Inference Control in Statistical Databases
Subtitle: From Theory to Practice (Lecture Notes in Computer Science)
Edition: 1 edition
Publisher: Springer
Published: May 28, 2002
Language: eng
Format: Paperback
Number of pages: 231
ISBN-13: 9783540436140
Subjects: Data security & data encryption; Privacy & data protection; Security; Database security; Statistics; Database Engineering; Mathematical Statistics; Computers; Computers - General Information; Textbooks; Probability & Statistics - General; Computer Books: General; Databases; Database Management - General; General; Computers / Computer Science; Security - General; Computers - Computer Security; Bases de donnâees; Mesures; Sâecuritâe
First sentence: The protection of confidential data is a constant issue of concern for data collectors and especially for national statistical agencies.
Description: 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.