Statistical Data Privacy Methods For Increasing Research Opportunities
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Statistical Data Privacy Methods For Increasing Research Opportunities
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Author : Joshua Snoke
language : en
Publisher:
Release Date : 2018
Statistical Data Privacy Methods For Increasing Research Opportunities written by Joshua Snoke and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
In this dissertation, we develop statistical methods for providing access to sensitive data, with the goal of simultaneously protecting individuals privacy and enabling high quality research. In addition to the theoretical contributions we provide to the area of statistical data privacy, our work is motivated by collaborations with practitioners and real policy problems, and as such is meant to be highly practical and easy to implement. We present two alternative paradigms for providing researchers access to sensitive data that build on ideas from statistical disclosure control (SDC) methodology, and techniques of secure multiparty computation (SMPC) and differential privacy (DP) from computer science.First, under the SMPC framework we develop an algorithm for computing secure maximum likelihood estimates (MLE) over partitioned databases without sharing any data or intermediate statistics. This is motivated by the scenario where different entities (or individuals) hold separate partitions of data, and researchers wish to obtain model estimates or statistics utilizing all the data which cannot be combined. We show that under a certain set of assumptions our method for estimation across these partitions achieves identical results as estimation with the full data but without violating privacy. We demonstrate the utility of the algorithm through the simulations and estimation of structural equation models with real data, and point out that is more widely applicable to factor models, linear regression, and PCA.Second, we provide new theoretical results for the utility evaluation of synthetic data based on its distributional similarity to the original data. The release of synthetic data is motivated by the desire for researchers to have downloadable microdata which they can use for exploration and model testing but that do not violate privacy. We derive new theoretical results for the propensity score mean-squared-error (pMSE) utility measure, and demonstrate how its use can improve on the choice of synthetic data models. We further combine the pMSE with differentially private methodology to produce synthetic data that maximize distributional similarity under the constraints of epsilon-DP. This ensures that we not only release synthetic data that others high utility, but it also guarantees quantifiable and provable privacy protections for the individuals in the data.
Expanding Access To Research Data
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 2005-12-11
Expanding Access To Research Data written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-12-11 with Computers categories.
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.
Federal Statistics Multiple Data Sources And Privacy Protection
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Author : National Academies of Sciences, Engineering, and Medicine
language : en
Publisher: National Academies Press
Release Date : 2018-01-27
Federal Statistics Multiple Data Sources And Privacy Protection written by National Academies of Sciences, Engineering, and Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-27 with Social Science categories.
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.
Innovations In Federal Statistics
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Author : National Academies of Sciences, Engineering, and Medicine
language : en
Publisher: National Academies Press
Release Date : 2017-04-21
Innovations In Federal Statistics written by National Academies of Sciences, Engineering, and Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-21 with Social Science categories.
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.
Improving Access To And Confidentiality Of Research Data
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 2000-08-11
Improving Access To And Confidentiality Of Research Data written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-08-11 with Social Science categories.
Improving Access to and Confidentiality of Research Data summarizes a workshop convened by the Committee on National Statistics (CNSTAT) to promote discussion about methods for advancing the often conflicting goals of exploiting the research potential of microdata and maintaining acceptable levels of confidentiality. This report outlines essential themes of the access versus confidentiality debate that emerged during the workshop. Among these themes are the tradeoffs and tensions between the needs of researchers and other data users on the one hand and confidentiality requirements on the other; the relative advantages and costs of data perturbation techniques (applied to facilitate public release) versus restricted access as tools for improving security; and the need to quantify disclosure risksâ€"both absolute and relativeâ€"created by researchers and research data, as well as by other data users and other types of data.
Data Confidentiality A Review Of Methods For Statistical Disclosure Limitation And Methods For Assessing Privacy
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Author : Gregory J. Matthews
language : en
Publisher:
Release Date : 2010
Data Confidentiality A Review Of Methods For Statistical Disclosure Limitation And Methods For Assessing Privacy written by Gregory J. Matthews and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Mathematical statistics categories.
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.
Statistical Methods In E Commerce Research
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Author : Wolfgang Jank
language : en
Publisher: John Wiley & Sons
Release Date : 2008-12-29
Statistical Methods In E Commerce Research written by Wolfgang Jank and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-29 with Mathematics categories.
This groundbreaking book introduces the application of statistical methodologies to e-Commerce data With the expanding presence of technology in today's economic market, the use of the Internet for buying, selling, and investing is growing more popular and public in nature. Statistical Methods in e-Commerce Research is the first book of its kind to focus on the statistical models and methods that are essential in order to analyze information from electronic-commerce (e-Commerce) transactions, identify the challenges that arise with new e-Commerce data structures, and discover new knowledge about consumer activity. This collection gathers over thirty researchers and practitioners from the fields of statistics, computer science, information systems, and marketing to discuss the growing use of statistical methods in e-Commerce research. From privacy protection to economic impact, the book first identifies the many obstacles that are encountered while collecting, cleaning, exploring, and analyzing e-Commerce data. Solutions to these problems are then suggested using established and newly developed statistical and data mining methods. Finally, a look into the future of this evolving area of study is provided through an in-depth discussion of the emerging methods for conducting e-Commerce research. Statistical Methods in e-Commerce Research successfully bridges the gap between statistics and e-Commerce, introducing a statistical approach to solving challenges that arise in the context of online transactions, while also introducing a wide range of e-Commerce applications and problems where novel statistical methodology is warranted. It is an ideal text for courses on e-Commerce at the upper-undergraduate and graduate levels and also serves as a valuable reference for researchers and analysts across a wide array of subject areas, including economics, marketing, and information systems who would like to gain a deeper understanding of the use of statistics in their work.
Privacy In Statistical Databases
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Author : Josep Domingo-Ferrer
language : en
Publisher: Springer
Release Date : 2004-06-30
Privacy In Statistical Databases written by Josep Domingo-Ferrer and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-06-30 with Computers categories.
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.
Privacy In Location Based Applications
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Author : Claudio Bettini
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-07-30
Privacy In Location Based Applications written by Claudio Bettini and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-30 with Computers categories.
Location-based applications refer to those that use location data in a prominent manner. Location data can be very effective for service provisioning, enabling the birth of a new generation of information services. Although data security and privacy issues have been extensively investigated in several domains, current techniques are not readily applicable to location-based applications. Conciliating the effectiveness of these applications with privacy concerns constitutes a unique challenge, mostly due to the semantic richness of location and time information. Research in this field involves aspects of spatio-temporal reasoning, query processing, system security, statistical inference, and more importantly, anonymization techniques. Several research groups have been working in recent years to identify privacy attacks and defense techniques in this domain. This state-of-the-art survey provides a solid ground for researchers approaching this topic to understand current achievements through a common categorization of privacy threats and defense techniques. This objective is particularly challenging considering the specific (and often implicit) assumptions that characterize the recent literature on privacy in location-based services. The book also illustrates the many facets that make the study of this topic a particularly interesting research subject, including topics that go beyond privacy preserving transformations of service requests, and include access control, privacy preserving publishing of moving object data, privacy in the use of specific positioning technology, and privacy in vehicular network applications.
Confidentiality Of Research And Statistical Data
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Author : United States. Law Enforcement Assistance Administration
language : en
Publisher:
Release Date : 1979
Confidentiality Of Research And Statistical Data written by United States. Law Enforcement Assistance Administration and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1979 with Confidential communications categories.