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:在云层杠杆上越来越多地使用基于微观服务的软件,使软件集装箱化,集装箱内部应用的安全以及集装箱环境本身是云层环境和5G的关键基础设施。为了解决安全问题,研究工作的重点是集装箱安全,包括入侵探测、恶意软件检测和集装箱安置战略等子领域。这些安全工作大致分为两类:基于规则的方法和机器学习,能够应对新的威胁。在本研究中,我们调查了集装箱安全文献,重点是利用机器学习应对安全挑战的方法。</s>