Glossary on Statistical Disclosure Control PDF Download
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Author: Mark Elliot
Publisher:
ISBN:
Category : Confidential business information
Languages : en
Pages : 15
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Book Description
Author: Mark Elliot
Publisher:
ISBN:
Category : Confidential business information
Languages : en
Pages : 15
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Book Description
Author: Anco Hundepool
Publisher: John Wiley & Sons
ISBN: 1118348214
Category : Mathematics
Languages : en
Pages : 308
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Book Description
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.
Author: OECD
Publisher: OECD Publishing
ISBN: 9264055088
Category :
Languages : en
Pages : 605
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Book Description
The OECD Glossary contains a comprehensive set of over 6 700 definitions of key terminology, concepts and commonly used acronyms derived from existing international statistical guidelines and recommendations.
Author: Leon Willenborg
Publisher: Springer
ISBN: 9781461301226
Category :
Languages : en
Pages : 284
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Book Description
Author: Duncan Geoffrey Smith
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
This work concerns the evaluation of statistical disclosure control risk by adopting the position of the data intruder. The underlying assertion is that risk metrics should be based on the actual inferences that an intruder can make. Ideally metrics would also take into account how sensitive the inferences would be, but that is subjective. A parallel theme is that of the knowledgeable data intruder; an intruder who has the technical skills to maximally exploit the information contained in released data. This also raises the issue of computational costs and the benefits of using good algorithms. A metric for attribution risk in tabular data is presented. It addresses the issue that most measures for tabular data are based on the risk of identification. The metric can also take into account assumed levels of intruder knowledge regarding the population, and it can be applied to both exact and perturbed collections of tables. An improved implementation of the Key Variable Mapping System (Elliot, et al., 2010) is presented. The problem is more precisely defined in terms of categorical variables rather than responses to survey questions. This allows much more efficient algorithms to be developed, leading to significant performance increases. The advantages and disadvantages of alternative matching strategies are investigated. Some are shown to dominate others. The costs of searching for a match are also considered, providing insight into how a knowledgeable intruder might tailor a strategy to balance the probability of a correct match and the time and effort required to find a match. A novel approach to model determination in decomposable graphical models is described. It offers purely computational advantages over existing schemes, but allows data sets to be more thoroughly checked for disclosure risk. It is shown that a Bayesian strategy for matching between a sample and a population offers much higher probabilities of a correct match than traditional strategies would suggest. The Special Uniques Detection Algorithm (Elliot et al., 2002) (Manning et al., 2008), for identifying risky sample counts of 1, is compared against Bayesian (using Markov Chain Monte Carlo and simulated annealing) alternatives. It is shown that the alternatives are better at identifying risky sample uniques, and can do so with reduced computational costs.
Author: United States. Federal Committee on Statistical Methodology. Subcommittee on Disclosure-Avoidance Techniques
Publisher:
ISBN:
Category : Government information
Languages : en
Pages : 84
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Book Description
Author: Matthias Templ
Publisher: Springer
ISBN: 3319502727
Category : Social Science
Languages : en
Pages : 299
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Book Description
This book on statistical disclosure control presents the theory, applications and software implementation of the traditional approach to (micro)data anonymization, including data perturbation methods, disclosure risk, data utility, information loss and methods for simulating synthetic data. Introducing readers to the R packages sdcMicro and simPop, the book also features numerous examples and exercises with solutions, as well as case studies with real-world data, accompanied by the underlying R code to allow readers to reproduce all results. The demand for and volume of data from surveys, registers or other sources containing sensible information on persons or enterprises have increased significantly over the last several years. At the same time, privacy protection principles and regulations have imposed restrictions on the access and use of individual data. Proper and secure microdata dissemination calls for the application of statistical disclosure control methods to the da ta before release. This book is intended for practitioners at statistical agencies and other national and international organizations that deal with confidential data. It will also be interesting for researchers working in statistical disclosure control and the health sciences.
Author: Gregory J. Matthews
Publisher:
ISBN:
Category :
Languages : en
Pages : 288
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Book Description
Author: Gregory J. Matthews
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 48
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Book Description
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.
Author: Vicenç Torra
Publisher: Springer Nature
ISBN: 3031128370
Category : Computers
Languages : en
Pages : 323
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Book Description
Data privacy technologies are essential for implementing information systems with privacy by design. Privacy technologies clearly are needed for ensuring that data does not lead to disclosure, but also that statistics or even data-driven machine learning models do not lead to disclosure. For example, can a deep-learning model be attacked to discover that sensitive data has been used for its training? This accessible textbook presents privacy models, computational definitions of privacy, and methods to implement them. Additionally, the book explains and gives plentiful examples of how to implement—among other models—differential privacy, k-anonymity, and secure multiparty computation. Topics and features: Provides integrated presentation of data privacy (including tools from statistical disclosure control, privacy-preserving data mining, and privacy for communications) Discusses privacy requirements and tools for different types of scenarios, including privacy for data, for computations, and for users Offers characterization of privacy models, comparing their differences, advantages, and disadvantages Describes some of the most relevant algorithms to implement privacy models Includes examples of data protection mechanisms This unique textbook/guide contains numerous examples and succinctly and comprehensively gathers the relevant information. As such, it will be eminently suitable for undergraduate and graduate students interested in data privacy, as well as professionals wanting a concise overview. Vicenç Torra is Professor with the Department of Computing Science at Umeå University, Umeå, Sweden.
