Method for Detecting Manipulation Attacks on Recommender Systems with Collaborative Filtering

Abstract

The security of recommendation systems with collaborative filtering from manipulation attacks is considered. The most common types of attacks are analyzed and identified. A modified method for detecting manipulation attacks on recommendation systems with collaborative filtering is proposed. Experimental testing and a comparison of the effectiveness of the modified method with other current methods are carried out.