The Study Of Secure Localization Technology In Wireless Sensor Networks

Recently, wireless sensor network (WSN) has received increasing attention, and it has wide applications in the aspects of industry, military, and environment. As one of the key enabling technologies and research hotspots, node localization is very important due to its direct correlation with theoretical research and practical application. In real environment, WSN is vulnerable to a variety of different forms of attack, which will affect localization process and even make the localization information completely meaningless. Therefore, security in localization process is very important. The paper has studied secure localization in WSN based on the DV-Hop protocol.Firstly, considering the existed security vulnerabilities of DV-Hop protocol in producing the average distance of each hop in networks, we propose a Minkowski distance based node localization algorithm for WSN. First of all, it collects the average distance of each hop produced by different beacons, and preprocesses them. In the meantime, it removes the beacons which make localization error quite large. Then, sensor nodes use the average distance of each hop produced by the beacons which have the right of localization and the average distance of each hop in networks to calculate the Minkowski distance. The distance is the distance of overall differences error. At last, sensor nodes determine the direction of the error deviation, and amend the average distance of each hop in networks. After that, they can get the reasonable average distance of each hop in networks, and finish localization.Secondly, since the present algorithms are on the assumption of correct beacon information, when the network is attacked, especially the beacons are captured by opponent, all algorithms will not work. To address this issue, an attack-resistant node localization algorithm which is on the basis of DV-Hop protocol and based on the voting mechanism is presented. Sensor nodes quantize the target field into the same size grids, establish the reference set of the locations of beacons, and divide the set into different subsets. It use trilateration to localization in each subset and the results are mapped to grids as votes. At last, sensor notes can fix their locations by computing the geometrical center of the area which has the most votes.The simulation results show that the improved algorithms have no excessive demands in the aspects of beacon density, network connectivity and additional hardware overhead. They can also improve the stability and practicality of the algorithms, and can be applied to WSN which has the low resources and large randomness of network topology.