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：随着基于微服务的云软件部署日益普及，容器化软件得到广泛运用。在云计算环境和5G网络中，容器内运行的应用程序及容器环境本身的安全构成关键基础设施。为应对安全挑战，学术界聚焦于容器安全研究，涵盖入侵检测、恶意软件检测及容器部署策略等子领域。这些安全方案大致分为两类：基于规则的检测方法，以及能够应对新型威胁的机器学习方法。本研究综述了容器安全领域的文献，重点梳理了利用机器学习技术解决安全挑战的研究成果。