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  • 1
    Book
    Book
    Berlin ; Heidelberg ; New York ; Barcelona ; Hong Kong ; London : Springer
    UID:
    b3kat_BV014243033
    Format: VIII, 229 S.
    ISBN: 3540436146
    Series Statement: Lecture notes in computer science 2316
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Statistische Datenbank ; Privatsphäre ; Anonymisierung ; Datensicherung ; Statistische Datenbank ; Datenschutz ; Datensicherung ; Statistikgeheimnis ; Konferenzschrift
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Book
    Book
    Berlin ; Heidelberg ; New York ; Barcelona ; Hong Kong ; London :Springer,
    UID:
    almahu_BV014243033
    Format: VIII, 229 S.
    ISBN: 3-540-43614-6
    Series Statement: Lecture notes in computer science 2316
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Statistische Datenbank ; Privatsphäre ; Anonymisierung ; Datensicherung ; Statistische Datenbank ; Datenschutz ; Datensicherung ; Statistikgeheimnis ; Konferenzschrift ; Konferenzschrift
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Online Resource
    Online Resource
    Berlin : Springer
    UID:
    gbv_366241095
    Format: Online-Ressource
    Edition: 2002 Springer eBook Collection. Computer Science
    ISBN: 3540478043 , 9783540478041
    Series Statement: Lecture notes in computer science 2316
    Note: Lizenzpflichtig
    Additional Edition: ISBN 3540436146
    Additional Edition: ISBN 9783540436140
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Statistische Datenbank ; Privatsphäre ; Anonymisierung ; Datensicherung ; Statistische Datenbank ; Datenschutz ; Datensicherung ; Statistikgeheimnis ; Konferenzschrift
    Library Location Call Number Volume/Issue/Year Availability
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  • 4
    Online Resource
    Online Resource
    Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg
    UID:
    gbv_1646448952
    Format: Online-Ressource , v.: digital
    ISBN: 9783540478041
    Series Statement: Lecture Notes in Computer Science 2316
    Content: Advances in Inference Control in Statistical Databases: An Overview -- Advances in Inference Control in Statistical Databases: An Overview -- Tabular Data Protection -- Cell Suppression: Experience and Theory -- Bounds on Entries in 3-Dimensional Contingency Tables Subject to Given Marginal Totals -- Extending Cell Suppression to Protect Tabular Data against Several Attackers -- Network Flows Heuristics for Complementary Cell Suppression: An Empirical Evaluation and Extensions -- HiTaS: A Heuristic Approach to Cell Suppression in Hierarchical Tables -- Microdata Protection -- Model Based Disclosure Protection -- Microdata Protection through Noise Addition -- Sensitive Micro Data Protection Using Latin Hypercube Sampling Technique -- Integrating File and Record Level Disclosure Risk Assessment -- Disclosure Risk Assessment in Perturbative Microdata Protection -- LHS-Based Hybrid Microdata vs Rank Swapping and Microaggregation for Numeric Microdata Protection -- Post-Masking Optimization of the Tradeoff between Information Loss and Disclosure Risk in Masked Microdata Sets -- Software and User Case Studies -- The CASC Project -- Tools and Strategies to Protect Multiple Tables with the GHQUAR Cell Suppression Engine -- SDC in the 2000 U.S. Decennial Census -- Applications of Statistical Disclosure Control at Statistics Netherlands -- Empirical Evidences on Protecting Population Uniqueness at Idescat.
    Content: 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.
    Note: In: Springer-Online
    Additional Edition: ISBN 9783540436140
    Additional Edition: Buchausg. u.d.T. Inference control in statistical databases Berlin : Springer, 2002 ISBN 3540436146
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Statistische Datenbank ; Privatsphäre ; Anonymisierung ; Datensicherung ; Statistische Datenbank ; Datenschutz ; Datensicherung ; Statistikgeheimnis ; Statistische Datenbank ; Privatsphäre ; Anonymisierung ; Datensicherung ; Datenschutz ; Statistikgeheimnis ; Konferenzschrift
    URL: Volltext  (lizenzpflichtig)
    URL: Volltext  (lizenzpflichtig)
    URL: Cover
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  • 5
    Book
    Book
    Berlin [u.a.] : Springer-Verlag
    UID:
    kobvindex_ZLB13362057
    Format: VIII, 229 Seiten , graph. Darst. , 24 cm
    ISBN: 3540436146
    Series Statement: Lecture notes in computer science 2316
    Note: Literaturangaben , Text engl.
    Language: English
    Keywords: Statistische Datenbank ; Privatsphäre ; Anonymisierung ; Datensicherung ; Kongress ; Statistische Datenbank ; Datenschutz ; Datensicherung ; Statistikgeheimnis ; Kongress ; Statistische Datenbank ; Privatsphäre ; Anonymisierung ; Datensicherung ; Kongress ; Luxemburg 〈Stadt, 2001〉 ; Statistische Datenbank ; Datenschutz ; Datensicherung ; Statistikgeheimnis ; Kongress ; Luxemburg 〈Stadt, 2001〉 ; Kongress ; Konferenzschrift
    Author information: Domingo-Ferrer, Josep
    Library Location Call Number Volume/Issue/Year Availability
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  • 6
    UID:
    gbv_34547743X
    Format: VIII, 229 S. , graph. Darst. , 24 cm
    ISBN: 3540436146
    Series Statement: Lecture notes in computer science 2316
    Note: Literaturangaben
    Additional Edition: Erscheint auch als Online-Ausgabe Inference Control in Statistical Databases Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg, 2006 ISBN 9783540478041
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Statistische Datenbank ; Privatsphäre ; Anonymisierung ; Datensicherung ; Statistische Datenbank ; Datenschutz ; Datensicherung ; Statistikgeheimnis ; Konferenzschrift
    URL: Cover
    Library Location Call Number Volume/Issue/Year Availability
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  • 7
    Online Resource
    Online Resource
    Berlin, Heidelberg :Springer Berlin Heidelberg,
    UID:
    almahu_9947920588102882
    Format: VIII, 231 p. , online resource.
    ISBN: 9783540478041
    Series Statement: Lecture Notes in Computer Science, 2316
    Content: 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.
    Note: Advances in Inference Control in Statistical Databases: An Overview -- Advances in Inference Control in Statistical Databases: An Overview -- Tabular Data Protection -- Cell Suppression: Experience and Theory -- Bounds on Entries in 3-Dimensional Contingency Tables Subject to Given Marginal Totals -- Extending Cell Suppression to Protect Tabular Data against Several Attackers -- Network Flows Heuristics for Complementary Cell Suppression: An Empirical Evaluation and Extensions -- HiTaS: A Heuristic Approach to Cell Suppression in Hierarchical Tables -- Microdata Protection -- Model Based Disclosure Protection -- Microdata Protection through Noise Addition -- Sensitive Micro Data Protection Using Latin Hypercube Sampling Technique -- Integrating File and Record Level Disclosure Risk Assessment -- Disclosure Risk Assessment in Perturbative Microdata Protection -- LHS-Based Hybrid Microdata vs Rank Swapping and Microaggregation for Numeric Microdata Protection -- Post-Masking Optimization of the Tradeoff between Information Loss and Disclosure Risk in Masked Microdata Sets -- Software and User Case Studies -- The CASC Project -- Tools and Strategies to Protect Multiple Tables with the GHQUAR Cell Suppression Engine -- SDC in the 2000 U.S. Decennial Census -- Applications of Statistical Disclosure Control at Statistics Netherlands -- Empirical Evidences on Protecting Population Uniqueness at Idescat.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9783540436140
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 8
    Online Resource
    Online Resource
    Berlin, Heidelberg :Springer Berlin Heidelberg :
    UID:
    almahu_9948621578502882
    Format: VIII, 231 p. , online resource.
    Edition: 1st ed. 2002.
    ISBN: 9783540478041
    Series Statement: Lecture Notes in Computer Science, 2316
    Content: 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.
    Note: Advances in Inference Control in Statistical Databases: An Overview -- Advances in Inference Control in Statistical Databases: An Overview -- Tabular Data Protection -- Cell Suppression: Experience and Theory -- Bounds on Entries in 3-Dimensional Contingency Tables Subject to Given Marginal Totals -- Extending Cell Suppression to Protect Tabular Data against Several Attackers -- Network Flows Heuristics for Complementary Cell Suppression: An Empirical Evaluation and Extensions -- HiTaS: A Heuristic Approach to Cell Suppression in Hierarchical Tables -- Microdata Protection -- Model Based Disclosure Protection -- Microdata Protection through Noise Addition -- Sensitive Micro Data Protection Using Latin Hypercube Sampling Technique -- Integrating File and Record Level Disclosure Risk Assessment -- Disclosure Risk Assessment in Perturbative Microdata Protection -- LHS-Based Hybrid Microdata vs Rank Swapping and Microaggregation for Numeric Microdata Protection -- Post-Masking Optimization of the Tradeoff between Information Loss and Disclosure Risk in Masked Microdata Sets -- Software and User Case Studies -- The CASC Project -- Tools and Strategies to Protect Multiple Tables with the GHQUAR Cell Suppression Engine -- SDC in the 2000 U.S. Decennial Census -- Applications of Statistical Disclosure Control at Statistics Netherlands -- Empirical Evidences on Protecting Population Uniqueness at Idescat.
    In: Springer Nature eBook
    Additional Edition: Printed edition: ISBN 9783540829706
    Additional Edition: Printed edition: ISBN 9783540436140
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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