Document Type : Research Article

Authors

1 University of Applied Science and Technology, Tehran, Iran

2 Department of Computer Engineering, Iran University of Science & Technology Tehran, Iran

3 Department of Computer Engineering, Iran University of Science and Technology Tehran, Iran

Abstract

Wireless Sensor Networks (WSNs) offer inherent packet redundancy since each point within the network area is covered by more than one sensor node. This phenomenon, which is known as sensors co-coverage, is used in this paper to detect unauthenticated events. Unauthenticated event broadcasting in a WSN imposes network congestion, worsens the packet loss rate, and increases the network energy congestion. In the proposed method, the more the safe, the less the unsafe (MSLU) method, each secure occurred event must be confirmed by various sensor nodes; otherwise the event is dropped. Indeed, the proposed method tends to forward event occurrence reports that are detected by various sensor nodes. The proposed method is evaluated by means of simulation as well as analytical modeling. A wide range of simulations, which are carried out using NS-2, show that the proposed method detects more than 85% of unauthenticated events. This comes at the cost of the network end-to-end delay of 20% because the proposed method does not impose delay on incoming packets. In addition, the proposed method is evaluated by means of an analytical model based on queuing networks. The model accurately estimates the network performance utilizing the proposed unauthenticated event detection method.

Keywords

[1] J. Feng, Z. Wang, and J. Henkel, "An Adaptive Data Gathering Strategy for Target Tracking in Cluster-based Wireless Sensor Networks," in IEEE Symposium on Computers and Communications (ISCC), Cappadocia, 2012, pp. 468-474.
[2] S. Bhattacharjee, P. Roy, S. Ghosh, S. Misra, and M. S. Obaidat, "Wireless sensor network-based fire detection, alarming, monitoring and prevention system for Bord-and-Pillar coal mines," The Journal of Systems and Software, vol. 85, pp. 571-581, 2012.
[3] M. J. Chae, H. S. Yoo, J. Y. Kim, and M. Y. Cho, "Development of a wireless sensor network system for suspension bridge health monitoring," Automation in Construction, vol. 21, p. 237–252, 2012.
[4] M. Kamarei, M. Hajimohammadi, A. Patooghy, and M. Fazeli, "An Efficient Data Aggregation Method for Event-Driven WSNs: A Modeling & Evaluation Approach," Wireless Personal Communications an International Journal, vol. 84, no. 1, pp. 745-764, 2015.
[5] J. H. Ho, H. C. Shih, Y. B. Liao, and S. C. Chu, "A ladder diffusion algorithm using ant colony optimization for wireless sensor networks," Information Sciences, vol. 192, no. 1, p. 204–212, 2011.
[6] M. E. Keskin, I. K. Altınel, N. Aras, and C. Ersoy, "Wireless sensor network lifetime maximization by optimal sensor deployment, activity scheduling, data routing and sink mobility," Ad Hoc Networks, vol. 17, p. 18–36, 2014.
[7] S. Cheng and T. Y. Chang, "An adaptive learning scheme for load balancing with zone partition in multi-sink wireless sensor network," Expert Systems with Applications, vol. 39, p. 9427–9434, 2012.
[8] P. Thao and C. H. Tae, "A multi-path interleaved hop-by-hop en-route filtering scheme in wireless sensor networks," Computer Communications, vol. 33, p. 1202–1209, 2010.
[9] R. S. Sachan, M. Wazid, A. Katal, D. P. Singh, and R. H. Goudar, "A Cluster Based Intrusion Detection and Prevention Technique for Misdirection Attack inside WSN," in International conference on Communication and Signal Processing, India, 2013, pp. 795-801.
[10] J. Wang, Z. Liu, S. Zhang, and X. Zhang, "Defending collaborative false data injection attacks in wireless sensor networks," Information Sciences, vol. 254, p. 39–53, 2014.
[11] S. V. Annlin Jeba and B. Paramasivan, "Energy efficient multipath data transfer scheme to mitigate false data injection attack in wireless sensor networks," Computers and Electrical Engineering, vol. 39, p. 1867–1879, 2013.
[12] D. R. Raymond, R. C. Marchany, M. I. Brownfield, and S. F. Midkiff, "Effects of Denial-of-Sleep Attacks on Wireless Sensor Network MAC Protocols," IEEE Transactions on Vehicular Technology, vol. 58, no. 1, pp. 367-380, 2009.
[13] P. M. Pawar, R. H. Nielsen, N. R. Prasad, S. Ohmori, and R. Prasad, "Behavioral Modeling of WSN MAC Layer Security Attacks: A Sequential UML Approach," Journal of Cyber Security and Mobility, vol. 1, no. 1, pp. 65-82, 2012.
[14] M. Kamarei, A. Patooghy, M. Fazeli, and M. J. Salehi, "AT2A: Defending Unauthenticated Broadcast Attacks in Mobile Wireless Sensor Networks," International Journal of Electronics Communication and Computer Engineering, vol. 5, no. 5, pp. 1216-1221, 2014.
[15] A. Patooghy, M. Kamarei, A. Farajzadeh, F. Tavakoli, and M. Saeidmanesh, "Load-Balancing Enhancement by a Mobile Data Collector in Wireless Sensor Networks," in Eighth International Conference on Sensing Technology, Liverpool, UK, 2014, pp. 634-638.
[16] P. Reindl, K. Nygard, and X. Du, "Defending malicious collision attacks in wireless sensor networks," in 8th International Conference on Embedded and Ubiquitous Computing (EUC), Hong Kong, 2010, pp. 771-776.
[17] W. Yee, et al., "Energy-efficient link-layer jamming attacks against wireless sensor network MAC protocols," ACM Transactions on Sensor Networks (TOSN), vol. 5, no. 1, pp. 1-6, 2009.
[18] S. Zhu, S. Setia, and S. Jajodia, "An interleaved hop-by-hop authentication scheme for filtering of injected false data in sensor networks," in Proceeding IEEE symposium on Security and privacy, 2004, p. 259–271.
[19] F. Ye, H. Luo, and L. Zhang, "Statistical en-route filtering of injected false data in sensor networks," in Proceedings of 23th Annual Joint Conference of the IEEE Computer and Communications Societies, 2004, p. 2446–2457.
[20] A. S. Uluagac, R. A. Beyah, L. Yingshu , and J. A. Copeland, "VEBEK: Virtual Energy-Based Encryption and Keying for Wireless Sensor Networks," IEEE Transactions on Mobile Computing, vol. 9, no. 7, pp. 994-1007, 2010.
[21] Q. Ren and Q. Liang, "Secure media access control (MAC) in wireless sensor networks: intrusion detections and countermeasures," in 15th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 2004, pp. 3025-3029.
[22] M. V. Ramesh, A. B. Raj, and T. Hemalatha, "Wireless Sensor Network Security: Real-Time Detection and Prevention of Attacks," in Fourth International Conference on Computational Intelligence and Communication Networks, Mathura, 2012, pp. 783-787.
[23] Y. Zhen and G. Yong, "A dynamic en-route filtering scheme for data reporting in wireless sensor networks," IEEE Trans Network, vol. 18, no. 1, pp. 150-163, 2010.
[24] N. Bandirmali and I. Erturk, "WSNSec: A scalable data link layer security protocol for WSNs," Ad Hoc Networks, vol. 10, pp. 37-45, 2012.
[25] J. Zhu and S. Papavassiliou, "On the Connectivity Modeling and the Tradeoffs between Reliability and Energy Efficiency in Large Scale Wireless Sensor Networks," in IEEE Wireless Communications and Networking, WCNC, New Orleans, LA, USA, 2003, pp. 1260-1265.
[26] M. Kamarei, M. Hajimohammadi, A. Patooghy, and M. Fazeli, "OLDA: An Efficient On-Line Data Aggregation Method for Wireless Sensor Networks," in Eighth International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA 2013), Compiegne, France, 2013, pp. 49-53.
[27] M. Kamarei, A. H. Nasrollah Barati, A. Patooghy, and M. Fazeli, "The More the Safe, the Less the Unsafe: An efficient method to unauthenticated packets detection in WSNs," in 7th Conference on Information and Knowledge Technology (IKT), Urmia, Iran, 2015, pp. 1-6.