一个强大的动态分析系统,防止沙盒检测由Android恶意软件

Jyoti Gajrani, Jitendra Sarswat, Meenakshi Tripathi, V. Laxmi, M. Gaur, M. Conti
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引用次数: 30

摘要

由于Android恶意软件应用程序的数量和多样性的增加,安全社区有必要开发自动动态分析系统。静态分析有其局限性,动态分析可以克服这些局限性。许多基于动态分析方法的工具采用仿真/虚拟化环境进行分析。虽然它一直是一种有效的分析技术,但它可以被最近复杂的恶意软件发现和规避。诸如Pincer, AnserverBot, BgServ, Wroba等恶意软件家族已经纳入了检查模拟或虚拟环境存在的方法。一旦检测到沙箱的存在,它们就不会执行任何恶意行为。本文提出并开发了一个鲁棒仿真环境,该环境对大多数检测技术具有弹性。我们将我们的恶意软件分析工具DroidAnalyst与12个公开可用的动态分析服务进行了比较,并表明在考虑抗反仿真技术的弹性时,我们的服务是最好的。在纯基于仿真的动态分析中引入反检测技术,阻碍了恶意软件对仿真环境的检测和规避。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A robust dynamic analysis system preventing SandBox detection by Android malware
Due to an increase in the number of Android malware applications and their diversity, it has become necessary for the security community to develop automated dynamic analysis systems. Static analysis has its limitations that can be overcome by dynamic analysis. Many tools based on dynamic analysis approach have been developed which employ emulated/virtualized environment for analysis. While it has been an effective technique for analysis, it can be espied and evaded by recent sophisticated malware. Malware families such as Pincer, AnserverBot, BgServ, Wroba have incorporated methods to check the presence of emulated or virtualized environment. Once the presence of the sandbox is detected, they do not execute any malicious behavior. In this paper, a robust emulated environment has been proposed and developed that is resilient against most of the detection techniques. We have compared our malware analysis tool DroidAnalyst against 12 publicly available dynamic analysis services and shown that our service is best when considering resilience against anti-emulation techniques. Incorporation of anti anti-detection techniques in the dynamic analysis that are purely based on emulation hinders the detection and evasion of emulated environment by malware.
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