V2E:结合硬件虚拟化和软件仿真,用于透明和可扩展的恶意软件分析

Lok K. Yan, Manjukumar Jayachandra, Mu Zhang, Heng Yin
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引用次数: 80

摘要

透明和可扩展的恶意软件分析平台对于击败恶意软件至关重要。这个平台应该是透明的,这样恶意软件就不能轻易地检测和绕过它。它还应该是可扩展的,以便为重量级仪器和分析效率提供强大的支持。然而,没有现有的平台可以同时满足这两种需求。利用硬件虚拟化技术,Ether等分析平台可以实现良好的透明性,但其仪器支持和分析效率较差。相比之下,软件仿真通过使用动态二进制转换为代码插装提供了强大的支持和良好的分析效率。然而,基于软件仿真的分析平台容易被恶意软件检测,透明度较差。为了实现透明性和可扩展性,我们提出了一种结合硬件虚拟化和软件仿真的分析平台。其本质是精确的异构重放:通过硬件虚拟化记录恶意软件的执行,然后在软件中重放。我们的设计确保执行回放是精确的。此外,通过页面级记录粒度,平台可以轻松调整以分析各种形式的恶意软件(进程、内核模块或共享库)。我们实现了一个名为V2E的原型,并通过对合成样本和14个真实世界的抗仿真恶意软件样本进行广泛评估,展示了其能力和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
V2E: combining hardware virtualization and softwareemulation for transparent and extensible malware analysis
A transparent and extensible malware analysis platform is essential for defeating malware. This platform should be transparent so malware cannot easily detect and bypass it. It should also be extensible to provide strong support for heavyweight instrumentation and analysis efficiency. However, no existing platform can meet both requirements. Leveraging hardware virtualization technology, analysis platforms like Ether can achieve good transparency, but its instrumentation support and analysis efficiency is poor. In contrast, software emulation provides strong support for code instrumentation and good analysis efficiency by using dynamic binary translation. However, analysis platforms based on software emulation can be easily detected by malware and thus is poor in transparency. To achieve both transparency and extensibility, we propose a new analysis platform that combines hardware virtualization and software emulation. The essence is precise heterogeneous replay: the malware execution is recorded via hardware virtualization and then replayed in software. Our design ensures the execution replay is precise. Moreover, with page-level recording granularity, the platform can easily adjust to analyze various forms of malware (a process, a kernel module, or a shared library). We implemented a prototype called V2E and demonstrated its capability and efficiency by conducting an extensive evaluation with both synthetic samples and 14 realworld emulation-resistant malware samples.
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