6 edition of Privacy in statistical databases found in the catalog.
Privacy in statistical databases
PSD 2008 (2008 Istanbul, Turkey)
|Statement||Josep Domingo-Ferrer, Yücel Saygin (eds.).|
|Series||Lecture notes in computer science -- 5262|
|Contributions||Domingo-Ferrer, Josep., Saygın, Yücel.|
|LC Classifications||QA76.9.A25 P79 2008|
|The Physical Object|
|Pagination||xi, 334 p. :|
|Number of Pages||334|
|LC Control Number||2008934858|
You will receive an email shortly at: Here at , we are committed to protecting your privacy. Your email address will never be sold or distributed to a third party for any : Magkos, Emmanouil. tems to preserve privacy in statistical studies that combine and analyse data from multiple databases. We describe an implementation on two real-world platforms|the Sharemind secure multi-party computation and the X-Road database federation platform. Our solution enables the privacy-preserving linking and analysis of databases belonging to di er-File Size: 1MB.
Auditing for secure statistical databases. F. Chin and G. Ozsoyoglu. ACM 81 Conference (). Suppression methodology and statistical disclosure control. L.H. Cox. JASA 75 (). A Security Model for the Statistical Database Problem. D.E. Denning. TODS 5 (). Secure statistical databases with random sample queries. D.E. Denning. TODS 5 (). However, supporting security in the statistical databases against the revealing of confidential data is complicated and ambitious task. This problem of privacy in the statistical databases has expanded in the recent years. This report will examine the main methods for providing privacy in the statistical databases. 2. Body
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Beyond respondent privacy, there are two additional privacy dimensions to be considered: privacy for the data owners (organizations owning or gathering the data, who would not like to share the data they have collected at great expense) and privacy for the users (those who submit queries to the database and would like their analyses to stay.
Juan-José Salazar-González, Philip Lowthian, Caroline Young, Giovanni Merola, Stephen Bond, David Brown. The PSD proceedings volume focuses on privacy in statistical databases.
The selected papers are organized into the following topics: tabular data protection; synthetic data; microdata and big data masking; record linkage; and spatial and mobility data. The scope of the conference is on following topics: tabular data protection; microdata and big data masking; protection using privacy models; synthetic data; remote and cloud access; disclosure risk assessment; co-utile anonymization.
Yue Ma, Yan-Xia Lin, James Chipperfield, John Newman, Victoria Leaver. This bar-code number lets you verify that you're getting exactly the right version or edition of a book.
The digit and digit formats both cturer: Springer. Overview The problem of statistical disclosure control—revealing accurate statistics about a population while preserving the privacy of individuals—has a venerable history.
An extensive literature spans multiple disciplines: statistics, theoretical computer science, security, and databases. Nevertheless, despite this extensive literature, «privacy breaches» are. The scope of the conference is on following topics: tabular data protection, microdata masking, protection using privacy models, synthetic data, record linkage, remote access, privacy-preserving protocols, and case studies.
The term is deliberately general as it covers relational databases, NoSQL databases, statistical environments such as R and SAS, and quite possibly scripts being run on a file system with a language such as AWK (Dougherty and Robbins, ) or Perl (Christiansen et al., ). This book’s definition of data analytics focuses on the.
An important contribution of this work is a deﬁnition of privacy (and privacy compromise) for statistical databases, together with a method for describing and comparing the privacy oﬀered by speciﬁc sanitization techniques. We obtain several privacy results using two diﬀerent sanitiza.
Josep Domingo-Ferrer, Mirjana Pejic-Bach: Privacy in Statistical Databases - UNESCO Chair in Data Privacy, International Conference, PSDDubrovnik, Croatia. Bookshare - Accessible Books for Individuals with Print Disabilities. A statistical database is a database used for statistical analysis purposes.
It is an OLAP (online analytical processing), instead of OLTP (online transaction processing) system. Modern decision, and classical statistical databases are often closer to the relational model than the multidimensional model commonly used in OLAP systems today.
Statistical databases. Josep Domingo-Ferrer is the author of Privacy in Statistical Databases ( avg rating, 0 ratings, 0 reviews), Privacy in Statistical Databases ( avg 4/5(1). Privacy in statistical databases 14 - 16 Sep (Event Over - New Dates Awaited) Centre For Advanced Academic Studies (CAAS), Dubrovnik, Croatia.
New From Stephenie Meyer, Midnight Sun Experience the story of Twilight, this time from the point of view of Edward Pre-Order Midnight Sun Now. Privacy in Statistical Databases by Josep Domingo-Ferrer,available at Book Depository with free delivery worldwide. Read Book Online Now ?book= Privacy in Statistical Databases: CASC Project International Workshop, PSDBarcelona, Spain, June.
in statistical databases: k-anonymity and microaggregation. Protecting the individual respondent information contained in The authors are partly supported by the Spanish Ministry of Science and. Topics of interest include but are not limited to: New anonymization methods for tabular data New anonymization methods for microdata (including non-conventional microdata types such as trajectories, graphs, etc.) Best anonymization practices for tabular data Best anonymization practices for microdata Co-utility for privacy preservation Big data anonymization Streaming.
Before releasing statistical outputs, data suppliers have to assess if the privacy of statistical units is endangered and apply Statistical Disclosure Control (SDC) methods if necessary.Learn about getting a more general randomized response, privacy loss, the privacy/utility tradeoff, and quantifying privacy loss in a statistical database.COVID Resources.
Reliable information about the coronavirus (COVID) is available from the World Health Organization (current situation, international travel).Numerous and frequently-updated resource results are available from this ’s WebJunction has pulled together information and resources to assist library staff as they consider how to handle .