Citation

Anaam, Elham Abdulwahab and Haw, Su Cheng and Naveen, Palanichamy and Ng, Kok Why (2023) Blockchain-Based Recommendation System: A Review Focusing On Security Aspect. Advances in Artificial Intelligence and Machine Learning, 03 (04). pp. 1572-1587. ISSN 2582-9793

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Abstract

Recently, blockchain technology has caused considerable interest in academic research in the recommendation system domain. These records frequently contain encryption to achieve a comprehensive and reliable recommendation system. These records frequently contain encryption keys. Additionally, recommendation systems concerning suitable evaluation metrics are crucial to providing an accurate recommender system. Despite the attempts to address these issues through various strategies, very few researchers have considered a success in encrypting, especially in safeguarding the subscribers’ data. Currently, blockchain technology has drawn a lot of interest amongst several researchers, including in the area of recommendation system. To define these gaps, the current study aims to review the adoption of blockchain as one significant upside plan to increase data protection in recommendation systems. The systematic literature review (SLR) method was used to analyze publications from different electronic databases and documents of studies from 2019 to 2022. This research contributed to an in-depth comprehension of blockchain-based security techniques for recommending systems in addition to offering an overview of currently available blockchainbased programs within industries. The report emphasizes and examines significant facts and information about the blockchain depends security techniques for recommendation networks. Researchers highlight interest in a higher rate of security data and highlight noteworthy elements determined by an independent evaluation technique.

Item Type:	Article
Uncontrolled Keywords:	Blockchain
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	03 Jan 2024 07:21
Last Modified:	03 Jan 2024 07:21
URII:	http://shdl.mmu.edu.my/id/eprint/12014

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