Privacy games along location traces: a game-theoretic framework for optimizing location privacy
- Submitting institution
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Cardiff University / Prifysgol Caerdydd
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 97100653
- Type
- D - Journal article
- DOI
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10.1145/3009908
- Title of journal
- ACM Transactions on Privacy and Security
- Article number
- 11
- First page
- -
- Volume
- 19
- Issue
- 4
- ISSN
- 2471-2566
- Open access status
- Compliant
- Month of publication
- December
- Year of publication
- 2016
- URL
-
http://dx.doi.org/10.1145/3009908
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
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C - Cybersecurity, privacy and human centred computing
- Citation count
- 32
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- A significant design for location privacy mechanisms, being provably optimal in two ways: First, no other mechanism can provide better privacy against any given adversarial strategy. Second, there is no better inference strategy for the adversary to reduce privacy. The design is based on Bayesian Stackelberg games and linear programming, where parameters of the mechanism are the variables of the optimisation problem, so optimality is guaranteed by construction. Such guarantees are rare anywhere in security research outside of formal methods and cryptography. Our definitions of location privacy have since been adopted by multiple researchers (e.g., https://doi.org/10.1109/CSF.2018.00026 and https://doi.org/10.1109/CSF49147.2020.00019)
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -