Modeling Attack Distribution in Sensor Networks

Attack is the major and unique security issues in sensor networks. There are many security approaches that can be used to detect attacks, yet few researches were focused on modeling these attacks' distribution. Knowing the distribution models of attacks can help us detect and defend against them efficiently and effectively. In this paper, we use probability theory to develop basic uniform model, basic gradient model of attack distribution based on the observations of different application environments. These models allow system to estimate the probability of a node to be attacked. To explain how important of these models and how to apply them in security design, we introduced some applications that can be improved using our models such as detecting attacks and secure routing.