VirusBattle: State-of-the-art malware analysis for better cyber threat intelligence

Craig Miles, Arun Lakhotia, Charles LeDoux, Aaron Newsom, Vivek Notani
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引用次数: 20

Abstract

Discovered interrelationships among instances of malware can be used to infer connections among seemingly unconnected objects, including actors, machines, and the malware itself. However, such malware interrelationships are currently underutilized in the cyber threat intelligence arena. To fill that gap, we are developing VirusBattle, a system employing state-of-the-art malware analyses to automatically discover interrelationships among instances of malware. VirusBattle analyses mine malware interrelationships over many types of malware artifacts, including the binary, code, code semantics, dynamic behaviors, malware metadata, distribution sites and e-mails. The result is a malware interrelationships graph which can be explored automatically or interactively to infer previously unknown connections.
VirusBattle:最先进的恶意软件分析,更好的网络威胁情报
发现的恶意软件实例之间的相互关系可以用来推断看似没有连接的对象之间的连接,包括参与者、机器和恶意软件本身。然而,这种恶意软件的相互关系目前在网络威胁情报领域未得到充分利用。为了填补这一空白,我们正在开发VirusBattle,这是一个采用最先进的恶意软件分析来自动发现恶意软件实例之间相互关系的系统。VirusBattle分析了多种类型的恶意软件工件之间的相互关系,包括二进制,代码,代码语义,动态行为,恶意软件元数据,分发站点和电子邮件。结果是一个恶意软件的相互关系图,可以自动或交互地探索,以推断以前未知的连接。
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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