An expert on computer privacy and security shows how we can build privacy into the design of systems from the start. We are tethered to our devices all day, every day, leaving data trails of our searches, posts, clicks, and communications. Meanwhile, governments and businesses collect our data and use it to monitor us without our knowledge. So we have resigned ourselves to the belief that privacy is hard--choosing to believe that websites do not share our information, for example, and declaring that we have nothing to hide anyway. In this informative and illuminating book, a computer privacy and security expert argues that privacy is not that hard if we build it into the design of systems from the start. Along the way, Jaap-Henk Hoepman debunks eight persistent myths surrounding computer privacy. The website that claims it doesn't collect personal data, for example; Hoepman explains that most data is personal, capturing location, preferences, and other information. You don't have anything to hide? There's nothing wrong with wanting to keep personal information--even if it's not incriminating or embarrassing--private. Hoepman shows that just as technology can be used to invade our privacy, it can be used to protect it, when we apply privacy by design. Hoepman suggests technical fixes, discussing pseudonyms, leaky design, encryption, metadata, and the benefits of keeping your data local (on your own device only), and outlines privacy design strategies that system designers can apply now.

The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology enables ever more powerful collection and curation of these data, the need increases for a robust, meaningful, and mathematically rigorous definition of privacy, together with a computationally rich class of algorithms that satisfy this definition. Differential Privacy is such a definition. The Algorithmic Foundations of Differential Privacy starts out by motivating and discussing the meaning of differential privacy, and proceeds to explore the fundamental techniques for achieving differential privacy, and the application of these techniques in creative combinations, using the query-release problem as an ongoing example. A key point is that, by rethinking the computational goal, one can often obtain far better results than would be achieved by methodically replacing each step of a non-private computation with a differentially private implementation. Despite some powerful computational results, there are still fundamental limitations. Virtually all the algorithms discussed herein maintain differential privacy against adversaries of arbitrary computational power -- certain algorithms are computationally intensive, others are efficient. Computational complexity for the adversary and the algorithm are both discussed. The monograph then turns from fundamentals to applications other than query-release, discussing differentially private methods for mechanism design and machine learning. The vast majority of the literature on differentially private algorithms considers a single, static, database that is subject to many analyses. Differential privacy in other models, including distributed databases and computations on data streams, is discussed. The Algorithmic Foundations of Differential Privacy is meant as a thorough introduction to the problems and techniques of differential privacy, and is an invaluable reference for anyone with an interest in the topic.

American essayist and Harper's contributing editor Garret Keizer offers a brilliant, literate look at our strip-searched, over-shared, viral-videoed existence. Body scans at the airport, candid pics on Facebook, a Twitter account for your stray thoughts, and a surveillance camera on every street corner -- today we have an audience for all of the extraordinary and banal events of our lives. The threshold between privacy and exposure becomes more permeable by the minute. But what happens to our private selves when we cannot escape scrutiny, and to our public personas when they pass from our control? In this wide-ranging, penetrating addition to the Big Ideas//Small Books series, and in his own unmistakable voice, Garret Keizer considers the moral dimensions of privacy in relation to issues of social justice, economic inequality, and the increasing commoditization of the global marketplace. Though acutely aware of the digital threat to privacy rights, Keizer refuses to see privacy in purely technological terms or as an essentially legalistic value. Instead, he locates privacy in the human capacity for resistance and in the sustainable society "with liberty and justice for all."

The threats to privacy are well known: the National Security Agency tracks our phone calls; Google records where we go online and how we set our thermostats; Facebook changes our privacy settings when it wishes; Target gets hacked and loses control of our credit card information; our medical records are available for sale to strangers; our children are fingerprinted and their every test score saved for posterity; and small robots patrol our schoolyards and drones may soon fill our skies. The contributors to this anthology don't simply describe these problems or warn about the loss of privacy—they propose solutions. They look closely at business practices, public policy, and technology design, and ask, “Should this continue? Is there a better approach?” They take seriously the dictum of Thomas Edison: “What one creates with his hand, he should control with his head.” It's a new approach to the privacy debate, one that assumes privacy is worth protecting, that there are solutions to be found, and that the future is not yet known. This volume will be an essential reference for policy makers and researchers, journalists and scholars, and others looking for answers to one of the biggest challenges of our modern day. The premise is clear: there's a problem—let's find a solution.

The information revolution has brought with it the technology for easily collecting personal information about individuals, a facility that inherently threatens personal privacy. Colin J. Bennett here examines political responses to the data protection issue in four Western democracies, comparing legislation that the United States, Britain, West Germany, and Sweden forged from the late 1960's to the 1980's to protect citizens from unwanted computer dissemination of personal information. Drawing on an extensive body of interviews and documentary evidence, Bennett considers how the four countries, each with different cultural traditions and institutions, formulated fair information policy. He finds that their computer regulatory laws are based on strikingly similar statutory principles, but that enforcement of these principles varies considerably: the United States relies on citizen initiative and judicial enforcement; Britain uses a registration system; Germany has installed an ombudsman; and Sweden employs a licensing system. Tracing the impact of key social, political, and technological factors on the ways different political systems have controlled the collection and communication of information, Bennett also deepens our understanding of policymaking theory. Regulating Privacy will be welcomed by political sciences--especially those working in comparative public policy, American politics, organization theory, and technology and politics--political economists, information systems analysts, and others concerned with issues of privacy.

Limited legal protections for privacy leave minority communities vulnerable to concrete injuries and violence when their information is exposed. In Privacy at the Margins, Scott Skinner-Thompson highlights why privacy is of acute importance for marginalized groups. He explains how privacy can serve as a form of expressive resistance to government and corporate surveillance regimes - furthering equality goals - and demonstrates why efforts undertaken by vulnerable groups (queer folks, women, and racial and religious minorities) to protect their privacy should be entitled to constitutional protection under the First Amendment and related equality provisions. By examining the ways even limited privacy can enrich and enhance our lives at the margins in material ways, this work shows how privacy can be transformed from a liberal affectation to a legal tool of liberation from oppression.

Privacy is one of the most important concepts of our time, yet it is also one of the most elusive. As rapidly changing technology makes information increasingly available, scholars, activists, and policymakers have struggled to define privacy, with many conceding that the task is virtually impossible. In this concise and lucid book, Daniel J. Solove offers a comprehensive overview of the difficulties involved in discussions of privacy and ultimately provides a provocative resolution. He argues that no single definition can be workable, but rather that there are multiple forms of privacy, related to one another by family resemblances. His theory bridges cultural differences and addresses historical changes in views on privacy. Drawing on a broad array of interdisciplinary sources, Solove sets forth a framework for understanding privacy that provides clear, practical guidance for engaging with relevant issues. Understanding Privacy will be an essential introduction to long-standing debates and an invaluable resource for crafting laws and policies about surveillance, data mining, identity theft, state involvement in reproductive and marital decisions, and other pressing contemporary matters concerning privacy.