Vol. 22 No. Special Issue 2 (2023): Mapana-Journal of Sciences
Research Articles

A Survey on Spoofing and Selective Forwarding Attacks on Zigbee based WSN

PDF
  • Nethra Pingala Suthishni D,
  • D. Shanmugapriya
Nethra Pingala Suthishni D
Avinashilingam Institute for Home Science and Higher Education for Women
D. Shanmugapriya
Avinashilingam Institute for Home Science and Higher Education for Women
DOI: https://doi.org/10.12723/mjs.sp2.23

Published 2023-12-27

Keywords

  • Zigbee,
  • WSN,
  • Protocol Stack,
  • Spoofing,
  • Selective Forwarding

Copyright (c) 2023

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Abstract

The main focus of WSN is to gather data from the physical world. It is often deployed for sensing, processing as well as disseminating information of the targeted physical environments. The main objective of the WSN is to collect data from the target environment using sensors as well as transmit those data to the desired place of choice. In order to achieve an efficient performance, WSN should have efficient as well as reliable networking protocols. The most popular technology behind WSN is Zigbee. In this paper a pilot study is done on important security issues on spoofing and selective forwarding attack on Zigbee based WSN. This paper identifies the security vulnerabilities of Zigbee network and gaps in the existing methodologies to address the security issues and will help the future researchers to narrow down their research in WSN.
Keywords: Zigbee, WSN, Protocol Stack, Spoofing and Selective Forwarding.

PDF

References

  1. . A. D. Wood and J. A. Stankovic, "Denial of service in sensor networks," in Computer, vol. 35, no. 10, pp. 54-62, Oct. 2002, doi: 10.1109/MC.2002.1039518
  2. . C. Karlof and D. Wagner, “Secure routing in wireless sensor networks: attacks and countermeasures,” in Ad Hoc Networks, Vol. 1, No. 2, 2003, pp. 293-315. https://doi.org/10.1016/S1570-8705(03)00008-8
  3. . Bo Yu and Bin Xiao, "Detecting selective forwarding attacks in wireless sensor networks," Proceedings 20th IEEE International Parallel & Distributed Processing Symposium, 2006, pp. 8 pp.-, doi: 10.1109/IPDPS.2006.1639675.
  4. . B. Yu and B. Xiao, “CHEMAS: identify suspect nodes in selective forwarding attacks,” in Journal of Parallel and Distributed Computing, Vol. 67, No. 11, 2007, pp. 1218-1230. https://doi.org/10.1016/j.jpdc.2007.04.014
  5. . S. Kaplantzis, A. Shilton, N. Mani and Y. A. Sekercioglu, "Detecting Selective Forwarding Attacks in Wireless Sensor Networks using Support Vector Machines," 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information, 2007, pp. 335-340, doi: 10.1109/ISSNIP.2007.4496866.
  6. . Hung-Min Sun, Chien-Ming Chen and Ying-Chu Hsiao, "An efficient countermeasure to the selective forwarding attack in wireless sensor networks," TENCON 2007 - 2007 IEEE Region 10 Conference, 2007, pp. 1-4, doi: 10.1109/TENCON.2007.4428866.
  7. . K. Ioannis and T. Dimitriou, “Toward intrusion detection in sensor networks,” in 13th European Wireless Conference, April 2007, pp.1-7. doi: 10.1119/ISSNIP.2007.55431.
  8. . Hae Young L, Tae Ho C. Fuzzy-based reliable data delivery for countering selective forwarding in sensor networks. Hong Kong, China, Springer-Verlag, 2007, p. 535-544. https://doi.org/10.1007/978-3-540-73549-6_53
  9. . T. H. Hai and E. -N. Huh, "Detecting Selective Forwarding Attacks in Wireless Sensor Networks Using Two-hops Neighbor Knowledge," 2008 Seventh IEEE International Symposium on Network Computing and Applications, 2008, pp. 325-331, doi: 10.1109/NCA.2008.13.
  10. . Y. K. Kim, H. Lee, K. Cho and D. H. Lee, "CADE: Cumulative Acknowledgement Based Detection of Selective Forwarding Attacks in Wireless Sensor Networks," 2008 Third International Conference on Convergence and Hybrid Information Technology, 2008, pp. 416-422, doi: 10.1109/ICCIT.2008.271.
  11. . J. Brown and X. Du, "Detection of Selective Forwarding Attacks in Heterogeneous Sensor Networks," 2008 IEEE International Conference on Communications, 2008, pp. 1583-1587, doi: 10.1109/ICC.2008.306.
  12. . Padmavathi DG, Shanmugapriya M. A survey of attacks,
  13. security mechanisms and challenges in wireless sensor
  14. networks. arXiv preprint arXiv:0909.0576. 2009 Sep 3.
  15. https://doi.org/10.48550/arXiv.0909.0576
  16. . H. Deng, X. Sun, B. Wang and Y. Cao, "Selective forwarding
  17. attack detection using watermark in WSNs," 2009 ISECS
  18. International Colloquium on Computing, Communication,
  19. Control, and Management, 2009, pp. 109-113, doi:
  20. 1109/CCCM.2009.5268016
  21. . X. Lei, X. Yong-jun, P. Yong and Z. Yue-fei, "A Polynomial-
  22. Based Countermeasure to Selective Forwarding Attacks in
  23. Sensor Networks," 2009 WRI International Conference on
  24. Communications and Mobile Computing, 2009, pp. 455-459,
  25. doi: 10.1109/CMC.2009.230
  26. . C. Tumrongwittayapak and R. Varakulsiripunth, "Detecting
  27. sinkhole attack and selective forwarding attack in wireless
  28. sensor networks," 2009 7th International Conference on
  29. Information, Communications and Signal Processing (ICICS),
  30. , pp. 1-5, doi: 10.1109/ICICS.2009.5397594.
  31. . W. Xin-sheng, Z. Yong-zhao, X. Shu-ming and W. Liang-min,
  32. "Lightweight defense scheme against selective forwarding
  33. attacks in wireless sensor networks," 2009 International
  34. Conference on Cyber-Enabled Distributed Computing and
  35. Knowledge Discovery, 2009, pp. 226-232, doi:
  36. 1109/CYBERC.2009.5342206.
  37. . Y. B. Reddy and S. Srivathsan, "Game theory model for
  38. selective forward attacks in wireless sensor networks," 2009
  39. th Mediterranean Conference on Control and Automation,
  40. , pp. 458-463, doi: 10.1109/MED.2009.5164584.
  41. . G. Li, X. Liu and C. Wang, "A sequential mesh test based
  42. selective forwarding attack detection scheme in wireless
  43. sensor networks," 2010 International Conference on
  44. Networking, Sensing and Control (ICNSC), 2010, pp. 554-558,
  45. doi: 10.1109/ICNSC.2010.5461599.
  46. . S.-B. Lee and Y.-H. Choi, A Resilient Packet-Forwarding
  47. Scheme against Maliciously Packet-Dropping Nodes in
  48. Sensor Networks, In Proceedings of the Fourth ACM
  49. Workshop on Security of Ad Hoc and Sensor
  50. Networks (SASN‟06), pp. 59-70, 2006. “
  51. https://doi.org/10.1145/1180345.1180353
  52. . S. Zhu, S. Setia, and S. Jajodia, LEAP: Efficient Security
  53. Mechanisms for Large-Scale Distributed Sensor Networks,
  54. The 10th ACM Conference on Computer and
  55. Communications Security (CCS ‟03), 62-72, 2003.
  56. https://doi.org/10.1145/1218556.1218559
  57. . S. Marti, T. J. Giuli, K. Lai, and M. Baker, “Mitigating routing
  58. misbehavior in mobile ad hoc networks,” in Proceedings of
  59. the 6th annual international conference on Mobile
  60. Computing and Networking (MobiCom ‟00), 2000, pp. 255–
  61. https://doi.org/10.1145/345910.345955
  62. . N. Nasser and Y. Chen, SEEM: Secure and energy efficient
  63. multipath routing protocol for wireless sensor networks,
  64. Computer Communications, Volume 30, Issue 11-12, pp.
  65. -2412, September 2007.
  66. https://doi.org/10.1016/j.comcom.2007.04.014
  67. . N. Ahmed, S. S. Kanhere, and S. Jha, “Intrusion Detection
  68. Techniques for Mobile Wireless Networks,” Mobile
  69. Computing and Communications Review, Vol. 9, No. 2, pp.
  70. , 2005.
  71. . X. Pu, Z. Yan, S. Mao, Y. Zhang and Y. Li, “The sequential
  72. mesh test for a proportion,” in Journal of East China Normal
  73. University, No. 1, 2006, pp. 63-71.
  74. https://xblk.ecnu.edu.cn/EN/Y2006/V2006/I1/63
  75. . L. Xiao et al., "PHY-Authentication Protocol for Spoofing
  76. Detection in Wireless Networks," 2010 IEEE Global
  77. Telecommunications Conference GLOBECOM 2010, 2010,
  78. pp. 1-6, doi: 10.1109/GLOCOM.2010.5683463.
  79. . F. A. Barbhuiya, S. Biswas and S. Nandi, "An active DES
  80. based IDS for ARP spoofing," 2011 IEEE International
  81. Conference on Systems, Man, and Cybernetics, 2011, pp.
  82. -2748, doi: 10.1109/ICSMC.2011.6084088.
  83. . Ferdous A Barbhuiya, Santosh Biswas and Sukumar Nandi,
  84. “An Active Host-based Intrusion detection system for ARP-
  85. related attacks and its verification”, IEEE Trans. International
  86. Journal of Network Security & Its Applications (IJNSA),
  87. Vol.3, No.3, May 2011.
  88. https://doi.org/10.5121/ijnsa.2011.3311
  89. . Wesam S. Bhaya and Samraa A. AlAsady, “Prevention of
  90. Spoofing Attacks in the Infrastructure Wireless Networks,”
  91. proc IEEE Journal of Computer Science 8 (10): Page(s): 1769-
  92. , 2012.
  93. . A. Broumandan, A. Jafarnia-Jahromi, V. Dehghanian, J.
  94. Nielsen and G. Lachapelle, "GNSS spoofing detection in
  95. handheld receivers based on signal spatial correlation,"
  96. Proceedings of the 2012 IEEE/ION Position, Location and
  97. Navigation Symposium, 2012, pp. 479-487, doi:
  98. 1109/PLANS.2012.6236917.
  99. . J. Yang, Y. Chen, W. Trappe and J. Cheng, "Detection and
  100. Localization of Multiple Spoofing Attackers in Wireless
  101. Networks," in IEEE Transactions on Parallel and Distributed
  102. Systems, vol. 24, no. 1, pp. 44-58, Jan. 2013, doi:
  103. 1109/TPDS.2012.104.
  104. . Q. Zeng, H. Li and L. Qian, "GPS spoofing attack on time
  105. synchronization in wireless networks and detection scheme
  106. design," MILCOM 2012 - 2012 IEEE Military
  107. Communications Conference, 2012, pp. 1-5, doi:
  108. 1109/MILCOM.2012.6415619.
  109. . Z. Zhang, M. Trinkle, L. Qian and H. Li, "Quickest detection
  110. of GPS spoofing attack," MILCOM 2012 - 2012 IEEE Military
  111. Communications Conference, 2012, pp. 1-6, doi:
  112. 1109/MILCOM.2012.6415722.
  113. . Hao Yang, Haiyun Luo, Yi Yang, Songwu Lu and Lixia
  114. Zhang, "HOURS: achieving DoS resilience in an open service
  115. hierarchy," International Conference on Dependable Systems
  116. and Networks, 2004, 2004, pp. 83-92, doi:
  117. 1109/DSN.2004.1311879.
  118. . Ahmed M.AbdelSalam ,Wail S.Elkilani and Khalid M.Amin,
  119. “An Automated approach for Preventing ARP Spoofing
  120. Attack using Static ARP Entries” Proc IEEE (IJACSA)
  121. International Journal of Advanced Computer Science and
  122. Applications, Vol. 5, No. 1, 2014. doi=10.1.1.676.4047
  123. . Y. Chen, W. Trappe and R. P. Martin, "Detecting and
  124. Localizing Wireless Spoofing Attacks," 2007 4th Annual IEEE
  125. Communications Society Conference on Sensor, Mesh and
  126. Ad Hoc Communications and Networks, 2007, pp. 193-202,
  127. doi: 10.1109/SAHCN.2007.4292831..
  128. . Archana Shelar and M.D.Ingale, ”Modeling Security with
  129. Localization of Multiple Spoofing Attackers in Wireless
  130. Network,” The International Journal Of Engineering And
  131. Science (IJES), Volume 3, Issue 01, Pages 01-06, 2014.
  132. DOI:10.1109/TPDS.2012.104
  133. . J. Yang, Y. Chen, W. Trappe and J. Cheng, "Detection and
  134. Localization of Multiple Spoofing Attackers in Wireless
  135. Networks," in IEEE Transactions on Parallel and Distributed
  136. Systems, vol. 24, no. 1, pp. 44-58, Jan. 2013, doi:
  137. 1109/TPDS.2012.104.
  138. . K. Salah, J. M. Alcaraz Calero, S. Zeadally, S. Al-Mulla and
  139. M. Alzaabi, "Using Cloud Computing to Implement a
  140. Security Overlay Network," in IEEE Security & Privacy, vol.
  141. , no. 1, pp. 44-53, Jan.-Feb. 2013, doi: 10.1109/MSP.2012.8
  142. . Patel, Anshuman, and Devesh Jinwala. "A reputation‐based
  143. RPL protocol to detect selective forwarding attack in Internet
  144. of Things." International Journal of Communication Systems
  145. 1 (2022): e5007.
  146. . Ezhilarasi, M., Gnanaprasanambikai, L., Kousalya, A. et al. A
  147. novel implementation of routing attack detection scheme by
  148. using fuzzy and feed-forward neural networks. Soft Comput
  149. (2022). https://doi.org/10.1007/s00500-022-06915-1.
  150. . Shafique, Arslan, Abid Mehmood, and Mourad Elhadef.
  151. "Detecting signal spoofing attack in uavs using machine
  152. learning models." IEEE Access 9 (2021): 93803-93815.