Outsourcing of privacy preserving data mining for large-scale non-structured information
| Project/Area Number |
24680015
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| Research Category |
Grant-in-Aid for Young Scientists (A)
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| Allocation Type | Partial Multi-year Fund |
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| Research Field |
Intelligent informatics
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| Research Institution | University of Tsukuba |
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Principal Investigator |
SAKUMA Jun 筑波大学, システム情報系, 教授 (90376963)
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| Project Period (FY) |
2012-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥26,260,000 (Direct Cost: ¥20,200,000、Indirect Cost: ¥6,060,000)
Fiscal Year 2015: ¥7,280,000 (Direct Cost: ¥5,600,000、Indirect Cost: ¥1,680,000)
Fiscal Year 2014: ¥7,540,000 (Direct Cost: ¥5,800,000、Indirect Cost: ¥1,740,000)
Fiscal Year 2013: ¥7,410,000 (Direct Cost: ¥5,700,000、Indirect Cost: ¥1,710,000)
Fiscal Year 2012: ¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
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| Keywords | 準同型暗号 / 差分プライバシー / プライバシ保護データマイニング / アウトソーシング / 秘密計算 / 統計解析 / レコードリンケージ / プライバシ / セキュリティ / データマイニング / 機械学習 / 差分プライバシ / 差別配慮 / プライバシー |
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| Outline of Final Research Achievements |
For outsourcing of privacy-preserving data mining with large-scale data, we consider two tasks: secure computation and statistical privacy. When the data contains private information and is distributed over multiple locations, the former provides a methodology that computes a specified function with the distributed data sources with keeping the secrecy of data in the process of computation. The latter aims to prevent inference of input from the computed results. In this research project, we developed studies on secure computation and statistical privacy (including differential privacy) for various statistics and data mining tasks. More specifically, we developed secure computation of vector matrix multiplication, set intersection cardinality, statistical testing, and so on. For statistical privacy, we studied differential privacy of outlier detection and privacy protection by interval release.
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Report
(6 results)
Research Products
(36 results)
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[Journal Article] Prediction with Model-Based Neutrality2015
Author(s)
Kazuto Fukuchi, Toshihiro Kamishima, and Jun Sakuma
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Journal Title
IEICE Transactions on Information and Systems
Volume: E98.D
Issue: 8
Pages: 1503-1516
DOI
NAID
ISSN
0916-8532, 1745-1361
Related Report
Peer Reviewed / Acknowledgement Compliant
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[Journal Article] Differentially Private Analysis of Outliers2015
Author(s)
Rina Okada, Kazuto Fukuchi, Jun Sakuma
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Journal Title
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015
Volume: 9285
Pages: 458-473
DOI
ISBN
9783319235240, 9783319235257
Related Report
Peer Reviewed / Acknowledgement Compliant
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