Privacy In Statistical Databases
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| Author | : Josep Domingo-Ferrer |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 394 |
| Release | : 2006-11-27 |
| Genre | : Computers |
| ISBN | : 3540493301 |
This book constitutes the refereed proceedings of the International Conference on Privacy in Statistical Databases, PSD 2006, held in December 2006 in Rome, Italy. The 31 revised full papers are organized in topical sections on methods for tabular protection, utility and risk in tabular protection, methods for microdata protection, utility and risk in microdata protection, protocols for private computation, case studies, and software.
| Author | : Josep Domingo-Ferrer |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 308 |
| Release | : 2010-09-09 |
| Genre | : Computers |
| ISBN | : 3642158374 |
This book constitutes the proceedings of the International Conference on Privacy in Statistical Databases held in Corfu, Greece, in September 2010.
| Author | : Milan Petkovic |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 467 |
| Release | : 2007-06-12 |
| Genre | : Computers |
| ISBN | : 3540698612 |
The vision of ubiquitous computing and ambient intelligence describes a world of technology which is present anywhere, anytime in the form of smart, sensible devices that communicate with each other and provide personalized services. However, open interconnected systems are much more vulnerable to attacks and unauthorized data access. In the context of this threat, this book provides a comprehensive guide to security and privacy and trust in data management.
| Author | : Henk C.A. van Tilborg |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 1457 |
| Release | : 2014-07-08 |
| Genre | : Computers |
| ISBN | : 1441959068 |
Expanded into two volumes, the Second Edition of Springer’s Encyclopedia of Cryptography and Security brings the latest and most comprehensive coverage of the topic: Definitive information on cryptography and information security from highly regarded researchers Effective tool for professionals in many fields and researchers of all levels Extensive resource with more than 700 contributions in Second Edition 5643 references, more than twice the number of references that appear in the First Edition With over 300 new entries, appearing in an A-Z format, the Encyclopedia of Cryptography and Security provides easy, intuitive access to information on all aspects of cryptography and security. As a critical enhancement to the First Edition’s base of 464 entries, the information in the Encyclopedia is relevant for researchers and professionals alike. Topics for this comprehensive reference were elected, written, and peer-reviewed by a pool of distinguished researchers in the field. The Second Edition’s editorial board now includes 34 scholars, which was expanded from 18 members in the First Edition. Representing the work of researchers from over 30 countries, the Encyclopedia is broad in scope, covering everything from authentication and identification to quantum cryptography and web security. The text’s practical style is instructional, yet fosters investigation. Each area presents concepts, designs, and specific implementations. The highly-structured essays in this work include synonyms, a definition and discussion of the topic, bibliographies, and links to related literature. Extensive cross-references to other entries within the Encyclopedia support efficient, user-friendly searches for immediate access to relevant information. Key concepts presented in the Encyclopedia of Cryptography and Security include: Authentication and identification; Block ciphers and stream ciphers; Computational issues; Copy protection; Cryptanalysis and security; Cryptographic protocols; Electronic payment and digital certificates; Elliptic curve cryptography; Factorization algorithms and primality tests; Hash functions and MACs; Historical systems; Identity-based cryptography; Implementation aspects for smart cards and standards; Key management; Multiparty computations like voting schemes; Public key cryptography; Quantum cryptography; Secret sharing schemes; Sequences; Web Security. Topics covered: Data Structures, Cryptography and Information Theory; Data Encryption; Coding and Information Theory; Appl.Mathematics/Computational Methods of Engineering; Applications of Mathematics; Complexity. This authoritative reference will be published in two formats: print and online. The online edition features hyperlinks to cross-references, in addition to significant research.
| Author | : National Academies of Sciences, Engineering, and Medicine |
| Publisher | : National Academies Press |
| Total Pages | : 151 |
| Release | : 2017-04-21 |
| Genre | : Social Science |
| ISBN | : 030945428X |
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.
| Author | : Josep Domingo-Ferrer |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 238 |
| Release | : 2002-04-17 |
| Genre | : Computers |
| ISBN | : 3540436146 |
Inference control in statistical databases, also known as statistical disclosure limitation or statistical confidentiality, is about finding tradeoffs to the tension between the increasing societal need for accurate statistical data and the legal and ethical obligation to protect privacy of individuals and enterprises which are the source of data for producing statistics. Techniques used by intruders to make inferences compromising privacy increasingly draw on data mining, record linkage, knowledge discovery, and data analysis and thus statistical inference control becomes an integral part of computer science. This coherent state-of-the-art survey presents some of the most recent work in the field. The papers presented together with an introduction are organized in topical sections on tabular data protection, microdata protection, and software and user case studies.
| Author | : Peter Christen |
| Publisher | : |
| Total Pages | : 476 |
| Release | : 2020 |
| Genre | : Computer security |
| ISBN | : 3030597067 |
This book provides modern technical answers to the legal requirements of pseudonymisation as recommended by privacy legislation. It covers topics such as modern regulatory frameworks for sharing and linking sensitive information, concepts and algorithms for privacy-preserving record linkage and their computational aspects, practical considerations such as dealing with dirty and missing data, as well as privacy, risk, and performance assessment measures. Existing techniques for privacy-preserving record linkage are evaluated empirically and real-world application examples that scale to population sizes are described. The book also includes pointers to freely available software tools, benchmark data sets, and tools to generate synthetic data that can be used to test and evaluate linkage techniques. This book consists of fourteen chapters grouped into four parts, and two appendices. The first part introduces the reader to the topic of linking sensitive data, the second part covers methods and techniques to link such data, the third part discusses aspects of practical importance, and the fourth part provides an outlook of future challenges and open research problems relevant to linking sensitive databases. The appendices provide pointers and describe freely available, open-source software systems that allow the linkage of sensitive data, and provide further details about the evaluations presented. A companion Web site at https://dmm.anu.edu.au/lsdbook2020 provides additional material and Python programs used in the book. This book is mainly written for applied scientists, researchers, and advanced practitioners in governments, industry, and universities who are concerned with developing, implementing, and deploying systems and tools to share sensitive information in administrative, commercial, or medical databases. The Book describes how linkage methods work and how to evaluate their performance. It covers all the major concepts and methods and also discusses practical matters such as computational efficiency, which are critical if the methods are to be used in practice - and it does all this in a highly accessible way! David J. Hand, Imperial College, London.
| Author | : Josep Domingo-Ferrer |
| Publisher | : Springer |
| Total Pages | : 370 |
| Release | : 2020-08-21 |
| Genre | : Computers |
| ISBN | : 9783030575205 |
This book constitutes the refereed proceedings of the International Conference on Privacy in Statistical Databases, PSD 2020, held in Tarragona, Spain, in September 2020 under the sponsorship of the UNESCO Chair in Data Privacy. The 25 revised full papers presented were carefully reviewed and selected from 49 submissions. The papers are organized into the following topics: privacy models; microdata protection; protection of statistical tables; protection of interactive and mobility databases; record linkage and alternative methods; synthetic data; data quality; and case studies. The Chapter “Explaining recurrent machine learning models: integral privacy revisited” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
| Author | : Josep Domingo-Ferrer |
| Publisher | : Springer Nature |
| Total Pages | : 375 |
| Release | : 2022-09-14 |
| Genre | : Computers |
| ISBN | : 3031139453 |
This book constitutes the refereed proceedings of the International Conference on Privacy in Statistical Databases, PSD 2022, held in Paris, France, during September 21-23, 2022. The 25 papers presented in this volume were carefully reviewed and selected from 45 submissions. They were organized in topical sections as follows: Privacy models; tabular data; disclosure risk assessment and record linkage; privacy-preserving protocols; unstructured and mobility data; synthetic data; machine learning and privacy; and case studies.
| Author | : Cynthia Dwork |
| Publisher | : |
| Total Pages | : 286 |
| Release | : 2014 |
| Genre | : Computers |
| ISBN | : 9781601988188 |
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.
