Kubernetes has emerged as the most popular orchestration platform for automatic deployment, expansion, and management of the Docker container life cycle. However, containerized environments also bring new challenges in terms of complete monitoring and security provision. Thus, hackers can exploit the security vulnerabilities of containers to gain remote control permissions and cause extensive damage to company assets. and one of the ways to secure k8s is by using Machine Learning (ML). ML techniques have been used in various ways to prevent or detect attacks and security gaps on the k8s cloud system. In this work, we provide a new effective way to secure the k8s system against common attacks using ML techniques.

Дарвиш Г. (науч. рук. Воробьева А.А.) Development of detection common attacks in Kubernetes environment using machine learning approaches // Сборник тезисов докладов конгресса молодых ученых. Электронное издание. – СПб: Университет ИТМО, [2022]. URL: https://kmu.itmo.ru/digests/article/7703