms.

Keywords

• Localization,Wireless Sensor Networks,Range-free,Node compromise attack,border problem

References

1. [1] C. Y. Chong, S. Kumar, Sensor networks: Evolution, opportunities, and challenges. Proceedings ofthe IEEE, 91(8), (2003), 1247-1256.
2. [2] C. Savarese, J. Rabay, Robust Positioning Algorithms for Distributed Ad-Hoc Wireless SensorNetworks, General Track of the annual conference on USENIX Annual Technical Conference, (2002),317-327.
3. [3] A. Savvides, C. C. Han, M. Srivastava, Dynamic Fine-Grained Localization in Ad-Hoc Networks ofSensors, 7th annual international conference on Mobile computing and networking, (2001), 166-179.
4. [4] D. Niculescu, B. Nath, Ad Hoc Positioning System (APS), Global Telecommunications Conference,(2001), 2926-2931.
5. [5] S. Capkun, M. Cagalj, M. Srivastava, Securing Localization with Hidden and Mobile Base Stations,25th IEEE Conference on Computer Communications, (2006), 1-10.
6. [6] S. Capkun, K. Rasmussen, M. Cagalj, M. Srivastava, Secure Location Verification with Hidden andMobile Base Stations, IEEE Transactions on Mobile Computing, 7(4), (2008), 470-483.
7. [7] T. He, C. Huang, B. M. Blum, J. A. Stankovic, T. Abdelzaher, Range-Free Localization Schemesfor Large Scale Sensor Networks, 9th Annual International Conference on Mobile Computing andNetworking, (2003), 81-95.
8. [8] L. Lazos, R. Poovendran, SeRLoc: Secure Range-Independent Localization for Wireless SensorNetworks, 3rd ACM workshop on Wireless security, (2004), 21-30.

9. [9] Z. Li, W. Trappe, Y. Zhang, B. Nath, Robust Statistical Methods for Securing Wireless Localizationin Sensor Networks, 4th international symposium on Information processing in sensor networks,(2005), 1-8.
10. [10] Y. Zhang, W. Liu, Y. Fang, D. Wu, Secure Localization and Authentication in Ultra-WidebandSensor Networks, IEEE Journal on Selected Areas in Communications, 24(4), (2006), 829-835.
11. [11] Y. Zhang, W. Liu, W. Lou, Y. Fang, Location-Based Compromise-Tolerant Security Mechanismsfor Wireless Sensor Networks, IEEE Journal on Selected Areas in Communications, 24(2), (2006), 247-260.
12. [12] R. Garg, A. Varna, M. Wu, An Efficient Gradient Descent Approach to Secure Localization inResource Constrained Wireless Sensor Networks, IEEE Transactions on Information Forensics andSecurity, 7(2), (2012), 717-730.
13. [13] Y. Zeng, J. Cao, J. Hong, S. Zhang, L. Xie, Secure Localization and Location Verification inWireless Sensor Networks: A Survey, The Journal of Supercomputing, 64(3), (2010), 685-701.
14. [14] G. Han, J. Jiang, L. Shu, M. Guizani, S. Nishio, A Two-Step Secure Localization for WirelessSensor Networks, The Computer Journal, 56(10), (2012), 1154-1166.
15. [15] H. Chen, W. Lou, Z. Wang, J. Wu, Z. Wang, A. Xia, Securing DV-Hop Localization AgainstWormhole Attacks in Wireless Sensor Networks, Pervasive and Mobile Computing, 16(1), (2015), 22-35.
16. [16] D. Tran, T. Nguyen, Localization in Wireless Sensor Networks Based on Support VectorMachines, IEEE Transactions on Parallel and Distributed Systems, 19(7), (2008), 981-994.
17. [17] A. Chatterjee, A Fletcher-Reeves Conjugate Gradient Neural-Network-Based LocalizationAlgorithm for Wireless Sensor Networks, IEEE Transactions on Vehicular Technology, 59(2), (2010),823-830.
18. [18] C. Wang, J. Chen, Y. Sun, Sensor Network Localization Using Kernel Spectral Regression,Wireless Communications and Mobile Computing, 10(8), (2009), 1045-1054.
19. [19] V. Chaurasiya, N. Jain, G. Nandi, A Novel Distance Estimation Approach for 3D Localization inWireless Sensor Network Using Multi Dimensional Scaling, Information Fusion, 15(1), (2014), 5-18.
20. [20] S. Afzal, H. Beigy, A Localization Algorithm for Large Scale Mobile Wireless Sensor Networks:A Learning Approach, The Journal of Supercomputing, 69(1), (2014), 98-120.
21. [21] J. Chen, C. Wang, Y. Sun, X. Shen, Semi-supervised Laplacian Regularized Least SquaresAlgorithm for Localization in Wireless Sensor Networks, Computer Networks, 55(10), (2011), 2481-2491.
22. [22] J. Lee, B. Choi, E. Kim, Novel Range-Free Localization Based on Multidimensional SupportVector Regression Trained in the Primal Space, IEEE Transactions on Neural Networks and LearningSystems, 24(7), (2013), 1099-1113.
23. [23] V. S. Feng, T. C. Wang, S. Y. Chang, H. P. Ma, Location Estimation in Indoor Wireless Networksby Hierarchical Support Vector Machines with Fast Learning Algorithm, International Conference onSystem Science and Engineering, (2010), 321-326.
24. [24] S. Yun, J. Lee, W. Chung, E. Kim, S. Kim, A Soft Computing Approach to Localization inWireless Sensor Networks, Expert Systems with Applications, 36(4), (2009), 7552-7561.
25. [25] A. Velimirovic, G. Djordjevic, M. Velimirovic, M. Jovanovic, Fuzzy Ring-Overlapping RangeFree(FRORF) Localization Method for Wireless Sensor Networks, Computer Communications, 35(13),(2012), 1590-1600.
26. [26] A. Boukerche, H. Oliveira, E. Nakamura , A. Loureiro, Secure Localization Algorithms forWireless Sensor Networks, IEEE Communications Magazine, 46(4), (2008), 96-101.
27. [27] M. M. Hamed, M.G Khalafallah, E.A. Hassanien, Prediction of Wastewater Treatment PlantPerformance using Artificial Neural Networks, Environmental Modelling & Software, 19(10), (2004),919-928.
28. [28] W. S. Sarle, Neural Network FAQ, Part 1 of 7: Introduction, Periodic Posting to the UsenetNewsgroup Comp. Ai. Neural-Nets. (2002), URL: ftp://ftp.sas.com/pub/neural/FAQ.html.