Attack-Resistant Location Estimation in Wireless Sensor Networks

  • Authors:
  • Donggang Liu;Peng Ning;An Liu;Cliff Wang;Wenliang Kevin Du

  • Affiliations:
  • The University of Texas at Arlington;North Carolina State University;North Carolina State University;Army Research Office;Syracuse University

  • Venue:
  • ACM Transactions on Information and System Security (TISSEC)
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

Many sensor network applications require sensors' locations to function correctly. Despite the recent advances, location discovery for sensor networks in hostile environments has been mostly overlooked. Most of the existing localization protocols for sensor networks are vulnerable in hostile environments. The security of location discovery can certainly be enhanced by authentication. However, the possible node compromises and the fact that location determination uses certain physical features (e.g., received signal strength) of radio signals make authentication not as effective as in traditional security applications. This article presents two methods to tolerate malicious attacks against range-based location discovery in sensor networks. The first method filters out malicious beacon signals on the basis of the “consistency” among multiple beacon signals, while the second method tolerates malicious beacon signals by adopting an iteratively refined voting scheme. Both methods can survive malicious attacks even if the attacks bypass authentication, provided that the benign beacon signals constitute the majority of the beacon signals. This article also presents the implementation and experimental evaluation (through both field experiments and simulation) of all the secure and resilient location estimation schemes that can be used on the current generation of sensor platforms (e.g., MICA series of motes), including the techniques proposed in this article, in a network of MICAz motes. The experimental results demonstrate the effectiveness of the proposed methods, and also give the secure and resilient location estimation scheme most suitable for the current generation of sensor networks.