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The Robustness of Localization Algorithms to Signal Strength Attacks: A Comparative Study

  • Yingying Chen
  • Konstantinos Kleisouris
  • Xiaoyan Li
  • Wade Trappe
  • Richard P. Martin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4026)

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.

Keywords

Bayesian Network Signal Strength Localization Algorithm Voronoi Cell Wormhole Attack 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yingying Chen
    • 1
  • Konstantinos Kleisouris
    • 1
  • Xiaoyan Li
    • 1
  • Wade Trappe
    • 1
  • Richard P. Martin
    • 1
  1. 1.Department of Computer Science and Wireless Information Network LaboratoryRutgers UniversityPiscatawayUSA

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