# Privacy-Preserving by Design: Indoor Positioning System Using Wi-Fi Passive TDOA

arXiv: https://arxiv.org/abs/2306.02211 · HTML: https://mlsanity.com/paper/2306.02211/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 66 references that are in the map.
- First posted on arXiv 3 Jun 2023.

## Builds on (most cited first, 5 of 5)

- [A Survey of Indoor Localization Systems and Technologies](https://mlsanity.com/paper/1709.01015/) (2017)
- [CSI-based Fingerprinting for Indoor Localization: A Deep Learning Approach](https://mlsanity.com/paper/1603.07080/) (2016)
- [Effectiveness of Data Augmentation in Cellular-based Localization Using Deep Learning](https://mlsanity.com/paper/1906.08171/) (2019)
- [Privacy-preserving Pedestrian Tracking using Distributed 3D LiDARs](https://mlsanity.com/paper/2303.09915/) (2023)
- [Communicating Is Crowdsourcing: Wi-Fi Indoor Localization with CSI-based Speed Estimation](https://mlsanity.com/paper/1307.6349/) (2013)

## Built on by (most cited first, 1 of 1)

- [TimeSense: Multi-Person Device-free Indoor Localization via RTT](https://mlsanity.com/paper/2409.00030/) (2024)

## Abstract (arXiv)

Indoor localization systems have become increasingly important in a wide range of applications, including industry, security, logistics, and emergency services. However, the growing demand for accurate localization has heightened concerns over privacy, as many localization systems rely on active signals that can be misused by an adversary to track users' movements or manipulate their measurements. This paper presents PassiFi, a novel passive Wi-Fi time-based indoor localization system that effectively balances accuracy and privacy. PassiFi uses a passive WiFi Time Difference of Arrival (TDoA) approach that ensures users' privacy and safeguards the integrity of their measurement data while still achieving high accuracy. The system adopts a fingerprinting approach to address multi-path and non-line-of-sight problems and utilizes deep neural networks to learn the complex relationship between TDoA and location. Evaluation in a real-world testbed demonstrates PassiFi's exceptional performance, surpassing traditional multilateration by 128%, achieving sub-meter accuracy on par with state-of-the-art active measurement systems, all while preserving privacy.