Blockchain-based Recommender Systems: Applications, Challenges and Future Opportunities
Yassine Himeur, Aya Sayed, Abdullah Alsalemi, Faycal Bensaali, Abbes, Amira, Iraklis Varlamis, Magdalini Eirinaki, Christos Sardianos, George, Dimitrakopoulos

TL;DR
This paper reviews how blockchain technology can enhance security and privacy in recommender systems across various domains, discussing challenges, solutions, and future research directions.
Contribution
It provides a comprehensive taxonomy of security and privacy challenges and reviews existing blockchain-based frameworks for recommender systems.
Findings
Blockchain improves security and privacy in recommender systems.
Current frameworks address some challenges but lack complete solutions.
Future research opportunities include developing more resilient and scalable blockchain solutions.
Abstract
Recommender systems have been widely used in different application domains including energy-preservation, e-commerce, healthcare, social media, etc. Such applications require the analysis and mining of massive amounts of various types of user data, including demographics, preferences, social interactions, etc. in order to develop accurate and precise recommender systems. Such datasets often include sensitive information, yet most recommender systems are focusing on the models' accuracy and ignore issues related to security and the users' privacy. Despite the efforts to overcome these problems using different risk reduction techniques, none of them has been completely successful in ensuring cryptographic security and protection of the users' private information. To bridge this gap, the blockchain technology is presented as a promising strategy to promote security and privacy preservation…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
