Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

Part of: Synthesis digital library of engineering and computer science.

Series from website.

Includes bibliographical references (p. 65-74).

1. Introduction --

Part I. Online social networks and information disclosure -- 2. A model for online social networks -- 3. Types of privacy disclosure -- 3.1 Identity disclosure -- 3.2 Attribute disclosure -- 3.3 Social link disclosure -- 3.4 Affiliation link disclosure -- 4. Statistical methods for inferring information in networks -- 4.1 Entity resolution -- 4.2 Collective classification -- 4.3 Link prediction -- 4.4 Group detection --

Part II. Data publishing and privacy-preserving mechanisms -- 5. Anonymity and differential privacy -- 5.1 k-anonymity -- 5.2 l-diversity and t-closeness -- 5.3 Differential privacy -- 5.4 Open problems -- 6. Attacks and privacy-preserving mechanisms -- 6.1 Privacy mechanisms for social networks -- 6.1.1 Anonymizing network structure -- 6.1.2 Anonymizing user attributes and network structure -- 6.1.3 Privacy of social recommendation algorithms -- 6.2 Privacy mechanisms for affiliation networks -- 6.2.1 Anonymization -- 6.3 Privacy mechanisms for complex networks -- 6.4 Open problems --

Part III. Modeling, evaluating, and managing users' privacy risk -- 7. Models of information sharing -- 7.1 Information-sharing model -- 7.2 Strategic behavior and information sharing -- 7.3 Discussion and summary of results -- 7.4 Open problems -- 8. Users' privacy risk -- 8.1 Privacy-score model -- 8.2 Methods for computing the privacy score -- 8.2.1 Frequency-based method -- 8.2.2 IRT-based method -- 8.3 Discussion and summary of results -- 8.4 Open problems -- 9. Management of privacy settings -- 9.1 A model for managing privacy settings -- 9.2 Predicting users' privacy settings -- 9.3 Discussion and summary of results -- 9.4 Open problems --

Bibliography -- Authors' biographies.

Abstract freely available; full-text restricted to subscribers or individual document purchasers.

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This synthesis lecture provides a survey of work on privacy in online social networks (OSNs). This work encompasses concerns of users as well as service providers and third parties. Our goal is to approach such concerns from a computer-science perspective, and building upon existing work on privacy, security, statistical modeling and databases to provide an overview of the technical and algorithmic issues related to privacy in OSNs. We start our survey by introducing a simple OSN data model and describe common statistical-inference techniques that can be used to infer potentially sensitive information. Next, we describe some privacy definitions and privacy mechanisms for data publishing. Finally, we describe a set of recent techniques for modeling, evaluating, and managing individual users' privacy risk within the context of OSNs.

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Title from PDF t.p. (viewed on April 22, 2012).