Statistical Confidentiality

Because statistical confidentiality embraces the responsibility for both protecting data and ensuring its beneficial use for statistical purposes, those working with personal and proprietary data can benefit from the principles and practices this book presents. Researchers can understand why an agency holding statistical data does not respond well to the demand, “Just give me the data; I’m only going to do good things with it.” Statisticians can incorporate the requirements of statistical confidentiality into their methodologies for data collection and analysis. Data stewards, caught between those eager for data and those who worry about confidentiality, can use the tools of statistical confidentiality toward satisfying both groups. The eight chapters lay out the dilemma of data stewardship organizations (such as statistical agencies) in resolving the tension between protecting data from snoopers while providing data to legitimate users, explain disclosure risk and explore the types of attack that a data snooper might mount, present the methods of disclosure risk assessment, give techniques for statistical disclosure limitation of both tabular data and microdata, identify measures of the impact of disclosure limitation on data utility, provide restricted access methods as administrative procedures for disclosure control, and finally explore the future of statistical confidentiality.

A reference to answer all your statistical confidentiality questions. This handbook provides technical guidance on statistical disclosure control and on how to approach the problem of balancing the need to provide users with statistical outputs and the need to protect the confidentiality of respondents. Statistical disclosure control is combined with other tools such as administrative, legal and IT in order to define a proper data dissemination strategy based on a risk management approach. The key concepts of statistical disclosure control are presented, along with the methodology and software that can be used to apply various methods of statistical disclosure control. Numerous examples and guidelines are also featured to illustrate the topics covered. Statistical Disclosure Control: Presents a combination of both theoretical and practical solutions Introduces all the key concepts and definitions involved with statistical disclosure control. Provides a high level overview of how to approach problems associated with confidentiality. Provides a broad-ranging review of the methods available to control disclosure. Explains the subtleties of group disclosure control. Features examples throughout the book along with case studies demonstrating how particular methods are used. Discusses microdata, magnitude and frequency tabular data, and remote access issues. Written by experts within leading National Statistical Institutes. Official statisticians, academics and market researchers who need to be informed and make decisions on disclosure limitation will benefit from this book.

These guidelines have been prepared a Task Force set up by the Conference of European Statisticians, with two main objectives.- The first is to foster greater uniformity of approach by countries to allow better access to microdata for the research community. The second is to produce guidelines and supporting case studies, which will help countries improve their arrangements for providing access to microdata.

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.

Statistical disclosure control is the discipline that deals with producing statistical data that are safe enough to be released to external researchers. This book concentrates on the methodology of the area. It deals with both microdata (individual data) and tabular (aggregated) data. The book attempts to develop the theory from what can be called the paradigm of statistical confidentiality: to modify unsafe data in such a way that safe (enough) data emerge, with minimum information loss. This book discusses what safe data, are, how information loss can be measured, and how to modify the data in a (near) optimal way. Once it has been decided how to measure safety and information loss, the production of safe data from unsafe data is often a matter of solving an optimization problem. Several such problems are discussed in the book, and most of them turn out to be hard problems that can be solved only approximately. The authors present new results that have not been published before. The book is not a description of an area that is closed, but, on the contrary, one that still has many spots awaiting to be more fully explored. Some of these are indicated in the book. The book will be useful for official, social and medical statisticians and others who are involved in releasing personal or business data for statistical use. Operations researchers may be interested in the optimization problems involved, particularly for the challenges they present. Leon Willenborg has worked at the Department of Statistical Methods at Statistics Netherlands since 1983, first as a researcher and since 1989 as a senior researcher. Since 1989 his main field of research and consultancy has been statistical disclosure control. From 1996-1998 he was the project coordinator of the EU co-funded SDC project.

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.

Report on data protection and confidentiality issues concerning the CHSS health statistical service of the USA - outlines the environment that conditions privacy and access to information, discusses legislation regarding data bases and file linking, etc., and includes recommendations. Bibliography pp. 49 and 50.

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.