The Research On Secure Localization Algorithm Against The Malicious Attack In Wireless Sensor Networks

The rapid development of micro-electromechanical systems, system-on-chip, low-power embedded technology and wireless communication technology carries out the wireless sensor network which brought about a information perception change with the nature of low power consumption, low cost, self-organization and distributed. Wireless sensor network is made up of a large number of micro cheap sensor nodes which are distributed in the monitoring area, and these sensor nodes form a self-organizing multi-hop network through wireless communication. According to the different application backgrounds, wireless sensor network supports low-rate and high-rate, near-field and far-field communication.Localization technique is one of the key technologies in wireless sensor network with a wide range of application prospect in the civilian and military fields. Since wireless sensor network is often deployed in malicious and dangerous environment, security has become another issue of concern. If there are attackers or malicious nodes in the environment, the accuracy of node localization will drop and the entire network will be difficult to run properly.This thesis researches the secure localization of malicious attacks environment and has proposed two secure localization algorithm:gradient descent secure localization algorithm and Newton iterative secure localization algorithm. The main idea of the gradient descent algorithm is to minimize a suitable cost function involving the location of the unknown node using an iterative gradient descent method. The gradient is dynamically updated in the process of iteration to remove the inconsistent information arising from malicious anchor nodes. The algorithm operates in two steps. In the first step, the location of unknown node is calculated using the information of all anchor nodes. In the second step, selective pruning of inconsistent information is performed to mitigate the influence of malicious anchor nodes on the solution. Newton iterative algorithm, on the basis of gradient descent algorithm, iterate using second-order Taylor series and Hessian matrix of cost function. It greatly reduces the number of iterations, while improving the stability and accuracy of the algorithm. Both simulations and field experiments are used to show the performance of our algorithms.