{"title":"Protecting data from malware threats using machine learning technique","authors":"Mozammel Chowdhury, Azizur Rahman, R. Islam","doi":"10.1109/ICIEA.2017.8283111","DOIUrl":null,"url":null,"abstract":"Cyber attacks against sensitive data have become as serious threats all over the world due to the rising applications of computer and information technology. New malware or malicious programs are released everyday by cyber criminals through the Internet in an attempt to steal or destroy important data. Hence, research on protecting data receives tremendous interest in the cyber community. In order to cope with new variants of malicious software, machine learning techniques can be used for accurate classification and detection. This paper proposes an efficient scheme for malware detection for protecting sensitive data from malicious threats using data mining and machine learning techniques. Experimental results shows that the proposed approach gives better performance compared to other similar methods.","PeriodicalId":443463,"journal":{"name":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIEA.2017.8283111","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
Cyber attacks against sensitive data have become as serious threats all over the world due to the rising applications of computer and information technology. New malware or malicious programs are released everyday by cyber criminals through the Internet in an attempt to steal or destroy important data. Hence, research on protecting data receives tremendous interest in the cyber community. In order to cope with new variants of malicious software, machine learning techniques can be used for accurate classification and detection. This paper proposes an efficient scheme for malware detection for protecting sensitive data from malicious threats using data mining and machine learning techniques. Experimental results shows that the proposed approach gives better performance compared to other similar methods.