This book presents the latest research on the challenges and solutions affecting the equilibrium between freedom of speech, freedom of information, information security and the right to informational privacy. Given the complexity of the topics addressed, the book shows how old legal and ethical frameworks may need to be not only updated, but also supplemented and complemented by new conceptual solutions. Neither a conservative attitude (“more of the same”) nor a revolutionary zeal (“never seen before”) is likely to lead to satisfactory solutions. Instead, more reflection and better conceptual design are needed, not least to harmonise different perspectives and legal frameworks internationally. The focus of the book is on how we may reconcile high levels of information security with robust degrees of informational privacy, also in connection with recent challenges presented by phenomena such as “big data” and security scandals, as well as new legislation initiatives, such as those concerning “the right to be forgotten” and the use of personal data in biomedical research. The book seeks to offer analyses and solutions of the new tensions, in order to build a fair, shareable and sustainable balance in this vital area of human interactions.

Reproduction of the original: The Right to Privacy by Samuel D. Warren, Louis D. Brandeis

Examines how copyright can evolve without compromising the interests of authors, users and those who connect them.

Federica Giovanella examines the on-going conflict between copyright and informational privacy rights within the judicial system in this timely and intriguing book.

Posner uses economic analysis to probe justice and efficiency, primitive law, privacy, and the constitutional regulation of racial discrimination.

The book provides in-depth insight to scholars, practitioners, and activists dealing with human rights, their expansion, and the emergence of 'new' human rights. Whereas legal theory tends to neglect the development of concrete individual rights, monographs on 'new' rights often deal with structural matters only in passing and the issue of 'new' human rights has received only cursory attention in literature. By bringing together a large number of emergent human rights, analysed by renowned human rights experts from around the world, and combining the analyses with theoretical approaches, this book fills this lacuna. The comprehensive and dialectic approach, which enables insights from individual rights to overarching theory and vice versa, will ensure knowledge growth for generalists and specialists alike. The volume goes beyond a purely legal analysis by observing the contestation, rhetorics, the struggle for recognition of 'new' human rights, thus speaking to human rights professionals beyond the legal sphere.

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.