Secure Tracking in Sensor Networks Using Adaptive Extended Kalman Filter
Location information of sensor nodes has become an essential part of many applications in Wireless Sensor Networks (WSN). The importance of location estimation and object tracking has made them the target of many security attacks. Various methods have tried to provide location information with high accuracy, while lots of them have neglected the fact that WSNs may be deployed in hostile environments. In this paper, the authors address the problem of securely tracking a Mobile Node (MN) which has been noticed very little previously. A novel secure tracking algorithm is proposed based on Extended Kalman Filter (EKF) that is capable of tracking a Mobile Node (MN) with high resolution in the presence of compromised or colluding malicious beacon nodes.