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Privacy Preserving Population Distribution Estimation without Trusted Third Parties

Research Project

Project/Area Number 16K16069
Research Category

Grant-in-Aid for Young Scientists (B)

Allocation TypeMulti-year Fund
Research Field Information security
Research InstitutionNational Institute of Advanced Industrial Science and Technology

Principal Investigator

Murakami Takao  国立研究開発法人産業技術総合研究所, 情報・人間工学領域, 主任研究員 (80587981)

Project Period (FY) 2016-04-01 – 2019-03-31
Project Status Completed (Fiscal Year 2018)
Budget Amount *help
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2017: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2016: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Keywords位置情報プライバシー / 空間統計データ / TTP / 加工メカニズム / 分布推定 / データプライバシー / 差分プライバシー / 反復ベイズ法 / 分布推定誤差 / 匿名性 / 再識別攻撃 / バイアス補正 / プライバシー / 位置情報 / 空間統計
Outline of Final Research Achievements

In this work, we studied privacy preserving population distribution estimation without trusted third parties, in which users obfuscates their locations by themselves and a data collector estimates population distribution statistics based on obfuscated location data. We first focused on the iterative Bayesian method, which is a state-of-the-art distribution estimation method, and proposed a method to reduce its estimation error. We showed, both theoretically and experimentally, that the estimation accuracy is improved. We then analyzed the security of the existing obfuscation mechanisms in terms of anonymity, and showed that OptSQL has promising in terms of the capability of anonymization.

Academic Significance and Societal Importance of the Research Achievements

従来の空間統計データ構築技術は,サービス提供事業者が信頼できる機関(TTP: Trusted Third Party)であると仮定しているが,情報漏洩の事故が多発している近年ではこの仮定が成立しなくなってきている.従って,本研究での成果は,ユーザにプライバシーの観点で真の安心感を与えるという大きな意義を持つ.また,その結果,より多くのユーザから大規模な位置情報を収集することが可能となるため,従来よりも高精度な空間統計データの構築も可能となる.

Report

(4 results)
  • 2018 Annual Research Report   Final Research Report ( PDF )
  • 2017 Research-status Report
  • 2016 Research-status Report
  • Research Products

    (4 results)

All 2018

All Journal Article (1 results) (of which Int'l Joint Research: 1 results,  Peer Reviewed: 1 results,  Open Access: 1 results) Presentation (3 results) (of which Int'l Joint Research: 2 results,  Invited: 1 results)

  • [Journal Article] Toward Distribution Estimation under Local Differential Privacy with Small Samples2018

    • Author(s)
      Murakami Takao、Hino Hideitsu、Sakuma Jun
    • Journal Title

      Proceedings on Privacy Enhancing Technologies

      Volume: 2018 Issue: 3 Pages: 84-104

    • DOI

      10.1515/popets-2018-0022

    • Related Report
      2018 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Presentation] On the Anonymization of Differentially Private Location Obfuscation2018

    • Author(s)
      Yusuke Kawamoto, Takao Murakami
    • Organizer
      Proceedings of the 2018 International Symposium on Information Theory and Its Applications (ISITA 2018)
    • Related Report
      2018 Annual Research Report
    • Int'l Joint Research
  • [Presentation] A Succinct Model for Re-identification of Mobility Traces Based on Small Training Data2018

    • Author(s)
      Takao Murakami
    • Organizer
      Proceedings of the 2018 International Symposium on Information Theory and Its Applications (ISITA 2018)
    • Related Report
      2018 Annual Research Report
    • Int'l Joint Research
  • [Presentation] 局所型差分プライバシーと分布推定への応用2018

    • Author(s)
      村上隆夫
    • Organizer
      PWS勉強会(PWS Seminar 2018)
    • Related Report
      2018 Annual Research Report
    • Invited

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Published: 2016-04-21   Modified: 2020-03-30  

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