A Comparative Assessment of Obfuscated Ransomware Detection Methods

Sergiu Sechel
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引用次数: 14

Abstract

Ransomware represents a class of malicious applications that encrypts the files of infected system and demands from victims a payment in cryptocurrency in order to receive the decryption key. The mainstream adoption of cryptocurrencies increased the number of ransomware attack. The outbreaks had risen in complexity and received mass-media attention in 2017 when two destructive campaigns crippled companies and institutions around the world. These outbreaks continue at an accelerated pace even though efforts are made to improve the detection and mitigation of ransomware. The purpose of this research is to assess the efficiency of current malware analysis methods and technologies in the detection of ransomware. The experiments presented here were performed using antivirus engines and dynamic malware analysis against live obfuscated ransomware samples.
混淆勒索软件检测方法的比较评估
勒索软件是一类恶意应用程序,它对受感染系统的文件进行加密,并要求受害者以加密货币支付以获得解密密钥。加密货币的主流采用增加了勒索软件攻击的数量。2017年,两场破坏性的运动使世界各地的公司和机构陷入瘫痪,疫情变得更加复杂,并引起了大众媒体的关注。尽管人们努力改进勒索软件的检测和缓解措施,但这些疫情仍在加速蔓延。本研究的目的是评估当前恶意软件分析方法和技术在检测勒索软件方面的效率。本文介绍的实验是使用反病毒引擎和针对实时混淆勒索软件样本的动态恶意软件分析进行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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17
审稿时长
8 weeks
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