| 研究課題/領域番号 |
19K20269
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| 研究機関 | 京都大学 |
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研究代表者 |
曹 洋 京都大学, 情報学研究科, 特定准教授 (60836344)
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| 研究期間 (年度) |
2019-04-01 – 2023-03-31
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| キーワード | differential privacy / spatiotemporal privacy / location privacy / data correlations |
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| 研究実績の概要 |
Local differential privacy (LDP) has been used widely for spatiotemporal data analysis; however, recent studies demonstrate LDP is vulnerable to manipulation attack under malicious clients. In order to prevent this risk, we propose secure and efficient verifiable LDP protocols to prevent manipulation attacks by leveraging Cryptographic Randomized Response Technique (CRRT) as a building block to convert existing LDP mechanisms into a verifiable version. This work was accepted in 35th Annual IFIP WG 11.3 Conference (DBSec) 2021. Also, we are studying how to enhance the utility of differentially private data release under temporal correlations. Our idea is to design a new post-processing method to leverage the temporal correlations, which is assumed to be public. We had obtained preliminary results that verified the effectiveness of our idea. Currently, we are working on completing the extensive experiments and submitting to an international conference.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
We have achieved the original goal of this project: exploring the issues when applying differential privacy to spatiotemporal data. Besides this, we also obtained some new results and insights regarding the new security vulnerability of existing privacy-enhancing techniques under malicious clients.
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| 今後の研究の推進方策 |
The extended period will be used to prepare the extensive experiments and submission for the topic of "boosting utility of differentially private stream data release".
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| 次年度使用額が生じた理由 |
We will need more time to prepare the extensive experiments and submission for the work on "boosting utility of differentially private stream data release".
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