Securing KVM-Based Cloud Systems via Virtualization Introspection

Sheng-Wei Lee, Fang Yu
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引用次数: 21

Abstract

Linux Kernel Virtual Machine (KVM) is one of the most commonly deployed hypervisor drivers in the IaaS layer of cloud computing ecosystems. The hypervisor provides a full-virtualization environment that intends to virtualize as much hardware and systems as possible, including CPUs, network interfaces and chipsets. With KVM, heterogeneous operating systems can be installed in Virtual Machines (VMs) in an homogeneous environment. However, it has been shown that various breaches due to software defects may cause damages on such a cloud ecosystem. We propose a new Virtualization Introspection System (VIS) to protect the host as well as VMs running on a KVM-based cloud structure from malicious attacks. VIS detects and intercepts attacks from VMs by collecting their static and dynamic status. We then replay the attacks on VMs and leverage artificial intelligence techniques to derive effective decision rules with unsupervised learning nature. The preliminary result shows the promise of the presented approach against several modern attacks on CVE-based vulnerabilities.
通过虚拟化自省保护基于kvm的云系统
Linux内核虚拟机(KVM)是云计算生态系统的IaaS层中最常部署的hypervisor驱动程序之一。hypervisor提供了一个完全虚拟化的环境,旨在虚拟化尽可能多的硬件和系统,包括cpu、网络接口和芯片组。使用KVM,可以在同构环境中的虚拟机上安装异构操作系统。然而,事实证明,由于软件缺陷导致的各种漏洞可能会对这样的云生态系统造成损害。我们提出了一种新的虚拟化自省系统(VIS)来保护主机以及运行在基于kvm的云结构上的虚拟机免受恶意攻击。VIS通过采集虚拟机的静态和动态状态,检测和拦截来自虚拟机的攻击。然后,我们在虚拟机上重播攻击,并利用人工智能技术获得具有无监督学习性质的有效决策规则。初步结果表明,所提出的方法可以抵御几种基于cve漏洞的现代攻击。
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