Hiding in the mobile crowd: location privacy through collaboration
- Submitting institution
-
Cardiff University / Prifysgol Caerdydd
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 97100533
- Type
- D - Journal article
- DOI
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10.1109/TDSC.2013.57
- Title of journal
- IEEE Transactions on Dependable and Secure Computing
- Article number
- -
- First page
- 266
- Volume
- 11
- Issue
- 3
- ISSN
- 1545-5971
- Open access status
- Out of scope for open access requirements
- Month of publication
- June
- Year of publication
- 2014
- URL
-
https://doi.org/10.1109/TDSC.2013.57
- 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
-
4
- Research group(s)
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C - Cybersecurity, privacy and human centred computing
- Citation count
- 90
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Location privacy mechanisms typically distort user locations before querying untrusted servers (e.g. “Where is the nearest restaurant?”), which reduces response quality. Our privacy solution avoids any distortion by leveraging collaboration with nearby mobile users. The solution is evaluated through simulation on a 509-user mobility dataset and empirically, with a mobile phone implementation that tests resource consumption. One of the first proposed collaboration-based approaches to location privacy, the work is frequently cited in reviews (e.g., https://doi.org/10.1109/JIOT.2018.2820039, https://doi.org/10.1109/ACCESS.2018.2822260), and adapted by other researchers (e.g. https://doi.org/10.1109/INFOCOM.2015.7218474, https://doi.org/10.1016/j.ins.2016.08.010).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -