{"title":"检测对协同过滤推荐系统的操纵攻击的方法","authors":"A. D. Dakhnovich, D. S. Zagalsky, R. S. Solovey","doi":"10.3103/S0146411623080047","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"57 8","pages":"868 - 874"},"PeriodicalIF":0.6000,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Method for Detecting Manipulation Attacks on Recommender Systems with Collaborative Filtering\",\"authors\":\"A. D. Dakhnovich, D. S. Zagalsky, R. S. Solovey\",\"doi\":\"10.3103/S0146411623080047\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":46238,\"journal\":{\"name\":\"AUTOMATIC CONTROL AND COMPUTER SCIENCES\",\"volume\":\"57 8\",\"pages\":\"868 - 874\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2024-02-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AUTOMATIC CONTROL AND COMPUTER SCIENCES\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.3103/S0146411623080047\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.3103/S0146411623080047","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Method for Detecting Manipulation Attacks on Recommender Systems with Collaborative Filtering
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.
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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