Anomaly Detection and Mitigation for Disaster Area Networks
One of the most challenging applications of wireless networking are in disaster area networks where lack of infrastructure, limited energy resources, need for common operational picture and thereby reliable dissemination are prevalent. In this paper we address anomaly detection in intermittently connected mobile ad hoc networks in which there is little or no knowledge about the actors on the scene, and opportunistic contacts together with a store-and-forward mechanism are used to overcome temporary partitions. The approach uses a statistical method for detecting anomalies when running a manycast protocol for dissemination of important messages to k receivers. Simulation of the random walk gossip (RWG) protocol combined with detection and mitigation mechanisms is used to illustrate that resilience can be built into a network in a fully distributed and attack-agnostic manner, at a modest cost in terms of drop in delivery ratio and additional transmissions. The approach is evaluated with attacks by adversaries that behave in a similar manner to fair nodes when invoking protocol actions.
KeywordsIntrusion Detection Delivery Ratio Anomaly Detection Disaster Area Optimise Link State Routing
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- 2.Steckler, B., Bradford, B.L., Urrea, S.: Hastily formed networks for complex humanitarian disasters after action report and lessons learned from the naval postgraduate school’s response to hurricane katrina. Technical Report, Naval Postgraduate School (2005)Google Scholar
- 3.Asplund, M., Nadjm-Tehrani, S.: A partition-tolerant manycast algorithm for disaster area networks. In: IEEE Symposium on Reliable Distributed Systems, pp. 156–165 (2009)Google Scholar
- 14.Scalavino, E., Russello, G., Ball, R., Gowadia, V., Lupu, E.C.: An opportunistic authority evaluation scheme for data security in crisis management scenarios. In: ASIACCS 2010: Proceedings of the 5th ACM Symposium on Information, Computer and Communications Security, pp. 157–168. ACM, New York (2010)CrossRefGoogle Scholar
- 15.Thamilarasu, G., Balasubramanian, A., Mishra, S., Sridhar, R.: A cross-layer based intrusion detection approach for wireless ad hoc networks. In: IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, pp. 854–861. IEEE, Los Alamitos (2005)Google Scholar
- 16.Sun, B., Wu, K., Pooch, U.W.: Zone-based intrusion detection for ad hoc networks. International Journal of Ad Hoc & Sensor Wireless Networks. Old City Publishing (2004)Google Scholar
- 19.Deodhar, A., Gujarathi, R.: A cluster based intrusion detection system for mobile ad hoc networks. Technical Report, Virginia Polytechnic Institute & State UniversityGoogle Scholar
- 21.Moore, D.S., Cabe, G.P.M.: Introduction to the practice of statistics, 5th edn. W. H. Freeman, New York (2005)Google Scholar