A Comparative Study on Security Attacks for Data Mining based Security Models in Wireless Sensor Networks

A wireless sensor network consists of geologically distributed autonomous sensors to monitor and control over physical or environmental conditions, like temperature, sound, pressure etc. and this information is passed through sensors in the network to a next location. Wireless sensor network is a trending technology now-a-days and has a wide range of applications such as battlefield surveillance, traffic surveillance, forest fire detection, flood detection etc. The many researchers have conducted different detection techniques and algorithms to proposed different types of detection schemes. This presents real challenges in the implementation of the following security requirements for WSNs. But wireless sensor networks are susceptible to a variety of potential attacks which obstructs the normal operation of the network. This paper discusses various literatures related to the black hole attack detection and prevention techniques. A Comparative study has been made along with further extension of the work.