2022 Fiscal Year Annual Research Report
Achieving Differential Privacy under Spatiotemporal Correlations
| Project/Area Number |
19K20269
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| Research Institution | Hokkaido University |
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Principal Investigator |
曹 洋 北海道大学, 情報科学研究院, 准教授 (60836344)
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| Project Period (FY) |
2019-04-01 – 2023-03-31
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| Keywords | differential privacy / spatiotemporal privacy / プライバシー保護 |
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| Outline of Annual Research Achievements |
During FY 2022, we continued to explore both privacy and utility issues arising from Differential Privacy (DP) in the context of spatiotemporal correlations. Regarding privacy issues, we demonstrated that road networks could expose vulnerabilities in users' location data, even under the protection of DP. Essentially, attackers can exploit prior knowledge about road networks to deduce true locations from noisy (perturbed) locations. For utility issues, we designed post-processing approaches that leverage spatiotemporal correlations as prior information. The idea is to treat correlations as a property of the data, allowing us to model post-processing as an optimization problem constrained by data correlations. Our method significantly improved the utility of privacy-protected data.
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