Osiris:一个在虚拟机监控层实现的恶意软件行为捕获系统

Ying Cao, Jiachen Liu, Qiguang Miao, Weisheng Li
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引用次数: 14

摘要

捕获恶意软件的行为是动态分析恶意软件的必要前提之一。在本文中,我们研究并设计了一个名为Osiris的系统,该系统利用虚拟机技术捕获恶意软件的行为。特别地,我们监视被分析进程(或目标程序)调用的Windows API调用,以重建其行为。监视器是在虚拟机管理器层实现的,而不是在Guest OS中实现的,与其他可用方法相比,这是一个创新。Qemu是一个开源系统模拟器,用作Osiris的模拟器组件。通过修改Qemu的转换过程,插入一个API分析框架来拦截API调用。除此之外,Osiris还直接从虚拟内存中收集与安全相关的操作系统内核数据,用于进一步分析。Osiris与以前的系统相比有优势,因为它不需要复杂的分析环境,也不会干扰目标程序的执行。它克服了以往所采用的信息收集不完整和不精确的缺点。这些特性使Osiris成为自动恶意软件分析的理想工具。它可以为基于行为的恶意软件检测提供精细的数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Osiris: A Malware Behavior Capturing System Implemented at Virtual Machine Monitor Layer
Capturing behavior of malware is one of the essential prerequisites for dynamic malware analysis. In this paper, we study and design a system called Osiris, which makes use of virtual machine technique to capture malware behavior. In particularly, we monitor Windows API calls invoked by the process under analysis (or target program) to rebuild its behaviors. The monitor is implemented at the virtual machine manager layer rather than inside the Guest OS, which is an innovation compared to other available methods. Qemu, an open-source system emulator, is used as the emulator component of Osiris. By modifying Qemu's translation process, an API analysis framework is inserted to intercept API calls. Besides this, Osiris also collects security relevant OS kernel data directly from virtual memory for further analysis. Osiris has advantages over previous systems in that it requires no complex analysis environment and does not interfere the execution of target programs. It overcomes the deficiencies previous ones employed that the information collected is incomplete and imprecise. These features make Osiris an ideal tool for automatic malware analysis. It can provide fine data for behavior-based malware detection.
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