Agent-based Vs Agent-less Sandbox for Dynamic Behavioral Analysis

Muhammad Ali, S. Shiaeles, M. Papadaki, B. Ghita
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引用次数: 6

Abstract

Malicious software is detected and classified by either static analysis or dynamic analysis. In static analysis, malware samples are reverse engineered and analyzed so that signatures of malware can be constructed. These techniques can be easily thwarted through polymorphic, metamorphic malware, obfuscation and packing techniques, whereas in dynamic analysis malware samples are executed in a controlled environment using the sandboxing technique, in order to model the behavior of malware. In this paper, we have analyzed Petya, Spyeye, VolatileCedar, PAFISH etc. through Agent-based and Agentless dynamic sandbox systems in order to investigate and benchmark their efficiency in advanced malware detection.
基于agent Vs .无agent的动态行为分析沙盒
恶意软件的检测和分类分为静态分析和动态分析两种。在静态分析中,恶意软件样本被逆向工程和分析,从而可以构建恶意软件的签名。这些技术可以很容易地通过多态、变形恶意软件、混淆和打包技术来挫败,而在动态分析中,恶意软件样本是在使用沙箱技术的受控环境中执行的,以便对恶意软件的行为进行建模。在本文中,我们通过基于代理和无代理的动态沙箱系统分析了Petya, Spyeye, VolatileCedar, PAFISH等,以调查和基准测试它们在高级恶意软件检测中的效率。
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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