Method for Detecting Manipulation Attacks on Recommender Systems with Collaborative Filtering

IF 0.6 Q4 AUTOMATION & CONTROL SYSTEMS AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2024-02-29 DOI:10.3103/S0146411623080047
A. D. Dakhnovich, D. S. Zagalsky, R. S. Solovey
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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.

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检测对协同过滤推荐系统的操纵攻击的方法
本文探讨了协同过滤推荐系统免受操纵攻击的安全性问题。分析并确定了最常见的攻击类型。提出了一种检测协同过滤推荐系统操纵攻击的改进方法。还进行了实验测试,并比较了改进方法与其他现有方法的有效性。
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来源期刊
AUTOMATIC CONTROL AND COMPUTER SCIENCES
AUTOMATIC CONTROL AND COMPUTER SCIENCES AUTOMATION & CONTROL SYSTEMS-
CiteScore
1.70
自引率
22.20%
发文量
47
期刊介绍: Automatic Control and Computer Sciences is a peer reviewed journal that publishes articles on• Control systems, cyber-physical system, real-time systems, robotics, smart sensors, embedded intelligence • Network information technologies, information security, statistical methods of data processing, distributed artificial intelligence, complex systems modeling, knowledge representation, processing and management • Signal and image processing, machine learning, machine perception, computer vision
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