An Efficient Gradient Descent Approach to Secure Localization in Resource Constrained Wireless Sensor Networks

Abstract

Many applications of wireless sensor networks require precise knowledge of the locations of constituent nodes. In these applications, it is desirable for the nodes to be able to autonomously determine their locations before they start sensing and transmitting data. Most localization algorithms use anchor nodes with known locations to determine the positions of the remaining nodes. However, these existing techniques often fail in hostile environments where some of the nodes may be compromised by adversaries and used to transmit misleading information aimed at preventing accurate localization of the remaining sensors. In this paper, a computationally efficient secure localization algorithm that withstands such attacks is described. The proposed algorithm combines iterative gradient descent with selective pruning of inconsistent measurements to achieve high localization accuracy. Results show that the proposed algorithm utilizes fewer computational resources and achieves an accuracy better than or comparable to that of existing schemes. The proposed secure localization algorithm can also be used in mobile sensor networks, where all nodes are moving, to estimate the relative locations of the nodes without relying on anchor nodes. Simulations demonstrate that the proposed algorithm can find the relative location map of the entire mobile sensor network even when some nodes are compromised and transmit false information.