Linking Sensitive Data: Methods and Techniques for Practical Privacy-Preserving Information Sharing
暫譯: 連結敏感數據：實用的隱私保護信息共享方法與技術
Christen, Peter, Ranbaduge, Thilina, Schnell, Rainer
- 出版商: Springer
- 出版日期: 2020-10-18
- 售價: $7,160
- 貴賓價: 9.5 折 $6,802
- 語言: 英文
- 頁數: 468
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 3030597059
- ISBN-13: 9783030597054
海外代購書籍(需單獨結帳)
商品描述
This book provides modern technical answers to the legal requirements of pseudonymisation as recommended by privacy legislation. It covers topics such as modern regulatory frameworks for sharing and linking sensitive information, concepts and algorithms for privacy-preserving record linkage and their computational aspects, practical considerations such as dealing with dirty and missing data, as well as privacy, risk, and performance assessment measures. Existing techniques for privacy-preserving record linkage are evaluated empirically and real-world application examples that scale to population sizes are described. The book also includes pointers to freely available software tools, benchmark data sets, and tools to generate synthetic data that can be used to test and evaluate linkage techniques.
This book consists of fourteen chapters grouped into four parts, and two appendices. The first part introduces the reader to the topic of linking sensitive data, the second part covers methods and techniques to link such data, the third part discusses aspects of practical importance, and the fourth part provides an outlook of future challenges and open research problems relevant to linking sensitive databases. The appendices provide pointers and describe freely available, open-source software systems that allow the linkage of sensitive data, and provide further details about the evaluations presented. A companion Web site at https: //dmm.anu.edu.au/lsdbook2020 provides additional material and Python programs used in the book. This book is mainly written for applied scientists, researchers, and advanced practitioners in governments, industry, and universities who are concerned with developing, implementing, and deploying systems and tools to share sensitive information in administrative, commercial, or medical databases.商品描述(中文翻譯)
這本書提供了現代技術解決方案，以滿足隱私法規所建議的假名化法律要求。內容涵蓋了現代監管框架以分享和連結敏感資訊的主題、隱私保護記錄連結的概念和演算法及其計算方面、實務考量如處理髒資料和缺失資料，以及隱私、風險和性能評估措施。現有的隱私保護記錄連結技術經過實證評估，並描述了可擴展到人口規模的實際應用範例。書中還包括指向免費可用的軟體工具、基準數據集和生成合成數據的工具，這些工具可用於測試和評估連結技術。
本書共由十四章組成，分為四個部分，並附有兩個附錄。第一部分介紹了連結敏感數據的主題，第二部分涵蓋了連結這些數據的方法和技術，第三部分討論了實務重要性方面，第四部分則提供了未來挑戰和與連結敏感數據庫相關的開放研究問題的展望。附錄提供了指向免費開源軟體系統的資訊，這些系統允許連結敏感數據，並提供有關所呈現評估的進一步細節。伴隨的網站 https://dmm.anu.edu.au/lsdbook2020 提供了額外的材料和書中使用的 Python 程式。
這本書主要是為應用科學家、研究人員以及政府、產業和大學中的高級從業人員撰寫的，他們關心開發、實施和部署系統及工具，以在行政、商業或醫療數據庫中分享敏感資訊。
這本書描述了連結方法的運作方式以及如何評估其性能。它涵蓋了所有主要概念和方法，並討論了計算效率等實務問題，這些在實際應用中至關重要——而且它以高度可讀的方式完成了這一切。
—— David J. Hand，倫敦帝國學院
作者簡介
Peter Christen is Professor at the Australian National University (ANU) Research School of Computer Science (RSCS). His research interests are in record linkage and data mining, with a focus on privacy and machine learning aspects of record linkage. He has published nearly 200 articles in these areas, including the monograph "Data Matching" published by Springer in 2012.
Thilina Ranbaduge is a research fellow at the Australian National University (ANU) Research School of Computer Science (RSCS). His research interests are in privacy-preserving record linkage, multi-database linkage, and data mining. He has published more than 30 papers related to record linkage and privacy-preserving record linkage.
Rainer Schnell is Professor at the University of Duisburg-Essen and holds the Chair in Research Methodology in the Social Sciences. He had been Director of the Centre of Comparative Social Surveys at the University of London, City from 2015 to 2017. He is a survey methodologist with a research focus on non-sampling errors, applied sampling, census operations, and privacy-preserving record linkage. He has published four books on research methodology and more than 60 papers on record linkage.
作者簡介(中文翻譯)
彼得·克里斯滕（Peter Christen）是澳洲國立大學（ANU）計算機科學研究學院（RSCS）的教授。他的研究興趣包括記錄連結和數據挖掘，特別關注記錄連結的隱私和機器學習方面。他在這些領域發表了近200篇文章，包括2012年由Springer出版的專著《數據匹配》（Data Matching）。
提利納·蘭巴杜格（Thilina Ranbaduge）是澳洲國立大學（ANU）計算機科學研究學院（RSCS）的研究員。他的研究興趣包括隱私保護的記錄連結、多數據庫連結和數據挖掘。他已發表超過30篇與記錄連結和隱私保護的記錄連結相關的論文。
雷納·施奈爾（Rainer Schnell）是杜伊斯堡-埃森大學的教授，並擔任社會科學研究方法論的講座教授。他曾於2015年至2017年擔任倫敦城市大學比較社會調查中心的主任。他是一位調查方法學家，研究重點包括非抽樣誤差、應用抽樣、普查操作和隱私保護的記錄連結。他已出版四本關於研究方法論的書籍，以及超過60篇有關記錄連結的論文。
