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DOLOS: Tricking the Wi-Fi APs with Incorrect User Locations

Aditya Arun, Vaibhav Anand, Wei Sun, Roshan Ayyalasomayajula, Dinesh Bharadia

TL;DR

DOLOS is a software-only solution that can protect the location privacy of the Wi-Fi user with a novel signal obfuscation approach that can degrade the localization accuracy of state-of-art systems by 6x for a single AP and 2.5x for multiple AP scenarios, thereby protecting the Wi-Fi user's location privacy without compromising the Wi-Fi communication performance.

Abstract

Wi-Fi-based indoor localization has been extensively studied for context-aware services. As a result, the accurate Wi-Fi-based indoor localization introduces a great location privacy threat. However, the existing solutions for location privacy protection are hard to implement on current devices. They require extra hardware deployment in the environment or hardware modifications at the transmitter or receiver side. To this end, we propose DOLOS, a system that can protect the location privacy of the Wi-Fi user with a novel signal obfuscation approach. DOLOSis a software-only solution that can be deployed on existing protocol-compliant Wi-Fi user devices. We provide this obfuscation by invalidating a simple assumption made by most localization systems -- "direct path signal arrives earlier than all the reflections to distinguish this direct path prior to estimating the location". However, DOLOS creates a novel software fix that allows the user to transmit the signal wherein this direct path arrives later, creating ambiguity in the location estimates. Our experimental results demonstrate DOLOS can degrade the localization accuracy of state-of-art systems by 6x for a single AP and 2.5x for multiple AP scenarios, thereby protecting the Wi-Fi user's location privacy without compromising the Wi-Fi communication performance.

DOLOS: Tricking the Wi-Fi APs with Incorrect User Locations

TL;DR

DOLOS is a software-only solution that can protect the location privacy of the Wi-Fi user with a novel signal obfuscation approach that can degrade the localization accuracy of state-of-art systems by 6x for a single AP and 2.5x for multiple AP scenarios, thereby protecting the Wi-Fi user's location privacy without compromising the Wi-Fi communication performance.

Abstract

Wi-Fi-based indoor localization has been extensively studied for context-aware services. As a result, the accurate Wi-Fi-based indoor localization introduces a great location privacy threat. However, the existing solutions for location privacy protection are hard to implement on current devices. They require extra hardware deployment in the environment or hardware modifications at the transmitter or receiver side. To this end, we propose DOLOS, a system that can protect the location privacy of the Wi-Fi user with a novel signal obfuscation approach. DOLOSis a software-only solution that can be deployed on existing protocol-compliant Wi-Fi user devices. We provide this obfuscation by invalidating a simple assumption made by most localization systems -- "direct path signal arrives earlier than all the reflections to distinguish this direct path prior to estimating the location". However, DOLOS creates a novel software fix that allows the user to transmit the signal wherein this direct path arrives later, creating ambiguity in the location estimates. Our experimental results demonstrate DOLOS can degrade the localization accuracy of state-of-art systems by 6x for a single AP and 2.5x for multiple AP scenarios, thereby protecting the Wi-Fi user's location privacy without compromising the Wi-Fi communication performance.
Paper Structure (30 sections, 11 equations, 14 figures)

This paper contains 30 sections, 11 equations, 14 figures.

Table of Contents

  1. Introduction
  2. Threat Model
  3. Primer on Wireless Localization
  4. Indoor localization
  5. Nulling to the direct path
  6. Designing Software-level Obfuscation
  7. Intuition on location obfuscation
  8. Channel estimation at the attacking AP
  9. Selective beamforming and controlled delay
  10. Adding back the reflections
  11. Generalizing to Multi-AP
  12. Enhancing location obfuscation through randomization
  13. Implementation
  14. Evaluation
  15. End-to-end System Evaluation
  16. ...and 15 more sections

Figures (14)

  • Figure 1: (a) DOLOS-disabled Wi-Fi user can be accurately localized by the Wi-Fi AP thereby introducing the location privacy threat. (b) DOLOS-enabled Wi-Fi user can obfuscate the wireless signals for location privacy protection.
  • Figure 2: (a) Direct path (green) arrives earlier at the AP due to shorter path length (b) Nulling the direct path obfuscates the AoA, but reduces signal strength (c) Naively delaying the paths does not change the relative arrival times, (d) DOLOS selectively delays only the direct path, breaking the assumption in (a). Inset: relative phase accrued from path length difference due to angle of arrival across receive antennas
  • Figure 3: Wi-Fi-based localization with estimated AoA and ToF. After the Wi-Fi AP obtains the AoA $\theta_0$ and ToF $\tau_0$, the user's location is pinpointed. The right figure shows the profile with the SpotFi algorithm for AoA and ToF identification.
  • Figure 4: Wireless Channel based User Localization: The user transmits a known precoded signal across $3$ time symbols from the $3$ antennas. The signals travel via multiple paths (green, blue) to the AP. The channel can be estimated based on the known transmitted signal. SpotFi spotfi is applied to segregate the paths across the angle and distance domain.
  • Figure 5: (a) SpotFi profile of channel simulated assuming 4 RX antennas, 4 TX antennas, and 40 MHz bandwidth; (b) applying delay and beamforming towards direct path, both paths are delayed; (c) applying delay and beamforming solely towards direct path and nulling elsewhere, removes reflections; (d) re-injecting reflections naively distorts the profile; (e) re-injecting reflections while aware of direct-path obfuscates channel.
  • ...and 9 more figures