個資去識別化技術之探析

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Title:	個資去識別化技術之探析 Analysis of Personal Data De-identification Techniques
Authors:	吳建成
Contributors:	資訊管理學系碩士在職專班
Keywords:	個資保護去識別化技術資料有用性適法性重新識別攻擊 personal data protection de-identification techniques data usefulness legality re-identification attack
Date:	2020
Issue Date:	2020-08-06
Abstract:	目前大數據及開放資料盛行，為了保護個人隱私，故而有去識別化技術之誕生，與此同時，我國亦推出相應之法規範及標準。基於資料有用性與隱私保護之權衡下，是以有去識別化之必要，而技術之擇用則對去識別化過程之成敗至關重要，至於成敗判定之標準，則端視法規範之要求。由於本論文乃以去識別化技術之探析為主軸，而資料有用性與適法性又是不可不考量者，因此，本論文先闡釋及探討常見之去識別化技術，其次，介紹兩種常用的正規隱私量測模型，使得去識別化後之效能得以量測。嗣後，則設計一情境來演示去識別化過程，再就結果進行技術性、資料有用性之分析，並依據我國法規範探討其適法性。希望藉由本論文指出之三構面——技術性、資料有用性與適法性，以及在此三構面下所建立的K-匿名模型之框架，在組織有去識別化之需求時，能於技術擇用、模型建立及效能評估方面給予參考與指引。 At present, big data and open data are prevalent. In order to protect personal privacy, de-identification techniques have been born. At the same time, our country has also intro-duced corresponding legal norms and standards. Based on the trade-off between usefulness and privacy protection, de-identification is necessary, and the selection of de-identification techniques are crucial to the success or failure of the de-identification process. As for the success or failure of the de-identification process, the judgment criteria depends on the requirements of legal norms. Since this paper focuses on the analysis of de-identification techniques, and data usefulness and legality are indispensable, this paper first explains and discusses the common de-identification techniques. Secondly, two commonly used formal privacy measurement models are introduced, so that the effectiveness of de-identification can be measured. After that, a scenario was designed to demonstrate the process of de-identification, and then the results were analyzed in terms of technicality and data use-fulness, and the legality of the results was discussed based on our country's legal norms. It is hoped that through the three dimensions pointed out in this paper—technicality, data use-fulness and legality, as well as the framework of the K-anonymity formal privacy meas-urement model established under these three dimensions, when the organization has the need for de-identification, they can provide reference and guidance in technques selection, model building and performance evaluation. This may be the meager contribution of this research to the protection of personal privacy.
Appears in Collections:	[Department of Information Management & Graduate Institute of Information Management] Thesis

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