A Secured Movie Recommendation System using Decentralized Blockchain Network

Recommender systems strongly affect a company’s profitability and regularly play a significant role in the success of companies’ sales policies. The companies are now collecting vast amounts of user information to make sure they can use recommender systems and related algorithms for recommending products and services according to customer needs, preferences, and likenesses. Unfortunately, privacy concerns prevent users from sharing data generously with interested companies, even if the quality of the recommendations would be improved. One way to overcome privacy-related issues is using a secured solution such as incorporating blockchain technologies for privacy-based applications. Blockchain is a distributed system and has a peer-to- peer linked structure. Integrating blockchain technology and the Internet of Things creates modern decentralized systems. The integration gives scalability and security to recommender systems. This research calls for innovative and advanced research on Blockchain and recommendation systems. We constructed a blockchain-based recommender system using “the Movielens” database. Learning case studies include a model to recommend movies to users. The accuracy of models is evaluated by an incentive mechanism that offers a fully trust-based recommendation system with acceptable performance. The results demonstrate that blockchain-based methods can be efficiently used for the privacy preservation of recommender systems.