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Blockchain-based recommender systems: Applications, challenges and future opportunities
Computer Science Review
  • Yassine Himeur, Qatar University
  • Aya Sayed, Qatar University
  • Abdullah Alsalemi, Qatar University
  • Faycal Bensaali, Qatar University
  • Abbes Amira, De Montfort University
  • Iraklis Varlamis, Harokopio University of Athens
  • Magdalini Eirinaki, San Jose State University
  • Christos Sardianos, Harokopio University of Athens
  • George Dimitrakopoulos, Harokopio University of Athens
Publication Date
Document Type

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 in recommender systems, not only because of its security and privacy salient features, but also due to its resilience, adaptability, fault tolerance and trust characteristics. This paper presents a holistic review of blockchain-based recommender systems covering challenges, open issues and solutions. Accordingly, a well-designed taxonomy is introduced to describe the security and privacy challenges, overview existing frameworks and discuss their applications and benefits when using blockchain before indicating opportunities for future research.

Funding Number
Funding Sponsor
Qatar Foundation
  • Big data and machine learning,
  • Blockchain,
  • Decentralized and collaborative recommender systems,
  • Recommender systems,
  • Scalability,
  • Security and privacy preservation
Creative Commons License
Creative Commons Attribution 4.0
Citation Information
Yassine Himeur, Aya Sayed, Abdullah Alsalemi, Faycal Bensaali, et al.. "Blockchain-based recommender systems: Applications, challenges and future opportunities" Computer Science Review Vol. 43 (2022)
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