# Optimal Geo-Indistinguishable Mechanisms for Location Privacy

arXiv: https://arxiv.org/abs/1402.5029 · HTML: https://mlsanity.com/paper/1402.5029/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Feb 2014.

## Built on by (most cited first, 9 of 9)

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- [Group privacy for personalized federated learning](https://mlsanity.com/paper/2206.03396/) (2022)
- [Privacy of Autonomous Vehicles: Risks, Protection Methods, and Future Directions](https://mlsanity.com/paper/2209.04022/) (2022)
- [Privacy-Utility Trades in Crowdsourced Signal Map Obfuscation](https://mlsanity.com/paper/2201.04782/) (2022)
- [Where have you been? A Study of Privacy Risk for Point-of-Interest Recommendation](https://mlsanity.com/paper/2310.18606/) (2023)
- [An Easy-to-use and Robust Approach for the Differentially Private De-Identification of Clinical Textual Documents](https://mlsanity.com/paper/2211.01147/) (2022)
- [Enhancing Scalability of Metric Differential Privacy via Secret Dataset Partitioning and Benders Decomposition](https://mlsanity.com/paper/2405.04344/) (2024)
- [Interpolation-Based Optimization for Enforcing lp-Norm Metric Differential Privacy in Continuous and Fine-Grained Domains](https://mlsanity.com/paper/2601.09946/) (2026)
- [Metric-Normalized Posterior Leakage (mPL): Attacker-Aligned Privacy for Joint Consumption](https://mlsanity.com/paper/2605.01137/) (2026)

## Abstract (arXiv)

We consider the geo-indistinguishability approach to location privacy, and the trade-off with respect to utility. We show that, given a desired degree of geo-indistinguishability, it is possible to construct a mechanism that minimizes the service quality loss, using linear programming techniques. In addition we show that, under certain conditions, such mechanism also provides optimal privacy in the sense of Shokri et al. Furthermore, we propose a method to reduce the number of constraints of the linear program from cubic to quadratic, maintaining the privacy guarantees and without affecting significantly the utility of the generated mechanism. This reduces considerably the time required to solve the linear program, thus enlarging significantly the location sets for which the optimal mechanisms can be computed.