Study On Wireless Sensor Network Secure Tracking Algorithm

As one of the primary application proposals of wireless sensor network, target tracking has always been a hotspot in research with a lot of merits, such as convenience, cheapness, concealment and robustness. But the traditional tracking and security mechanisms can not be applied to Wireless Sensor Network directly due to many demerits caused by large scale and distributed architecture and limited capability of sensor nodes. These drawbacks restrict WSN's application, calling for the necessity of developing high security and accuracy tracking algorithms for large scale tracking WSN under the limitation of low energy support.Based on the distributed computing and security technology, secure target tracking algorithms are studied in this dissertation. And based on the study of security problems and tracking models of large scale WSN, the dissertation focuses on key distribution algorithms and dynamic cluster tracking algorithms. The research includes random predistribution key, distributed target tracking protocol, tracking cluster season key management protocol, range-free convex data fusion algorithm and distributed particle filter algorithm.Encryption and authentication of the tracking results are basic security mechanisms. A hashed random predistribution key protocol is proposed in that it combines the merits of basic random predistribution key, q composition, multi-path reinforcement and one way hash function and it can be used in net layer key distribution and management for large scale WSN. The analysis of it sheds light on the fact that this algorithm can effectively resist node capture attack. With the scalability, security and energy of WSN taken into account, this protocol can be applied to all kinds of large scale WSN.For target tracking application, a layered dynamic tracking cluster protocol is proposed to achieve distributed information driven cluster management and data fusion in application layer. Through organizing the sensor nodes around the target and forming a tracking cluster to follow the target, the protocol can accurately track fast moving objects, decrease communication loads and improve the network's reliability and service life at the same time. The cluster head can also fuse the member reports according to an improved convex fusion method. By this way, the WSN can accurately locate the target with cheap range-free sensors. Simulation result proves that this protocol can track fast moving objects with excellent efficiency and accuracy.To protect the link layer encryption key, season key management concepts are introduced to the tracking cluster mechanism and a tracking cluster rekey protocol is proposed. The cluster season key can be arranged and transmitted through secure links and updated with the cluster's upgrade. It is used to encrypt cluster member reports. This method can increase difficulty to key analysis and improve the security of the tracking result under certain transmission energy cost.To further improve the tracking accuracy, the dissertation introduces the sequence bayes filter method and proposes a distributed particle filter model to reprocess the tracking result in cluster heads. The DPF method can efficiently improve the tracking accuracy. And a Localizer window method is proposed to limit the computation cost of nodes. The testing result proves that this algorithm can efficiently decrease the tracking error between the estimated results and the location of target.