Download or read book The Fundamental Limits of Statistical Data Privacy written by Peter Kairouz and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Innovations in Federal Statistics written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2017-04-21 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: Federal government statistics provide critical information to the country and serve a key role in a democracy. For decades, sample surveys with instruments carefully designed for particular data needs have been one of the primary methods for collecting data for federal statistics. However, the costs of conducting such surveys have been increasing while response rates have been declining, and many surveys are not able to fulfill growing demands for more timely information and for more detailed information at state and local levels. Innovations in Federal Statistics examines the opportunities and risks of using government administrative and private sector data sources to foster a paradigm shift in federal statistical programs that would combine diverse data sources in a secure manner to enhance federal statistics. This first publication of a two-part series discusses the challenges faced by the federal statistical system and the foundational elements needed for a new paradigm.
Download or read book The Algorithmic Foundations of Differential Privacy written by Cynthia Dwork and published by . This book was released on 2014 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Private Lives and Public Policies written by National Research Council and published by National Academies Press. This book was released on 1993-01-01 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Americans are increasingly concerned about the privacy of personal dataâ€"yet we demand more and more information for public decision making. This volume explores the seeming conflicts between privacy and data access, an issue of concern to federal statistical agencies collecting the data, research organizations using the data, and individuals providing the data. A panel of experts offers principles and specific recommendations for managing data and improving the balance between needed government use of data and the privacy of respondents. The volume examines factors such as the growth of computer technology, that are making confidentiality an increasingly critical problem. The volume explores how data collectors communicate with data providers, with a focus on informed consent to use data, and describes the legal and ethical obligations data users have toward individual subjects as well as toward the agencies providing the data. In the context of historical practices in the United States, Canada, and Sweden, statistical techniques for protecting individuals' identities are evaluated in detail. Legislative and regulatory restraints on access to data are examined, including a discussion about their effects on research. This volume will be an important and thought-provoking guide for policymakers and agencies working with statistics as well as researchers and concerned individuals.
Download or read book The Ethical Algorithm written by Michael Kearns and published by Oxford University Press. This book was released on 2019-10-04 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the course of a generation, algorithms have gone from mathematical abstractions to powerful mediators of daily life. Algorithms have made our lives more efficient, more entertaining, and, sometimes, better informed. At the same time, complex algorithms are increasingly violating the basic rights of individual citizens. Allegedly anonymized datasets routinely leak our most sensitive personal information; statistical models for everything from mortgages to college admissions reflect racial and gender bias. Meanwhile, users manipulate algorithms to "game" search engines, spam filters, online reviewing services, and navigation apps. Understanding and improving the science behind the algorithms that run our lives is rapidly becoming one of the most pressing issues of this century. Traditional fixes, such as laws, regulations and watchdog groups, have proven woefully inadequate. Reporting from the cutting edge of scientific research, The Ethical Algorithm offers a new approach: a set of principled solutions based on the emerging and exciting science of socially aware algorithm design. Michael Kearns and Aaron Roth explain how we can better embed human principles into machine code - without halting the advance of data-driven scientific exploration. Weaving together innovative research with stories of citizens, scientists, and activists on the front lines, The Ethical Algorithm offers a compelling vision for a future, one in which we can better protect humans from the unintended impacts of algorithms while continuing to inspire wondrous advances in technology.
Download or read book Confidentiality Disclosure and Data Access written by Pat Doyle and published by Elsevier Science & Technology. This book was released on 2001 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a fundamental tension at the heart of every statistical agency mission. Each is charged with collecting high quality data to inform the national policy and enable statistical research. This necessitates dissemination of both summary and micro data. Each is also charged with protecting the confidentiality of survey respondents. This often necessitates the blurring of the data to reduce the probability of the re-identification of individuals. The tradeoff dilemma, which could well be stated as protecting confidentiality (avoiding disclosure) but optimizing access, has become more complex as both technological advances and public perceptions have altered in an information age. Fortunately, statistical disclosure techniques have kept pace with these changes. This volume is intended to provide a review of new state of the art techniques that directly address these issues from both a theoretical and practical perspective. It provides a review of new research in the area of confidentiality and statistical disclosure techniques. A major section of the book provides an overview of new advances in the field of both economic and demographic data in measuring disclosure risk and information loss. It also presents new information on the different approaches taken by statistical agencies in disseminating data - ranging from licensing agreements , to secure access and provides a new survey of what statistical disclosure techniques are used by statistical agencies around the world. This is complimented by a series of chapters on public perceptions of statistical agency actions, including the results of a new survey on business perceptions. The book concludes with a chapter on the challenges of technology to data protection. National Statistical Agencies, statistical practitioners, thinktanks, research organisations and universities will find this a useful tool.
Download or read book Information Security written by Zhiqiang Lin and published by Springer Nature. This book was released on 2019-09-02 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 22nd International Conference on Information Security, ISC 2019, held in New York City, NY, USA, in September 2019. The 23 full papers presented in this volume were carefully reviewed and selected from 86 submissions. The papers were organized in topical sections named: Attacks and Cryptanalysis; Crypto I: Secure Computation and Storage; Machine Learning and Security; Crypto II: Zero-Knowledge Proofs; Defenses; Web Security; Side Channels; Malware Analysis; Crypto III: Signatures and Authentication.
Download or read book Concentration of Maxima and Fundamental Limits in High Dimensional Testing and Inference written by Zheng Gao and published by Springer. This book was released on 2021-09-08 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a unified exposition of some fundamental theoretical problems in high-dimensional statistics. It specifically considers the canonical problems of detection and support estimation for sparse signals observed with noise. Novel phase-transition results are obtained for the signal support estimation problem under a variety of statistical risks. Based on a surprising connection to a concentration of maxima probabilistic phenomenon, the authors obtain a complete characterization of the exact support recovery problem for thresholding estimators under dependent errors.
Download or read book Federal Statistics Multiple Data Sources and Privacy Protection written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-01-27 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.
Download or read book Protecting Individuals Against the Negative Impact of Big Data written by Manon Oostveen and published by Kluwer Law International B.V.. This book was released on 2018-07-13 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the contemporary information society, organisations increasingly rely on the collection and analysis of large-scale data (popularly called ‘big data’) to make decisions. These processes, which take place largely beyond the individual’s knowledge, produce a cascade of effects that go beyond privacy and data protection. Should we focus on the possibilities of tackling these often negative effects through other areas of law, or maybe even find new solutions to cope with the dark side of big data? This ground-breaking book is the first to address this crucially important question in detail. Among the issues raised in the analysis are such vital elements as the following: − what is meant by ‘big data’; – ‘privacy’ according to the European Court of Human Rights and the Court of Justice of the European Union; – what the European Union legal framework on privacy and data protection consists of and how it functions in the light of big data; – what companies, governments and other organisations are permitted to do with big data under the current regulatory framework; – the central importance of personal autonomy; – circumstances that influence whether or not the right to privacy is triggered; – big data’s possible impact on democracy through, inter alia, potentially limiting freedom of expression; – how governmental or corporate surveillance chills the receiver’s gathering of information and ideas; – selective offering of choices or information, or manipulation of people’s ideas; – procedural aspects that influence the extrapolation of normative concepts of privacy and data protection; and – how discrimination occurs in big data. This book foregrounds a critical scrutiny of commercial uses of big data – its scale, its limited capacity for independent oversight and the expected prevalence of interference with individuals’ rights. The author’s conclusions explore possible legal alternatives to mitigate the negative impact of big data, using legal instruments, case law and legal academic literature in her analysis. Because the amount of digital data keeps growing and the private lives of individuals are increasingly taking place online – and because of the opacity of the big data process, the fundamental values that are at stake, and the speed of technological developments compared to the pace of legal reform – this comprehensive assessment of flaws in the current framework and possible practical solutions will be warmly welcomed by practitioners, policymakers and government officials in all legal fields related to privacy and data protection.
Download or read book Data Privacy Foundations New Developments and the Big Data Challenge written by Vicenç Torra and published by Springer. This book was released on 2017-05-17 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a broad, cohesive overview of the field of data privacy. It discusses, from a technological perspective, the problems and solutions of the three main communities working on data privacy: statistical disclosure control (those with a statistical background), privacy-preserving data mining (those working with data bases and data mining), and privacy-enhancing technologies (those involved in communications and security) communities. Presenting different approaches, the book describes alternative privacy models and disclosure risk measures as well as data protection procedures for respondent, holder and user privacy. It also discusses specific data privacy problems and solutions for readers who need to deal with big data.
Download or read book Data Confidentiality a Review of Methods for Statistical Disclosure Limitation and Methods for Assessing Privacy written by Gregory J. Matthews and published by . This book was released on 2010 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is an ever increasing demand from researchers for access to useful microdata files. However, there are also growing concerns regarding the privacy of the individuals contained in the microdata. Ideally, microdata could be released in such a way that a balance between usefulness of the data and privacy is struck. This paper presents a review of proposed methods of statistical disclosure control and techniques for assessing the privacy of such methods under different definitions of disclosure.
Download or read book Privacy in Statistical Databases written by Josep Domingo-Ferrer and published by Springer. This book was released on 2004-06-30 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Privacy in statistical databases is about ?nding tradeo?s to the tension between the increasing societal and economical demand for accurate information and the legal and ethical obligation to protect the privacy of individuals and enterprises, which are the source of the statistical data. Statistical agencies cannot expect to collect accurate information from individual or corporate respondents unless these feel the privacy of their responses is guaranteed; also, recent surveys of Web users show that a majority of these are unwilling to provide data to a Web site unless they know that privacy protection measures are in place. “Privacy in Statistical Databases2004” (PSD2004) was the ?nal conference of the CASC project (“Computational Aspects of Statistical Con?dentiality”, IST-2000-25069). PSD2004 is in the style of the following conferences: “Stat- tical Data Protection”, held in Lisbon in 1998 and with proceedings published by the O?ce of O?cial Publications of the EC, and also the AMRADS project SDC Workshop, held in Luxemburg in 2001 and with proceedings published by Springer-Verlag, as LNCS Vol. 2316. The Program Committee accepted 29 papers out of 44 submissions from 15 di?erentcountriesonfourcontinents.Eachsubmittedpaperreceivedatleasttwo reviews. These proceedings contain the revised versions of the accepted papers. These papers cover the foundations and methods of tabular data protection, masking methods for the protection of individual data (microdata), synthetic data generation, disclosure risk analysis, and software/case studies.
Download or read book Confidentiality of Research and Statistical Data written by United States. Law Enforcement Assistance Administration and published by . This book was released on 1979 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Expanding Access to Research Data written by National Research Council and published by National Academies Press. This book was released on 2005-12-11 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: Policy makers need information about the nationâ€"ranging from trends in the overall economy down to the use by individuals of Medicareâ€"in order to evaluate existing programs and to develop new ones. This information often comes from research based on data about individual people, households, and businesses and other organizations, collected by statistical agencies. The benefit of increasing data accessibility to researchers and analysts is better informed public policy. To realize this benefit, a variety of modes for data accessâ€" including restricted access to confidential data and unrestricted access to appropriately altered public-use dataâ€"must be used. The risk of expanded access to potentially sensitive data is the increased probability of breaching the confidentiality of the data and, in turn, eroding public confidence in the data collection enterprise. Indeed, the statistical system of the United States ultimately depends on the willingness of the public to provide the information on which research data are based. Expanding Access to Research Data issues guidance on how to more fully exploit these tradeoffs. The panel's recommendations focus on needs highlighted by legal, social, and technological changes that have occurred during the last decade.
Download or read book Information Privacy and Statistics written by Tore Dalenius and published by . This book was released on 1978 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Inference in the Differential Privacy Model written by Huanyu Zhang and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In modern settings of data analysis, we may be running our algorithms on datasets that are sensitive in nature. However, classical machine learning and statistical algorithms were not designed with these risks in mind, and it has been demonstrated that they may reveal personal information. These concerns disincentivize individuals from providing their data, or even worse, encouraging intentionally providing fake data. To assuage these concerns, we import the constraint of differential privacy to the statistical inference, considered by many to be the gold standard of data privacy. This thesis aims to quantify the cost of ensuring differential privacy, i.e., understanding how much additional data is required to perform data analysis with the constraint of differential privacy. Despite the maturity of the literature on differential privacy, there is still inadequate understanding in some of the most fundamental settings. In particular, we make progress in the following problems : *What is the sample complexity of DP hypothesis testing? *Can we privately estimate distribution properties with a negligible cost? *What is the fundamental limit in private distribution estimation? *How can we design algorithms to privately estimate random graphs? *What is the trade-off between the sample complexity and the interactivity in private hypothesis selection?
