A study to Understand Malware Behavior through Malware Analysis

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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
通过恶意软件分析了解恶意软件行为的研究
大多数恶意软件检测技术都使用恶意软件签名进行检测。检测系统中已知的恶意程序很容易,但当恶意软件未知时,问题就出现了。因为,未知的恶意软件无法通过使用可用的已知恶意软件签名来检测。基于签名的检测技术无法检测到未知攻击和零日攻击。需要一种新颖的方法来有效地表示恶意软件的特征,以检测混淆、未知和变异的恶意软件。本文重点讨论了利用不同分析技术提取的恶意软件行为、特征和属性,以及是否将其包含在基于行为的恶意软件签名中。我们已经尝试使用一些公开可用的恶意软件分析工具来理解恶意软件的行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Security Analytics For Heterogeneous Web Pipeline Gas Leakage Detection And Location Identification System IoT Enabled Forest Fire Detection and Early Warning System Research opportunities on virtual reality and augmented reality: a survey Performance Analysis of Hub BLDC Motor Using Finite Element Analysis
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1