A simple agent based model for detecting abnormal event patterns in distributed wireless sensor networks
Wireless Sensor networks (WSN) is a promising technology for current as well as future. There is vast use of WSN in different fields like military surveillance and target tracking, traffic management, weather forecasting, habitat monitoring, designing smart home, structural and seismic monitoring, etc. For success application of ubiquitous WSN it is important to maintain the basic security, both from external and internal attacks else entire network may collapse. Maintaining security in WSN network is not a simple job just like securing wireless networks because sensor nodes are deployed in randomize manner. Hence major challenges in WSNs are security. In this paper we have discussed different attacks in WSN and how these attacks were efficiently detected by using our agent based model. Our model identifies the abnormal event pattern sensor nodes in a largely deployed distributed sensor network under a common anomaly detection framework which will design by agent based learning and distributed data mining technique.