The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Unique in the Crowd: The privacy bounds of human mobility
Open accessAbstract
We study fifteen months of human mobility data for one and a half million individuals and find that human mobility traces are highly unique. In fact, in a dataset where the location of an individual is specified hourly, and with a spatial resolution equal to that given by the carrier's antennas, four spatio-temporal points are enough to uniquely identify 95% of the individuals. We coarsen the data spatially and temporally to find a formula for the uniqueness of human mobility traces given their resolution and the available outside information. This formula shows that the uniqueness of mobility traces decays approximately as the 1/10 power of their resolution. Hence, even coarse datasets provide little anonymity. These findings represent fundamental constraints to an individual's privacy and have important implications for the design of frameworks and institutions dedicated to protect the privacy of individuals.
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“Indeed, it is clear that it is possible to reverse engineer anonymization strategies by combing and combining datasets [56,57] unless the data are fully de-identified.”
From The ethics of smart cities and urban science (2016) · cites this paper as [57]
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Metadata
- Authors
- de Montjoye, Y.-A., Hidalgo, C. A., Verleysen, M., & Blondel, V. D.
- Affiliations
- Harvard University (US)
- UCLouvain (BE)
- Massachusetts Institute of Technology (US)
- Venue
- Scientific Reports
- Published
- 2013-03-25
- Volume
- 3
- Issue
- 1
- Pages
- 1376-1376
- ISSN
- 2045-2322 (ISSN-L)
- PMC
- PMC3607247
- OpenAlex
- W2115240023
- Semantic Scholar
- 7fe16a270f403048f78fa89a64410e570ae5c16f
- Cited by
- 1,645
- References
- 29
- Citations by year
- 2026: 96 · 2025: 86 · 2024: 92 · 2023: 96 · 2022: 133 · 2021: 156 · 2020: 191 · 2019: 153 · 2018: 152 · 2017: 124 · 2016: 124 · 2015: 119 · 2014: 89 · 2013: 33
- FWCI
- 134.68
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Scientific Reports (publishedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-nd)
- Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)) (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Keywords
- human mobility, privacy, anonymity, spatiotemporal resolution, location data, privacy preservation
- MeSH terms
- Geography, Humans, Privacy, Databases as Topic, Cell Phone
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