The robustness of localization algorithms to signal strength attacks: a comparative study

  • Authors:

  • Yingying Chen;Konstantinos Kleisouris;Xiaoyan Li;Wade Trappe;Richard P. Martin

  • Affiliations:

  • Department of Computer Science and Wireless Information Network Laboratory, Rutgers University, Piscataway, NJ;Department of Computer Science and Wireless Information Network Laboratory, Rutgers University, Piscataway, NJ;Department of Computer Science and Wireless Information Network Laboratory, Rutgers University, Piscataway, NJ;Department of Computer Science and Wireless Information Network Laboratory, Rutgers University, Piscataway, NJ;Department of Computer Science and Wireless Information Network Laboratory, Rutgers University, Piscataway, NJ

  • Venue:
  • DCOSS'06 Proceedings of the Second IEEE international conference on Distributed Computing in Sensor Systems
  • Year:
  • 2006

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Abstract

In this paper, we examine several localization algorithms and evaluate their robustness to attacks where an adversary attenuates or amplifies the signal strength at one or more landmarks. We propose several performance metrics that quantify the estimator's precision and error, including Hölder metrics, which quantify the variability in position space for a given variability in signal strength space. We then conduct a trace-driven evaluation of several point-based and area-based algorithms, where we measured their performance as we applied attacks on real data from two different buildings. We found the median error degraded gracefully, with a linear response as a function of the attack strength. We also found that area-based algorithms experienced a decrease and a spatial-shift in the returned area under attack, implying that precision increases though bias is introduced for these schemes. We observed both strong experimental and theoretic evidence that all the algorithms have similar average responses to signal strength attacks.