| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2014: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Outline of Final Research Achievements |
While data about various personal activities had been collected and used through data mining, such use of personal data had caused privacy problem. Anonymization techniques had been expected to solve the privacy problem but security of these techniques had not been sufficiently analyzed. To clarify the security of anonymization techniques, we studied de-anonymization attacks that enable re-identifying persons from anonymized data. We also studied level of anonymization that stands against the de-anonymization attacks. We developed our de-anonymization techniques based on machine learning by using real data of SNS posts and of location histories collected through WiFi base stations.
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