ABSTRACT
Wireless Sensor Networks (WSNs) can be used to monitor otherwise difficult-to-reach environments due to the physical characteristics of the nodes and their ability to transmit data from a distance. However, they also bear the disadvantages of small life cycle, low data reliability and malicious intervention. A solution to this problem can be the incorporation of dedicated software in the operating system capable to monitor specifc parameters of the node and inform the sink when something is wrong with the operation of the node. In this work we propose a lightweight run time monitoring tool, called Run-time Monitoring Tool (RMT), developed for operation in Contiki O/S. This tool can be customized to monitor parameters of interest and execute instructions at runtime. A multilayer, multiprotocol approach is taken in RMT, with the ability to monitor two Contiki O/S layers, have detailed node power consumption and observe the operation of a routing protocol. Our evaluation shows that RMT guarantees minimum overhead and low energy consumption.
- I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci. A survey on sensor networks. Comm. Mag., Aug. 2002. Google ScholarDigital Library
- N. Alrajei, H. Fu, and Y. Zhu. Information theory based intrusion detection in wireless sensor networks. Journal of Communications Technology, Electronics and Computer Science, 2016.Google Scholar
- N. Aschenbruck, J. Bauer, J. Bieling, A. Bothe, and M. Schwamborn. A security architecture and modular intrusion detection system for wsns. In Networked Sensing Systems (INSS), 2012 Ninth International Conference on, June 2012.Google ScholarCross Ref
- V. Bhuse, A. Gupta, and A. Al-Fuqaha. Detection of masquerade attacks on wireless sensor networks. In Communications, 2007. ICC '07. IEEE International Conference on, June 2007.Google ScholarCross Ref
- A. P. R. da Silva, M. H. T. Martins, B. P. S. Rocha, A. A. F. Loureiro, L. B. Ruiz, and H. C. Wong. Decentralized intrusion detection in wireless sensor networks. In Proceedings of the 1st ACM International Workshop on Quality of Service & Security in Wireless and Mobile Networks (Q2SWinet '05), New York, NY, USA, 2005. ACM. Google ScholarDigital Library
- A. Dunkels, J. Eriksson, N. Finne, and N. Tsiftes. Powertrace: Network-level power profiling for low-power wireless networks. Technical report, Swedish Institute of Computer Science, 2011.Google Scholar
- J. Ko, C. Lu, M. B. Srivastava, J. A. Stankovic, A. Terzis, and M. Welsh. Wireless sensor networks for healthcare. Proceedings of the IEEE, 2010.Google ScholarCross Ref
- F. Liu, X. Cheng, and D. Chen. Insider attacker detection in wireless sensor networks. In INFOCOM 2007. 26th IEEE International Conference on Computer Communications. IEEE, May 2007. Google ScholarDigital Library
- Y. Liu and F. Yu. Immunity-based intrusion detection for wireless sensor networks. In Neural Networks, 2008. IJCNN 2008. IEEE International Joint Conference on, June 2008.Google Scholar
- Moteiv Corporation. Tmote Sky Ultra Low Power IEEE 802.15.4 compliant wireless sensor module, 6 2006.Google Scholar
- R. Muraleedharan and L. Osadciw. Security: Cross layer protocol in wireless sensor network. In INFOCOM 2006. 25th IEEE International Conference on Computer Communications. Proceedings, April 2006.Google ScholarCross Ref
- T. O'donovan, J. Brown, F. Büsching, A. Cardoso, J. Cecílio, P. Furtado, P. Gil, A. Jugel, W.-B. Pöttner, U. Roedig, et al. The ginseng system for wireless monitoring and control: Design and deployment experiences. ACM Transactions on Sensor Networks (TOSN), 2013. Google ScholarDigital Library
- I. Onat and A. Miri. An intrusion detection system for wireless sensor networks. In Wireless And Mobile Computing, Networking And Communications, 2005. (WiMob'2005), IEEE International Conference on, Aug 2005.Google Scholar
- M. R. Palattella, N. Accettura, X. Vilajosana, T. Watteyne, L. A. Grieco, G. Boggia, and M. Dohler. Standardized protocol stack for the internet of (important) things. IEEE Communications Surveys Tutorials, Third 2013.Google Scholar
- P. Pongle and G. Chavan. Real time intrusion and wormhole attack detection in internet of things. International Journal of Computer Applications, 2015.Google Scholar
- S. Raza, L. Wallgren, and T. Voigt. Svelte: Real-time intrusion detection in the internet of things. Ad hoc networks, 2013. Google ScholarDigital Library
- G. Werner-Allen, K. Lorincz, M. Welsh, O. Marcillo, J. Johnson, M. Ruiz, and J. Lees. Deploying a wireless sensor network on an active volcano. IEEE Internet Computing, Mar. 2006. Google ScholarDigital Library
Index Terms
- RMT: A Wireless Sensor Network Monitoring Tool
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