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Keyword: Shilling attacksOpen AccessArticle
8 Pages, 547 KB 
Dismantle Shilling Attacks in Recommendations Systems
Abstract:
Collaborative filtering of recommended systems (CFRSs) suffers from overrun false rating injections that diverge the system functions for creating accurate recommendations. In this paper, we propose a three-stage unsupervised approach. Starts by defining the mechanism(s) that makes recommendation vulnerable to attack. Second, find the maximum-paths or the associated related items valued by the user. We…
Read More(This article belongs to the SP10 (Special Issue on Multidisciplinary Sciences and Engineering 2020-21) & Section Interdisciplinary Applications of Computer Science (CSI))