The rising use of microservices based software deployment on the cloud leverages containerized software extensively. The security of applications running inside containers as well as the container environment itself are critical infrastructure in the cloud setting and 5G. To address the security concerns, research efforts have been focused on container security with subfields such as intrusion detection, malware detection and container placement strategies. These security efforts are roughly divided into two categories: rule based approaches and machine learning that can respond to novel threats. In this study, we have surveyed the container security literature focusing on approaches that leverage machine learning to address security challenges.
翻译:随着云平台上基于微服务的软件部署的逐渐普及,软件容器的使用呈现出爆炸式增长。容器环境本身以及其中运行的应用程序的安全性对于云平台和5G来说都是关键的基础设施。为了解决安全问题,研究工作已经重点关注了容器安全领域,包括入侵检测、恶意软件检测和容器部署等。这些安全工作大致分为两类:规则型方法和机器学习方法,旨在应对新型威胁。在本研究中,我们对容器安全文献进行了综述,重点关注了应用机器学习方法应对安全挑战的方法。