| 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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| 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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