METHOD FOR DETECTING SHILLING ATTACKS BASED ON IMPLICIT FEEDBACK IN RECOMMENDER SYSTEMS
Oksana Chala, Lyudmyla Novikova, Larysa Chernyshova, Angelika Kalnitskaya The problem of identifying shilling attacks, which are aimed at forming false ratings of objects in the recommender system, is considered. The purpose of such attacks is to include in the recommended list of items the goods specified by the attacking user. The recommendations obtained as a […]
METHOD FOR DETECTING SHILLING ATTACKS IN E-COMMERCE SYSTEMS USING WEIGHTED TEMPORAL RULES
Oksana Chala, Lyudmyla Novikova, Larysa Chernyshova The problem of shilling attacks detecting in e-commerce systems is considered. The purpose of such attacks is to artificially change the rating of individual goods or services by users in order to increase their sales. A method for detecting shilling attacks based on a comparison of weighted temporal rules […]