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. The Book describes how linkage methods work and how to evaluate their performance. It covers all the major concepts and methods and also discusses practical matters such as computational efficiency, which are critical if the methods are to be used in practice - and it does all this in a highly accessible way!David J. Hand, Imperial College, London

This textbook provides a unique lens through which the myriad of existing Privacy Enhancing Technologies (PETs) can be easily comprehended and appreciated. It answers key privacy-centered questions with clear and detailed explanations. Why is privacy important? How and why is your privacy being eroded and what risks can this pose for you? What are some tools for protecting your privacy in online environments? How can these tools be understood, compared, and evaluated? What steps can you take to gain more control over your personal data? This book addresses the above questions by focusing on three fundamental elements: It introduces a simple classification of PETs that allows their similarities and differences to be highlighted and analyzed; It describes several specific PETs in each class, including both foundational technologies and important recent additions to the field; It explains how to use this classification to determine which privacy goals are actually achievable in a given real-world environment. Once the goals are known, this allows the most appropriate PETs to be selected in order to add the desired privacy protection to the target environment. To illustrate, the book examines the use of PETs in conjunction with various security technologies, with the legal infrastructure, and with communication and computing technologies such as Software Defined Networking (SDN) and Machine Learning (ML). Designed as an introductory textbook on PETs, this book is essential reading for graduate-level students in computer science and related fields, prospective PETs researchers, privacy advocates, and anyone interested in technologies to protect privacy in online environments.

This handbook presents state-of-the-art research in reinforcement learning, focusing on its applications in the control and game theory of dynamic systems and future directions for related research and technology. The contributions gathered in this book deal with challenges faced when using learning and adaptation methods to solve academic and industrial problems, such as optimization in dynamic environments with single and multiple agents, convergence and performance analysis, and online implementation. They explore means by which these difficulties can be solved, and cover a wide range of related topics including: deep learning; artificial intelligence; applications of game theory; mixed modality learning; and multi-agent reinforcement learning. Practicing engineers and scholars in the field of machine learning, game theory, and autonomous control will find the Handbook of Reinforcement Learning and Control to be thought-provoking, instructive and informative.

This book examines how face recognition technology is affecting privacy and confidentiality in an era of enhanced surveillance. Further, it offers a new approach to the complex issues of privacy and confidentiality, by drawing on Joseph K in Kafka's disturbing novel The Trial, and on Isaiah Berlin's notion of liberty and freedom. Taking into consideration rights and wrongs, protection from harm associated with compulsory visibility, and the need for effective data protection law, the author promotes ethical practices by reinterpreting privacy as a property right. To protect this right, the author advocates the licensing of personal identifiable images where appropriate. The book reviews American, UK and European case law concerning privacy and confidentiality, the effect each case has had on the developing jurisprudence, and the ethical issues involved. As such, it offers a valuable resource for students of ethico-legal fields, professionals specialising in image rights law, policy-makers, and liberty advocates and activists.

What if you could peer into the minds of an entire population? What if you could target the weakest with rumours that only they saw?

In 2016, an obscure British military contractor turned the world upside down. Funded by a billionaire on a crusade to start his own far-right insurgency, Cambridge Analytica combined psychological research with private Facebook data to make an invisible weapon with the power to change what voters perceived as real.

The firm was created to launch the then unknown Steve Bannon's ideological assault on America. But as it honed its dark arts in elections from Trinidad to Nigeria, 24-year-old research director Christopher Wylie began to see what he and his colleagues were unleashing.

He had heard the disturbing visions of the investors. He saw what CEO Alexander Nix did behind closed doors. When Britain shocked the world by voting to leave the EU, Wylie realised it was time to expose his old associates. The political crime of the century had just taken place - the weapon had been tested - and nobody knew.

This book presents the data privacy protection which has been extensively applied in our current era of big data. However, research into big data privacy is still in its infancy. Given the fact that existing protection methods can result in low data utility and unbalanced trade-offs, personalized privacy protection has become a rapidly expanding research topic.In this book, the authors explore emerging threats and existing privacy protection methods, and discuss in detail both the advantages and disadvantages of personalized privacy protection. Traditional methods, such as differential privacy and cryptography, are discussed using a comparative and intersectional approach, and are contrasted with emerging methods like federated learning and generative adversarial nets. The advances discussed cover various applications, e.g. cyber-physical systems, social networks, and location-based services. Given its scope, the book is of interest to scientists, policy-makers, researchers, and postgraduates alike.

The CCPA (California Consumer Privacy Act) is a data privacy law that took effect on January 1, 2020. It applied to businesses that collect California residents' personal information, and its privacy requirements are similar to those of the GDPR (General Data Protection Regulation). On May 4, 2020, Californians for Consumer Privacy (an advocacy group, founded by Alistair MacTaggart) announced that it had collected more than 900,000 signatures to qualify the CPRA (California Privacy Rights Act) for the November 2020 ballot. Also known as 'CCPA 2.0', the CPRA enhances privacy protections established by the CCPA and builds on consumer rights. CPRA effectively replaces the CCPA and bolsters privacy protections for California consumers. While many elements of the two laws are similar, there are some striking differences that could impact CPRA implementation plans, including: Limiting deletion rights that apply to unstructured data A new right to data minimization with retention requirements related to personal data New definitions and obligations related to cross-context behavioral advertising Amending breach liability to include an email address in combination with a password or security question Establishing a new regulatory enforcement body: the California Privacy Protection Agency Organizations that fail to comply with the CPRA's requirements are subject to civil penalties of up to $7,500 and a civil suit that gives every affected consumer the right to seek between $100 and $750 in damages per incident, or actual damages if higher. The law is complex and requires careful reading to understand the actual requirements for organizations - The California Privacy Rights Act - An implementation and compliance guide is here to help you. Ensure your business is CPRA compliant with essential guidanceThis book is your ideal resource for understanding the CPRA and how you can implement a strategy to ensure your organization complies with the legislation. It will give you a comprehensive understanding of the legislation by providing definitions of key terms, explanations of the security requirements, details of the breach notification procedure, and covering the penalties for noncompliance. The California Privacy Rights Act - An implementation and compliance guide is essential reading for anyone with business interests in the state of California. Not only does it serve as an introduction to the legislation, it also discusses the challenges a business may face when trying to achieve CPRA compliance. It gives you the confidence to begin your CPRA compliance journey, while highlighting the potential ongoing developments of the CPRA. Buy this book and start implementing your CPRA compliance strategy today!

The subjects of this volume are more relevant than ever, especially in light of the raft of electoral scandals concerning voter profiling. This volume brings together papers that offer conceptual analyses, highlight issues, propose solutions, and discuss practices regarding privacy and data protection. It is one of the results of the twelfth annual International Conference on Computers, Privacy and Data Protection, CPDP, held in Brussels in January 2019. The book explores the following topics: dataset nutrition labels, lifelogging and privacy by design, data protection iconography, the substance and essence of the right to data protection, public registers and data protection, modelling and verification in data protection impact assessments, examination scripts and data protection law in Cameroon, the protection of children's digital rights in the GDPR, the concept of the scope of risk in the GDPR and the ePrivacy Regulation. This interdisciplinary book has been written at a time when the scale and impact of data processing on society - not only on individuals, but also on social systems - is becoming ever starker. It discusses open issues as well as daring and prospective approaches, and will serve as an insightful resource for readers with an interest in computers, privacy and data protection.