中大機構典藏-NCU Institutional Repository-提供博碩士論文、考古題、期刊論文、研究計畫等下載:Item 987654321/81196
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 78852/78852 (100%)
Visitors : 37996993      Online Users : 795
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version


    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/81196


    Title: 為減少推論機敏資料設計以資料相依性控制存取權;To Reduce the Inference of Sensitive Data, Design Access Control by Data Dependency
    Authors: 賴彥丞;Lai, Yen-Cheng
    Contributors: 資訊工程學系
    Keywords: 資料推論;功能相依性;資訊系統安全控制;馬賽克理論;個人資料保護;data inference;functional dependency;information system security control;mosaic theory;personal information protection
    Date: 2019-07-26
    Issue Date: 2019-09-03 15:39:04 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 對後端資訊系統而言,目前對個人資料保護的要求與手段,是將機敏性資料隔絕使
    一般大眾不能直接取得。至少就我們近來接觸到的高教校務研究,乃至一般公家機關的
    公開資料,對於間接由一些非敏感性公開資料,拼湊推論而推論出機敏性資料的可能,
    一直並沒有討論與面對。
    在美國雖有「馬賽克理論」與相關案例,對間接推論行為有訂定資料保護權責,但
    保護手段並沒有積極研究。若長此以往不面對處理,可能抑制資訊保有者彼此整合交流
    與公開,使資訊片面破碎,而社會空有豐富資訊卻不能有意義的全盤了解與分析。
    本研究探索功能相依性,據此得出能推論機敏資料的高風險屬性集合,並藉由這些
    高風險屬性集合比對使用者在查詢時是否存在機敏資料推論行為,從而加以防範保護。
    ;From the back-end data system point of view, the primary personal information protection
    mechanism is to block the direct accessing of sensitive data. We have observed the related issues
    in fields of Institutional Research, as well as governments’ information publication. And the
    possibility that sensitive data may be indirectly inferenced by public information, have not been
    addressed.
    In United States, there are cases and discussions about “Mosaic theory”. And
    responsibilities of data holders were legally stated. But no known researches were invested to
    create a responsible mechanism. This may lead to a situation where data holders will not
    willingly integrate, exchange, and publish their data. Our society may not be able to
    comprehensively understand ourselves and conduct effective analysis, even though we do have
    huge volume oh data.
    This research explores the functional dependencies, and compute risky column sets based
    on them. We can then process users’ queries and initiate protection operation if risky data are
    involved.
    Appears in Collections:[Graduate Institute of Computer Science and Information Engineering] Electronic Thesis & Dissertation

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML161View/Open


    All items in NCUIR are protected by copyright, with all rights reserved.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 隱私權政策聲明