Privacy in Statistical Databases: UNESCO Chair in Data Privacy, International Conference, Psd 2020, Tarragona, Spain, September 23-25, 2020, Proceedin
暫譯: 統計資料庫中的隱私：聯合國教科文組織數據隱私講座，國際會議，Psd 2020，西班牙塔拉戈納，2020年9月23-25日，會議紀錄
Domingo-Ferrer, Josep, Muralidhar, Krishnamurty
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商品描述
This book constitutes the refereed proceedings of the International Conference on Privacy in Statistical Databases, PSD 2020, held in Tarragona, Spain, in September 2020 under the sponsorship of the UNESCO Chair in Data Privacy.
The 25 revised full papers presented were carefully reviewed and selected from 49 submissions. The papers are organized into the following topics: privacy models; microdata protection; protection of statistical tables; protection of interactive and mobility databases; record linkage and alternative methods; synthetic data; data quality; and case studies.
The Chapter "Explaining recurrent machine learning models: integral privacy revisited" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
商品描述(中文翻譯)
本書是2020年9月在西班牙塔拉戈納舉行的國際統計數據庫隱私會議（PSD 2020）的經過審核的會議論文集，該會議由聯合國教科文組織數據隱私講座贊助。
本書收錄的25篇修訂完整論文是從49篇投稿中精心審核和選出的。這些論文的主題包括：隱私模型；微數據保護；統計表的保護；互動和移動數據庫的保護；記錄連結和替代方法；合成數據；數據質量；以及案例研究。
章節「解釋重複的機器學習模型：整體隱私的再探討」可通過link.springer.com在創用CC 4.0國際授權下開放訪問。
