Abstract

Wireless Sensor Networks (WSNs) are emerging as a promising technology because of their wide range of applications in industrial, environmental monitoring, military and civilian domains. Due to economic considerations, the nodes are usually simple and low cost. They are often unattended, however, and are hence likely to suffer from different types of novel attack. WSNs are increasingly being deployed in security-critical applications. Due to their inherent resource constrained characteristics, they are prone to various security attacks, and a black hole attack is a type of attack that seriously affects data collection. In this paper, using the recent advances in uncertain reasoning that has originated from the artificial intelligence community, we propose a trust management scheme named Hybrid and Efficient Intrusion Detection Systems that enhances the security in networks. Here, we have used two frameworks for Trust Calculation and Decision-Making process. The trust value is derived using Bayesian Inference, and Decision Making is based on Dempster Shafer theory, which is a mathematical theory of evidence.