Privacy-Preserving Record Linkage: Theory, Applications, and Challenges
暫譯: 隱私保護的記錄連結：理論、應用與挑戰
Vatsalan, Dinusha, Asghar, Hassan, Kaafar, Dali
- 出版商: Springer
- 出版日期: 2026-07-29
- 售價: $8,950
- 貴賓價: 9.5 折 $8,502
- 語言: 英文
- 頁數: 275
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 3032219310
- ISBN-13: 9783032219312
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相關分類:
Data-mining
海外代購書籍(需單獨結帳)
商品描述
This is the first book on Privacy-Preserving Record Linkage (PPRL) that provides a comprehensive coverage of the different aspects, ranging from ethical considerations such as fairness-bias in record linkage, and adversarial aspects such as attacks and provable defenses, to advanced data matching and analytics technologies such as linking complex and/or unstructured data and machine learning-based linkage techniques. Personal Identifiable Information (PII) about individuals, such as customers, taxpayers, patients, and mobile application users, is increasingly collected and linked across disparate data sources to enable customized, high-quality, and timely analytical services in a variety of applications. The data needed for the linkage is, however, often personal, and sensitive, and needs to be processed using privacy-preserving techniques.
A large body of work has been conducted in the topic of PPRL over the past three decades. This book covers the technological, adversarial, ethical, and analytical developments in PPRL to provide a comprehensive view of PPRL for implementing practical applications in the Big Data and Analytics Era. It provides 360 degrees of the evolving and contemporary topic covering all the different aspects required to the understanding, designing and implementation of sound and practical PPRL solutions for real-world applications.
This book targets advanced-level students focused on data privacy, record linkage, and data analytics as well as researchers working in this related field. Data science or data linkage practitioners in different domains including health, security, games, business, and finance will also find this book a valuable resource.
商品描述(中文翻譯)
這是第一本關於隱私保護記錄連結（Privacy-Preserving Record Linkage, PPRL）的書籍，全面涵蓋了不同的方面，包括倫理考量，如記錄連結中的公平性偏見，以及對抗性方面，如攻擊和可證明的防禦，還有先進的數據匹配和分析技術，如連結複雜和/或非結構化數據以及基於機器學習的連結技術。關於個人的可識別信息（Personal Identifiable Information, PII），例如客戶、納稅人、病人和移動應用程序用戶，越來越多地被收集並在不同數據來源之間連結，以便在各種應用中提供定制的、高質量的和及時的分析服務。然而，用於連結的數據通常是個人且敏感的，需要使用隱私保護技術進行處理。
在過去三十年中，關於PPRL的研究已經積累了大量的工作。本書涵蓋了PPRL的技術、對抗性、倫理和分析發展，旨在提供一個全面的PPRL視角，以便在大數據和分析時代實施實際應用。它提供了對這一不斷演變和當代主題的360度全景，涵蓋了理解、設計和實施健全且實用的PPRL解決方案所需的所有不同方面，以應對現實世界的應用。
本書的目標讀者是專注於數據隱私、記錄連結和數據分析的高級學生，以及在相關領域工作的研究人員。來自健康、安全、遊戲、商業和金融等不同領域的數據科學或數據連結從業者也會發現本書是一本有價值的資源。
作者簡介
Dinusha Vatsalan is a Senior Lecturer in IT (Higher Grade) at the Northern Uni, Sri Lanka, and an Honorary Lecturer at Macquarie University, Australia. She received her PhD in Computer Science from Australian National University and BSc (Hons) in Information and Communication Technology from University of Colombo, Sri Lanka. She was previously a Senior Lecturer in Cyber Security at Macquarie University, Australia and a Research Scientist at the Australian government's Commonwealth Scientific and Industrial Research Organization (CSIRO). Her research interests are in cybersecurity and privacy-preserving techniques, including privacy in data matching and record linkage, privacy in social media, privacy-preserving data analytics in stream data, privacy risk evaluation and prediction, health informatics, and population informatics. She has published over 80 articles in high-ranked venues on these topics, which have attracted more than 2550 citations.
Hassan Jameel Asghar is a Senior Lecturer and researcher at Macquarie University, specializing in privacy, cryptography, and information security. He has a PhD from the Department of Computing, Macquarie University, and has previously worked as a Research Scientist at Data61, CSIRO. Asghar is a member of the Information Security and Privacy Research Group at Macquarie University and has contributed to various research and industry projects related to security and privacy. He has authored over 80 articles on security and privacy related topics including quantitative privacy risk assessment, privacy-preserving access to and release of data, and secure protocols for outsourced computation.
Dali Kaafar is a Professor at Macquarie University and Executive Director of Macquarie University Cyber Security Hub. He obtained a Ph.D. in Computer Science from University of Nice Sophia Antipolis at Inria France. He was the founder of the Information Security and Privacy Group and leader of the Networks group at CSIRO Data61. He was previously a Senior Principal Researcher, Research leader and a principal researcher at the Mobile Networks Systems group at NICTA and a researcher at the Privatics team at INRIA in France. Dali has made significant contributions to the fields of cybersecurity, privacy, and AI. His research interests include digital privacy, distributed systems security, authentication systems, and security risks measurement and modeling. He has authored over 300 scientific peer-reviewed papers and has advised governments on scam prevention policy. He is also the founder and CEO of Apate.ai, a company that builds large-scale conversational bots to disrupt global scams and extract threat intelligence in real time.
作者簡介(中文翻譯)
Dinusha Vatsalan 是斯里蘭卡北方大學的資深講師（高級職級），同時也是澳洲麥考瑞大學的榮譽講師。她在澳洲國立大學獲得計算機科學博士學位，並在斯里蘭卡科倫坡大學獲得資訊與通信技術的榮譽學士學位。她曾擔任澳洲麥考瑞大學的網絡安全資深講師，以及澳洲政府的聯邦科學與工業研究組織（CSIRO）的研究科學家。她的研究興趣包括網絡安全和隱私保護技術，涵蓋數據匹配和記錄連結中的隱私、社交媒體中的隱私、流數據中的隱私保護數據分析、隱私風險評估和預測、健康資訊學以及人口資訊學。她在這些主題上發表了超過80篇高排名的文章，並吸引了超過2550次的引用。
Hassan Jameel Asghar 是麥考瑞大學的資深講師和研究員，專注於隱私、密碼學和資訊安全。他擁有麥考瑞大學計算系的博士學位，並曾在CSIRO的Data61擔任研究科學家。Asghar 是麥考瑞大學資訊安全與隱私研究小組的成員，並參與了多個與安全和隱私相關的研究和產業專案。他在安全和隱私相關主題上發表了超過80篇文章，包括定量隱私風險評估、隱私保護的數據訪問和釋放，以及外包計算的安全協議。
Dali Kaafar 是麥考瑞大學的教授及麥考瑞大學網絡安全中心的執行董事。他在法國的尼斯索非亞大學獲得計算機科學博士學位。Dali 是資訊安全與隱私小組的創始人，並曾在CSIRO Data61擔任網絡小組的負責人。他曾擔任NICTA移動網絡系統小組的資深首席研究員、研究負責人及首席研究員，並在法國的INRIA Privatics團隊擔任研究員。Dali 在網絡安全、隱私和人工智慧領域做出了重要貢獻。他的研究興趣包括數位隱私、分散式系統安全、身份驗證系統以及安全風險的測量和建模。他已發表超過300篇經過同行評審的科學論文，並為政府提供有關防詐騙政策的建議。他也是Apate.ai的創始人和首席執行官，該公司建立大規模的對話式機器人，以打擊全球詐騙並實時提取威脅情報。
