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 book constitutes the thoroughly refereed post-proceedings of the 6th International Workshop on Privacy Enhancing Technologies, PET 2006, held in Cambridge, UK, in June 2006 co-located with WEIS 2006, the Workshop on the Economics of Information Security, and WOTE 2006, the IAVoSS Workshop On Trustworthy Elections. The 24 revised full papers present novel research on all theoretical and practical aspects of privacy technologies.

This open access book provides researchers and professionals with a foundational understanding of online privacy as well as insight into the socio-technical privacy issues that are most pertinent to modern information systems, covering several modern topics (e.g., privacy in social media, IoT) and underexplored areas (e.g., privacy accessibility, privacy for vulnerable populations, cross-cultural privacy). The book is structured in four parts, which follow after an introduction to privacy on both a technical and social level: Privacy Theory and Methods covers a range of theoretical lenses through which one can view the concept of privacy. The chapters in this part relate to modern privacy phenomena, thus emphasizing its relevance to our digital, networked lives. Next, Domains covers a number of areas in which privacy concerns and implications are particularly salient, including among others social media, healthcare, smart cities, wearable IT, and trackers. The Audiences section then highlights audiences that have traditionally been ignored when creating privacy-preserving experiences: people from other (non-Western) cultures, people with accessibility needs, adolescents, and people who are underrepresented in terms of their race, class, gender or sexual identity, religion or some combination. Finally, the chapters in Moving Forward outline approaches to privacy that move beyond one-size-fits-all solutions, explore ethical considerations, and describe the regulatory landscape that governs privacy through laws and policies. Perhaps even more so than the other chapters in this book, these chapters are forward-looking by using current personalized, ethical and legal approaches as a starting point for re-conceptualizations of privacy to serve the modern technological landscape. The book's primary goal is to inform IT students, researchers, and professionals about both the fundamentals of online privacy and the issues that are most pertinent to modern information systems. Lecturers or teachers can assign (parts of) the book for a “professional issues” course. IT professionals may select chapters covering domains and audiences relevant to their field of work, as well as the Moving Forward chapters that cover ethical and legal aspects. Academics who are interested in studying privacy or privacy-related topics will find a broad introduction in both technical and social aspects.

Anonymity and unobservability have become key issues in the context of securing privacy on the Internet and in other communication networks. Services that provide anonymous and unobservable access to the Internet are important for electronic commerce applications as well as for services where users want to remain anonymous. This book is devoted to the design and realization of anonymity services for the Internet and other communcation networks. The book offers topical sections on: attacks on systems, anonymous publishing, mix systems, identity management, pseudonyms and remailers. Besides nine technical papers, an introduction clarifying the terminology for this emerging area is presented as well as a survey article introducing the topic to a broader audience interested in security issues.

Over the last several years, the realm of technology and privacy has been transformed, creating a landscape that is both dangerous and encouraging. Significant changes include large increases in communications bandwidths; the widespread adoption of computer networking and public-key cryptography; new digital media that support a wide range of social relationships; a massive body of practical experience in the development and application of data-protection laws; and the rapid globalization of manufacturing, culture, and policy making. The essays in this book provide a new conceptual framework for the analysis and debate of privacy policy and for the design and development of information systems.

This book constitutes the thoroughly refereed post-proceedings of the Second International Workshop on Privacy Enhancing Technologies, PET 2002, held in San Francisco, CA, USA, in April 2002. The 17 revised full papers presented were carefully selected during two rounds of reviewing and improvement. Among the topics addressed are Internet security, private authentication, information theoretic anonymity, anonymity measuring, enterprise privacy practices, service architectures for privacy, intersection attacks, online trust negotiation, random data perturbation, Website fingerprinting, Web user privacy, TCP timestamps, private information retrieval, and unobservable Web surfing.

In the past four decades, information technology has altered chains of value production, distribution, and information access at a significant rate. These changes, although they have shaken up numerous economic models, have so far not radically challenged the bases of our society.This book addresses our current progress and viewpoints on digital identity management in different fields (social networks, cloud computing, Internet of Things (IoT), with input from experts in computer science, law, economics and sociology. Within this multidisciplinary and scientific context, having crossed analysis on the digital ID issue, it describes the different technical and legal approaches to protect digital identities with a focus on authentication systems, identity federation techniques and privacy preservation solutions. The limitations of these solutions and research issues in this field are also discussed to further understand the changes that are taking place. - Offers a state of the discussions and work places on the management of digital identities in various contexts, such as social networking, cloud computing and the Internet of Things - Describes the advanced technical and legal measures to protect digital identities - Contains a strong emphasis of authentication techniques, identity federation tools and technical protection of privacy

Keep sensitive user data safe and secure without sacrificing the performance and accuracy of your machine learning models. In Privacy Preserving Machine Learning, you will learn: Privacy considerations in machine learning Differential privacy techniques for machine learning Privacy-preserving synthetic data generation Privacy-enhancing technologies for data mining and database applications Compressive privacy for machine learning Privacy-Preserving Machine Learning is a comprehensive guide to avoiding data breaches in your machine learning projects. You’ll get to grips with modern privacy-enhancing techniques such as differential privacy, compressive privacy, and synthetic data generation. Based on years of DARPA-funded cybersecurity research, ML engineers of all skill levels will benefit from incorporating these privacy-preserving practices into their model development. By the time you’re done reading, you’ll be able to create machine learning systems that preserve user privacy without sacrificing data quality and model performance. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning applications need massive amounts of data. It’s up to you to keep the sensitive information in those data sets private and secure. Privacy preservation happens at every point in the ML process, from data collection and ingestion to model development and deployment. This practical book teaches you the skills you’ll need to secure your data pipelines end to end. About the Book Privacy-Preserving Machine Learning explores privacy preservation techniques through real-world use cases in facial recognition, cloud data storage, and more. You’ll learn about practical implementations you can deploy now, future privacy challenges, and how to adapt existing technologies to your needs. Your new skills build towards a complete security data platform project you’ll develop in the final chapter. What’s Inside Differential and compressive privacy techniques Privacy for frequency or mean estimation, naive Bayes classifier, and deep learning Privacy-preserving synthetic data generation Enhanced privacy for data mining and database applications About the Reader For machine learning engineers and developers. Examples in Python and Java. About the Author J. Morris Chang is a professor at the University of South Florida. His research projects have been funded by DARPA and the DoD. Di Zhuang is a security engineer at Snap Inc. Dumindu Samaraweera is an assistant research professor at the University of South Florida. The technical editor for this book, Wilko Henecka, is a senior software engineer at Ambiata where he builds privacy-preserving software. Table of Contents PART 1 - BASICS OF PRIVACY-PRESERVING MACHINE LEARNING WITH DIFFERENTIAL PRIVACY 1 Privacy considerations in machine learning 2 Differential privacy for machine learning 3 Advanced concepts of differential privacy for machine learning PART 2 - LOCAL DIFFERENTIAL PRIVACY AND SYNTHETIC DATA GENERATION 4 Local differential privacy for machine learning 5 Advanced LDP mechanisms for machine learning 6 Privacy-preserving synthetic data generation PART 3 - BUILDING PRIVACY-ASSURED MACHINE LEARNING APPLICATIONS 7 Privacy-preserving data mining techniques 8 Privacy-preserving data management and operations 9 Compressive privacy for machine learning 10 Putting it all together: Designing a privacy-enhanced platform (DataHub)

This open access book provides the first comprehensive collection of papers that provide an integrative view on cybersecurity. It discusses theories, problems and solutions on the relevant ethical issues involved. This work is sorely needed in a world where cybersecurity has become indispensable to protect trust and confidence in the digital infrastructure whilst respecting fundamental values like equality, fairness, freedom, or privacy. The book has a strong practical focus as it includes case studies outlining ethical issues in cybersecurity and presenting guidelines and other measures to tackle those issues. It is thus not only relevant for academics but also for practitioners in cybersecurity such as providers of security software, governmental CERTs or Chief Security Officers in companies.

This book constitutes the thoroughly refereed post-proceedings of the 7th International Symposium on Privacy Enhancing Technologies, PET 2007, held in conjunction with WOTE 2007, the IAVoSS Workshop on Trustworthy Elections. The papers cover design and realization of privacy services for the internet and other communication networks and present novel research on all theoretical and practical aspects of privacy technologies, as well as experimental studies of fielded systems.