Central Library

Normal view MARC view ISBD view

Data Privacy: Foundations, New Developments and the Big Data Challenge [electronic resource] / by Vicenç Torra.

By: Torra, Vicenç [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Big Data: 28Publisher: Cham : Springer International Publishing : Imprint: Springer, 2017Edition: 1st ed. 2017.Description: XIV, 269 p. 22 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319573588.Subject(s): Computational intelligence | Artificial intelligence | Computational Intelligence | Artificial IntelligenceAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
Introduction -- Machine and Statistical Learning -- On the Classification of Protection Procedures -- User’s privacy -- Privacy Models and Disclosure Risk Measures -- Masking methods -- Information loss: evaluation and measures -- Selection of masking methods -- Conclusions.
In: Springer Nature eBookSummary: This book offers a broad, cohesive overview of the field of data privacy. It discusses, from a technological perspective, the problems and solutions of the three main communities working on data privacy: statistical disclosure control (those with a statistical background), privacy-preserving data mining (those working with data bases and data mining), and privacy-enhancing technologies (those involved in communications and security) communities. Presenting different approaches, the book describes alternative privacy models and disclosure risk measures as well as data protection procedures for respondent, holder and user privacy. It also discusses specific data privacy problems and solutions for readers who need to deal with big data.
    average rating: 0.0 (0 votes)
No physical items for this record

Introduction -- Machine and Statistical Learning -- On the Classification of Protection Procedures -- User’s privacy -- Privacy Models and Disclosure Risk Measures -- Masking methods -- Information loss: evaluation and measures -- Selection of masking methods -- Conclusions.

This book offers a broad, cohesive overview of the field of data privacy. It discusses, from a technological perspective, the problems and solutions of the three main communities working on data privacy: statistical disclosure control (those with a statistical background), privacy-preserving data mining (those working with data bases and data mining), and privacy-enhancing technologies (those involved in communications and security) communities. Presenting different approaches, the book describes alternative privacy models and disclosure risk measures as well as data protection procedures for respondent, holder and user privacy. It also discusses specific data privacy problems and solutions for readers who need to deal with big data.

There are no comments for this item.

Log in to your account to post a comment.