Om Prakash Samantray, S. Tripathy, Susant Kumar Das
{"title":"A study to Understand Malware Behavior through Malware Analysis","authors":"Om Prakash Samantray, S. Tripathy, Susant Kumar Das","doi":"10.1109/ICSCAN.2019.8878680","DOIUrl":null,"url":null,"abstract":"Most of the malware detection techniques use malware signatures for detection. It is easy to detect known malicious program in a system but the problem arises when the malware is unknown. Because, unknown malware cannot be detected by using available known malware signatures. Signature based detection techniques fails to detect unknown and zero-day attacks. A novel approach is required to represent malware features effectively to detect obfuscated, unknown, and mutated malware. This paper emphasizes malware behavior, characteristics and properties extracted by different analytic techniques and to decide whether to include them to create behavioral based malware signature. We have made an attempt to understand the malware behavior using a few openly available tools for malware analysis.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSCAN.2019.8878680","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Most of the malware detection techniques use malware signatures for detection. It is easy to detect known malicious program in a system but the problem arises when the malware is unknown. Because, unknown malware cannot be detected by using available known malware signatures. Signature based detection techniques fails to detect unknown and zero-day attacks. A novel approach is required to represent malware features effectively to detect obfuscated, unknown, and mutated malware. This paper emphasizes malware behavior, characteristics and properties extracted by different analytic techniques and to decide whether to include them to create behavioral based malware signature. We have made an attempt to understand the malware behavior using a few openly available tools for malware analysis.