进程外嫁接:一种用于细粒度进程执行监控的高效“虚拟机外”方法

D. Srinivasan, Zhi Wang, Xuxian Jiang, Dongyan Xu
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引用次数: 101

摘要

最近恶意软件的快速增长暴露了传统的主机内恶意软件防御系统的局限性,并推动了基于虚拟机外安全虚拟化解决方案的开发。通过将易受攻击的系统作为虚拟机运行,并将安全软件从虚拟机内部移动到外部,out- vm解决方案可以安全地将反恶意软件与易受攻击的系统隔离开来。然而,语义缺口的存在也导致了不支持现有防御软件的兼容性问题。在本文中,我们提出了进程外嫁接,这是一种架构方法,用于解决细粒度进程级执行监视的虚拟机外方法中的隔离和兼容性挑战。具体来说,通过将可疑进程从VM内部重新定位到与VM外安全工具并排运行,我们的技术有效地消除了语义差距,并支持现有的用户模式进程监控工具,而无需进行任何修改。此外,通过将系统调用转发回VM,我们可以在不削弱监控工具的隔离性的情况下,顺利地继续执行接出的进程。我们已经开发了一个基于kvm的原型,并使用它来本地支持许多现有的工具,而无需进行任何修改。通过对基准程序的测试,验证了该方法的有效性和实用性,且性能开销小。
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Process out-grafting: an efficient "out-of-VM" approach for fine-grained process execution monitoring
Recent rapid malware growth has exposed the limitations of traditional in-host malware-defense systems and motivated the development of secure virtualization-based out-of-VM solutions. By running vulnerable systems as virtual machines (VMs) and moving security software from inside the VMs to outside, the out-of-VM solutions securely isolate the anti-malware software from the vulnerable system. However, the presence of semantic gap also leads to the compatibility problem in not supporting existing defense software. In this paper, we present process out-grafting, an architectural approach to address both isolation and compatibility challenges in out-of-VM approaches for fine-grained process-level execution monitoring. Specifically, by relocating a suspect process from inside a VM to run side-by-side with the out-of-VM security tool, our technique effectively removes the semantic gap and supports existing user-mode process monitoring tools without any modification. Moreover, by forwarding the system calls back to the VM, we can smoothly continue the execution of the out-grafted process without weakening the isolation of the monitoring tool. We have developed a KVM-based prototype and used it to natively support a number of existing tools without any modification. The evaluation results including measurement with benchmark programs show it is effective and practical with a small performance overhead.
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CiteScore
9.20
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