User's Privacy in Recommendation Systems Applying Online Social Network Data, A Survey and Taxonomy

Understand

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.