エビデンスに基づいた匿名化  [in Japanese] Evidence Based Anonymization  [in Japanese]

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Abstract

<p>匿名データについて,個体識別が可能か否かの判定は定義に関わる.しかしこの判定は明確に定式化されていないため,改善のための議論がかみ合わない.従って本論文は,個体識別可能性の判定方式を定量評価に基づいて明確化する.このような判定方式に関する既存研究は存在するが,個体識別可能性の測度について閾値を定める理論が欠けている.この点について本論文では,個体識別が起きていないという観測可能な事実に基づいて統計的に閾値を推定する.このような実証的態度により,匿名データ制度を根拠に基づいて継続的に改善することが出来る.実際に本論文では個体識別可能性審査の改善を提案する.</p>

<p>Anonymized Data are defined so that no individual shall be identified. This unidentifiability, however, is not clearly defined. Hence the assessment process of this unidentifiability has not been clearly formulated, which results in few consistent arguments on the improvement of the process. Therefore the present paper substantiates one clear method to decide whether given data are identifiable or not by measuring re-identification risk. The existing theory of re-identification risk lacks the method of deciding its critical value; the present paper statistically estimates it using a fact that identification has not been observed. Our evidence based method, supported by facts, ensures lasting improvements on the institution of Anonymized Data. The present paper actually proposes concrete improvements on its assessment process.</p>

Journal

  • Journal of the Japan Statistical Society, Japanese Issue

    Journal of the Japan Statistical Society, Japanese Issue 46(1), 1-42, 2016

    Japan Statistical Society

Codes

  • NII Article ID (NAID)
    130006026435
  • NII NACSIS-CAT ID (NCID)
    AA11989749
  • Text Lang
    JPN
  • ISSN
    0389-5602
  • NDL Article ID
    027853684
  • NDL Call No.
    Z3-1003
  • Data Source
    NDL  J-STAGE 
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