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Location Proximity Attacks Against Mobile Targets: Analytical Bounds and Attacker Strategies

  • Xueou Wang
  • Xiaolu Hou
  • Ruben Rios
  • Per Hallgren
  • Nils Ole Tippenhauer
  • Martín Ochoa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11099)

Abstract

Location privacy has mostly focused on scenarios where users remain static. However, investigating scenarios where the victims present a particular mobility pattern is more realistic. In this paper, we consider abstract attacks on services that provide location information on other users in the proximity. In that setting, we quantify the required effort of the attacker to localize a particular mobile victim. We prove upper and lower bounds for the effort of an optimal attacker. We experimentally show that a Linear Jump Strategy (LJS) practically achieves the upper bounds for almost uniform initial distributions of victims. To improve performance for less uniform distributions known to the attacker, we propose a Greedy Updating Attack Strategy (GUAS). Finally, we derive a realistic mobility model from a real-world dataset and discuss the performance of our strategies in that setting.

Notes

Acknowledgements

Xueou was supported by SUTD-ZJU grant ZJUSP1600102. R. Rios was partially funded by the Spanish Ministry of Economy and Competitiveness (TIN2016-79095-C2-1-R, TIN2014-54427-JIN) and the ‘Captación de Talento para la Investigación’ fellowship from University of Malaga. This work was partly funded by the Swedish Foundation for Strategic Research (SSF) and the Swedish Research Council (VR).

Supplementary material

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Singapore University of Technology and Design (SUTD)SingaporeSingapore
  2. 2.Cyber Security Lab, School of Computer Science and EngineeringNanyang Technological UniversitySingaporeSingapore
  3. 3.Computer Science DepartmentUniversity of MálagaMálagaSpain
  4. 4.Chalmers University of TechnologyGothenburgSweden
  5. 5.Einride ABStockholmSweden
  6. 6.Department of Applied Mathematics and Computer ScienceUniversidad del RosarioBogotáColombia

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