AI-driven container security approaches for 5G and beyond: A survey

None Ilter Taha Aktolga, None Elif Sena Kuru, None Yigit Sever, None Pelin Angin
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Abstract

The rising use of microservice-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 for infrastructure in cloud settings and 5G. To address 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 survey the container security literature focusing on approaches that leverage machine learning to address security challenges.
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ai驱动的5G及以后的容器安全方法:一项调查
基于微服务的软件部署在云上的使用越来越多,这广泛地利用了容器化软件。在容器内运行的应用程序以及容器环境本身的安全性对于云设置和5G中的基础设施至关重要。为了解决安全问题,研究工作一直集中在容器安全的子领域,如入侵检测、恶意软件检测和容器放置策略。这些安全工作大致分为两类:基于规则的方法和可以响应新威胁的机器学习。在本研究中,我们调查了容器安全文献,重点关注利用机器学习解决安全挑战的方法。
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