基于ARM架构的Docker容器安全性分析

Md. Sadun Haq, A. Tosun, T. Korkmaz
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引用次数: 1

摘要

容器提供了比虚拟机更好的性能和更快的部署,并提供了接近本机的性能,但存在隔离和安全缺点。尽管对于Intel架构的容器安全性已经进行了更详细的研究,但是对于ARM架构的容器安全性的研究还很有限。在本文中,我们解决了研究中的这一空白,并专注于为物联网设备中大量使用的ARM架构设计的容器的安全性。边缘计算提供了许多优势,包括减少了云上的延迟和资源需求,因为数据可以在发送到云之前在边缘进行处理。在物联网边缘云系统的边缘节点上使用容器可以增强这些优势,但代价是增加此类系统的安全漏洞。因此,有必要研究针对ARM架构设计的容器的安全性。因此,我们从DockerHub获得了官方的ARM映像,并使用各种安全工具扫描这些ARM映像。我们发现72%的漏洞显示出不同的严重级别,每个工具似乎对特定的基本映像最有效。我们研究了每个工具如何检测子包并实现不同的命中率,而没有一个工具可以单独检测至少80%的漏洞。此外,我们还通过运行两次扫描工具,调查了Docker映像及其漏洞在六个月内的变化情况。最后,我们还对树莓派上的一些图像进行了动态分析,并研究了它们的效果。我们相信本文将通过解决安全问题,促进ARM容器在基于ARM的边缘节点上的使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Security Analysis of Docker Containers for ARM Architecture
Containers provide a better performance, faster deployment than virtual machines and provide near-native performance, with isolation and security drawbacks. Although the security of containers for the Intel architecture has been investigated in more detail, there is limited work on the security of containers for the ARM architecture. In this paper, we address this gap in research and focus on the security of containers designed for the ARM architecture, which is heavily used in IoT devices. Edge computing offers many advantages, including reduced latency and resource requirements at the cloud because data can be processed at the edge before it is sent to the cloud. Using containers at the edge nodes of IoT-Edge-Cloud systems can enhance such advantages at the cost of increasing security vulnerabilities in such systems. Therefore, it is essential to investigate the security of containers designed for the ARM architecture. Accordingly, we obtained official ARM images from DockerHub and used various security tools to scan these ARM images. We found that 72% of all the vulnerabilities show varying severity levels and each tool seems to work best for particular base images. We investigated how each tool detects sub-packages and achieves a different hit ratio while none of them alone can detect at least 80% of all the vulnerabilities. In addition, we also investigated how the Docker images and their vulnerability landscape change over a period of six months by running the scanning tools twice. Finally, we also conducted a dynamic analysis of some of the images on the Raspberry Pi and study their effects. We believe this paper will facilitate the use of ARM containers at the ARM-based edge nodes by addressing security issues.
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