Privacy-Preserving Data Publishing
eBook - PDF

Privacy-Preserving Data Publishing

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Privacy-Preserving Data Publishing

Book details
Table of contents
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About This Book

Privacy preservation has become a major issue in many data analysis applications. When a data set is released to other parties for data analysis, privacy-preserving techniques are often required to reduce the possibility of identifying sensitive information about individuals. For example, in medical data, sensitive information can be the fact that a particular patient suffers from HIV. In spatial data, sensitive information can be a specific location of an individual. In web surfing data, the information that a user browses certain websites may be considered sensitive. Consider a dataset containing some sensitive information is to be released to the public. In order to protect sensitive information, the simplest solution is not to disclose the information. However, this would be an overkill since it will hinder the process of data analysis over the data from which we can find interesting patterns. Moreover, in some applications, the data must be disclosed under the government regulations. Alternatively, the data owner can first modify the data such that the modified data can guarantee privacy and, at the same time, the modified data retains sufficient utility and can be released to other parties safely. This process is usually called as privacy-preserving data publishing. In this monograph, we study how the data owner can modify the data and how the modified data can preserve privacy and protect sensitive information. Table of Contents: Introduction / Fundamental Concepts / One-Time Data Publishing / Multiple-Time Data Publishing / Graph Data / Other Data Types / Future Research Directions

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Yes, you can access Privacy-Preserving Data Publishing by Raymond Chi-Wing Wong,Ada Wai-Chee Fu in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Networking. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Springer
Year
2022
ISBN
9783031018343

Table of contents

  1. Cover
  2. Copyright
  3. Title Page
  4. Contents
  5. Introduction
  6. Fundamental Concepts
  7. Multiple-Time Data Publishing
  8. One-Time Data Publishing
  9. Graph Data
  10. Other Data Types
  11. Future Research Directions
  12. Definition of Entropy l-Diversity and Recursive l-Diversity
  13. Bibliography
  14. Authors' Biographies