S. Vitel, Gheorghe Balan, Dumitru-Bogdan Prelipcean
{"title":"Improving Detection of Malicious Office Documents Using One-Side Classifiers","authors":"S. Vitel, Gheorghe Balan, Dumitru-Bogdan Prelipcean","doi":"10.1109/SYNASC49474.2019.00041","DOIUrl":null,"url":null,"abstract":"The current threat landscape is diverse and has lately been shifting from the binary executable application to a more light-coded and data-oriented approach. Considering this, the use of Microsoft Office documents in attacks has increased. The number of malicious samples is high and the complexity of evasion techniques is also challenging. The VBA macros are highly used in enterprise environments with benign purposes, so, in terms of detection, the number of false alarms should be close to zero. In this paper we discuss and propose a solution which focuses on keeping the rate of false positives as low as possible and, at the same time, maximizes the detection rate.","PeriodicalId":102054,"journal":{"name":"2019 21st International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 21st International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYNASC49474.2019.00041","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The current threat landscape is diverse and has lately been shifting from the binary executable application to a more light-coded and data-oriented approach. Considering this, the use of Microsoft Office documents in attacks has increased. The number of malicious samples is high and the complexity of evasion techniques is also challenging. The VBA macros are highly used in enterprise environments with benign purposes, so, in terms of detection, the number of false alarms should be close to zero. In this paper we discuss and propose a solution which focuses on keeping the rate of false positives as low as possible and, at the same time, maximizes the detection rate.