rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Database anonymization
    sub title: privacy models, data utility, and microaggregation-based inter-model connections
  title info:
    title: Synthesis digital library of engineering and computer science
  name:
    name part: Domingo-Ferrer, Josep
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Sanchez, David
    role:
      role term: author.
  name:
    name part: Soria-Comas, Jordi
    role:
      role term: author.
  type of resource: text
  genre: abstract or summary
  genre: Electronic books.
  origin info:
    place:
      place term: cau
    date issued: 2016
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (xv, 120 pages) : illustrations.
  abstract: The current social and economic context increasingly demands open data to improve scientific research and decision making. However, when published data refer to individual respondents, disclosure risk limitation techniques must be implemented to anonymize the data and guarantee by design the fundamental right to privacy of the subjects the data refer to. Disclosure risk limitation has a long record in the statistical and computer science research communities, who have developed a variety of privacy-preserving solutions for data releases. This Synthesis Lecture provides a comprehensive overview of the fundamentals of privacy in data releases focusing on the computer science perspective. Specifically, we detail the privacy models, anonymization methods, and utility and risk metrics that have been proposed so far in the literature. Besides, as a more advanced topic, we identify and discuss in detail connections between several privacy models (i.e., how to accumulate the privacy guarantees they offer to achieve more robust protection and when such guarantees are equivalent or complementary); we also explore the links between anonymization methods and privacy models (how anonymization methods can be used to enforce privacy models and thereby offer ex ante privacy guarantees). These latter topics are relevant to researchers and advanced practitioners, who will gain a deeper understanding on the available data anonymization solutions and the privacy guarantees they can offer.
  table of contents: 1. Introduction --
  table of contents: 10. Differential privacy by individual ranking microaggregation -- 10.1 Limitations of multivariate microaggregation -- 10.2 Sensitivity reduction via individual ranking -- 10.3 Choosing the microggregation parameter k -- 10.4 Summary --
  table of contents: 11. Conclusions and research directions -- 11.1 Summary and conclusions -- 11.2 Research directions -- Bibliography -- Authors' biographies.
  table of contents: 2. Privacy in data releases -- 2.1 Types of data releases -- 2.2 Microdata sets -- 2.3 Formalizing privacy -- 2.4 Disclosure risk in microdata sets -- 2.5 Microdata anonymization -- 2.6 Measuring information loss -- 2.7 Trading off information loss and disclosure risk -- 2.8 Summary --
  table of contents: 3. Anonymization methods for microdata -- 3.1 Non-perturbative masking methods -- 3.2 Perturbative masking methods -- 3.3 Synthetic data generation -- 3.4 Summary --
  table of contents: 4. Quantifying disclosure risk: record linkage -- 4.1 Threshold-based record linkage -- 4.2 Rule-based record linkage -- 4.3 Probabilistic record linkage -- 4.4 Summary --
  table of contents: 5. The k-anonymity privacy model -- 5.1 Insufficiency of data de-identification -- 5.2 The k-anonymity model -- 5.3 Generalization and suppression based k-anonymity -- 5.4 Microaggregation-based k-anonymity -- 5.5 Probabilistic k-anonymity -- 5.6 Summary --
  table of contents: 6. Beyond k-anonymity: l-diversity and t -closeness -- 6.1 l-diversity -- 6.2 t-closeness -- 6.3 Summary --
  table of contents: 7. t-closeness through microaggregation -- 7.1 Standard microaggregation and merging -- 7.2 t-closeness aware microaggregation: k-anonymity-first -- 7.3 t-closeness aware microaggregation: t-closeness-first -- 7.4 Summary --
  table of contents: 8. Differential privacy -- 8.1 Definition -- 8.2 Calibration to the global sensitivity -- 8.3 Calibration to the smooth sensitivity -- 8.4 The exponential mechanism -- 8.5 Relation to k-anonymity-based models -- 8.6 Differentially private data publishing -- 8.7 Summary --
  table of contents: 9. Differential privacy by multivariate microaggregation -- 9.1 Reducing sensitivity via prior multivariate microaggregation -- 9.2 Differentially private data sets by insensitive microaggregation -- 9.3 General insensitive microaggregation -- 9.4 Differential privacy with categorical attributes -- 9.5 A semantic distance for differential privacy -- 9.6 Integrating heterogeneous attribute types -- 9.7 Summary --
  target audience: specialized
  note: Josep Domingo-Ferrer, David Sánchez, and Jordi Soria-Comas.
  note: Abstract freely available; full-text restricted to subscribers or individual document purchasers.
  note: Also available in print.
  note: Mode of access: World Wide Web.
  note: System requirements: Adobe Acrobat Reader.
  note: Includes bibliographical references (pages 109-118).
  subject:
    topic: Data protection
  subject:
    topic: Database security
  subject:
    topic: anonymization
  subject:
    topic: data releases
  subject:
    topic: microaggregation
  subject:
    topic: privacy models
  subject:
    topic: privacy protection
  subject:
    topic: statistical disclosure control
  subject:
    topic: statistical disclosure limitation
  classification: HF5548.37 .D653 2016
  classification: 658.478
  related item:
    title info:
      title: Synthesis lectures on information security, privacy and trust ; # 15
  identifier: 9781627058445
  identifier: 9781627058438
  identifier: http://proxy.library.tamu.edu/login
  access condition: Abstract freely available; full-text restricted to subscribers or individual document purchasers.
  record info:
    record content source: CaBNVSL
    record creation date: 160122
    record change date: 20210728125150.0
    record identifier: in00003778561
    language of cataloging:
      language term: eng