Detection performance improvement using risk assessment framework

The border region monitoring task can be achieved using surveillance wireless sensor networks. The network detects trespassers and inform the sink node. There are many mobility models proposed for users within an ad hoc network. On the other hand, the behavior of trespassers are generally different than mobile users and does not follow a random pattern. Observations from previous security related studies are used to form a realistic model representing a border region. The performance of a surveillance network depends on its risk prediction capabilities and detection ratio. A risk assessment framework is proposed to be used for the performance evaluation. The framework quantizes the security risk value of each point within the monitored zone. The performance metric takes environmental parameters such as sensor coverage, miss probability and breach frequency into consideration and gives a normalized risk value for a given point. The metric can be customized for different types of networks and scenarios easily. The framework is used for forecasting probable threat points in order to take the necessary counter measures. In this paper, additional sensor deployment is proposed as a such measure and the improvement in detection performance using different deployment schemes is measured. It is shown that the additional deployment done using risk assessment framework gives better detection improvement.