Distributed Regression Protocols for Privacy Preserving Data Mining
| Project/Area Number |
25870812
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Intelligent informatics
Information security
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| Research Institution | Waseda University |
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Principal Investigator |
SUKO Tota 早稲田大学, 社会科学総合学術院, 講師 (40409660)
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| Project Period (FY) |
2013-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2014: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2013: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | データマイニング / プライバシー保護 / 分散計算 / 回帰分析 / アルゴリズム |
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| Outline of Final Research Achievements |
In this research, we study a privacy-preserving linear regression analysis. We consider the situation that a number of users have different data. They don’t want to show their data each other, but they want to calculate a certain estimator using all users data. Although some protocols conventionally proposed, we proposed some kind of protocols of distributed calculation method for practical use. we became privacy-preserving linear regression analysis available, if there is multicollinearity ,or sparse data.
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Report
(3 results)
Research Products
(10 results)
