Annotation: This article discusses the security of recommendation systems with collaborative filtering from manipulation attacks. 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 comparison of the effectiveness of the modified method with other relevant methods were carried out.

Keywords: recommendation systems, collaborative filtering, shilling attack detection.