LocLok: Location Cloaking with Differential Privacy via Hidden Markov Model
Summary: LocLok combines hidden Markov models with differential-privacy location cloaking, explicitly modeling temporal correlations. It uses the planar isotropic mechanism—the first to attain the DP lower bound—to release optimal noisy locations and infer true positions. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Yonghui Xiao (Emory University)
- 2. Li Xiong (Emory University)
- 3. Si Zhang (Jianghan University)
- 4. Yang Cao (Emory University)
BibTeX Citation
@article{xiao_vldb17,
title = {{LocLok: Location Cloaking with Differential Privacy via Hidden Markov Model}},
author = {Xiao, Yonghui and Xiong, Li and Zhang, Si and Cao, Yang},
journal = {PVLDB},
series = {{VLDB} '17},
volume = {10},
number = {12},
pages = {1901--1904},
doi = {10.14778/3137765.3137804},
url = {https://doi.org/10.14778/3137765.3137804},
year = {2017}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,818 | PANDA: Policy-aware Location Privacy for Epidemic Surveillance | 2020 | VLDB | 5.093636e-05 |
| 13,511 | PriSTE: Protecting Spatiotemporal Event Privacy in Continuous Location-Based Services | 2019 | VLDB | - |
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Outgoing Citations (Sorted by Pagerank)
Showing 1 of 1 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,499 | MaskIt: Privately Releasing User Context Streams for Personalized Mobile Applications | 2012 | SIGMOD | 6.1972571e-05 |
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