An Extensive Study of Privacy Preserving Recommendation System Using Collaborative Filtering

Recommender system is the most information filtering-based system that deals with information overload by filtering vital information from large dynamically collected information according to the user’s choices, interest, or item’s behavior. The collaborative-based filtering recommender system is one of the best filtering approaches, which is very effective in a wide range of applications. The recommender system’s accuracy usually depends on the quality of the collected data, which cannot be collected from users without concerning their privacy requirements. Today’s recommender systems are obliged to collapse unless they provide a measure of privacy to users. However, privacy and accuracy are conflicting goals because preserving privacy requires a level of distortion in original data, which yields a decrease in recommender systems’ accuracy. Nowadays, providing privacy to sensitive information in a side recommender system is the main requirement with the best accuracy. This chapter summarizes all privacy-preserving methods for providing security and privacy to the user’s rating of a particular item.