Systematic studies on de-anonymization attacks and their countermeasures
Project/Area Number |
26330153
|
Research Category |
Grant-in-Aid for Scientific Research (C)
|
Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
Information security
|
Research Institution | The University of Electro-Communications |
Principal Investigator |
Yoshiura Hiroshi 電気通信大学, 大学院情報理工学研究科, 教授 (40361828)
|
Co-Investigator(Kenkyū-buntansha) |
久保山 哲二 学習院大学, 付置研究所, 教授 (80302660)
|
Project Period (FY) |
2014-04-01 – 2018-03-31
|
Project Status |
Completed (Fiscal Year 2017)
|
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)
|
Keywords | プライバシー保護 / 個人情報保護 / 情報セキュリティ / 匿名化 / 個人特定 / 不正抑止 / 機械学習 |
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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Report
(5 results)
Research Products
(17 results)