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：随着基于微服务的软件部署在云环境中的日益普及，容器化软件被广泛采用。运行在容器内的应用程序以及容器环境本身的安全性，在云环境和5G中均构成关键基础设施。为应对安全挑战，研究界围绕容器安全领域开展了大量工作，涉及入侵检测、恶意软件检测和容器部署策略等子方向。这些安全方法大致分为两类：基于规则的方法和能够应对新型威胁的机器学习方法。本研究系统综述了容器安全领域文献，重点关注利用机器学习解决安全挑战的相关方法。