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User's privacy in recommendation systems applying online social network data: a survey and taxonomy

User's privacy in recommendation systems applying online social network data: a survey and taxonomy

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Recommender systems have become an integral part of many social networks and extract knowledge from a user's personal and sensitive data both explicitly, with the user's knowledge, and implicitly. This trend has created major privacy concerns as users are mostly unaware of what data and how much data is being used and how securely it is used. In this context, several works have been done to address privacy concerns for usage in online social network data and by recommender systems. This paper surveys the main privacy concerns, measurements and privacy-preserving techniques used in large-scale online social networks and recommender systems. It is based on historical works on security, privacy-preserving, statistical modeling and datasets to provide an overview of the technical difficulties and problems associated with privacy preserving in online social networks.

Chapter Contents:

  • 12.1 Introduction
  • 12.2 Recommender systems and techniques: privacy of online social network data
  • 12.2.1 Privacy: definition
  • 12.2.2 Online social networks, classification, and privacy
  • 12.3 Taxonomy of privacy
  • 12.3.1 Privacy concerns in social networks
  • 12.3.2 User-specific privacy risks and invasion
  • 12.3.3 Measuring privacy in online social networks
  • 12.3.3.1 Dichotomous approach
  • 12.3.3.2 Polytomous approach
  • 12.3.4 Privacy-preserving approaches
  • 12.3.5 Privacy-preserving models
  • 12.3.5.1 k-Anonymity
  • 12.3.5.2 l-Diversity
  • 12.3.5.3 T-Closeness
  • 12.3.5.4 Differential privacy
  • 12.4 Privacy preservation in recommender systems
  • 12.5 Conclusion and future directions
  • References

Inspec keywords: recommender systems; information filtering; social networking (online); information filters; data privacy

Other keywords: large-scale online social networks; user; recommender systems; recommendation systems; online social network data; privacy preserving; main privacy concerns; privacy-preserving techniques

Subjects: Information retrieval techniques; Business and administration; Data security; Information networks; Internet software

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