{"title":"Features of Detecting Malicious Installation Files Using Machine Learning Algorithms","authors":"P. E. Yugai, E. V. Zhukovskii, P. O. Semenov","doi":"10.3103/S0146411623080333","DOIUrl":null,"url":null,"abstract":"<p>This paper presents a study of the possibility of using machine learning methods to detect malicious installation files related to the type of Trojan installers and downloaders. A comparative analysis of machine learning algorithms applicable for the solution of this problem is provided: the naive Bayes classifier (NBC), random forest, and C4.5 algorithm. Machine learning models are developed using the Weka software. The most significant attributes of installation files of legitimate and Trojan programs are highlighted.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"57 8","pages":"968 - 974"},"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/S0146411623080333","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents a study of the possibility of using machine learning methods to detect malicious installation files related to the type of Trojan installers and downloaders. A comparative analysis of machine learning algorithms applicable for the solution of this problem is provided: the naive Bayes classifier (NBC), random forest, and C4.5 algorithm. Machine learning models are developed using the Weka software. The most significant attributes of installation files of legitimate and Trojan programs are highlighted.
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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