The increasing adoption of Kubernetes presents new cybersecurity challenges, particularly in detecting resource consumption attacks like DoS. This work proposes a monitoring approach using Prometheus and Node Exporter to collect key host metrics, including CPU usage, memory consumption, disk activity, and network traffic. Machine learning algorithms such as Random Forest and AdaBoost are applied to detect anomalies. The model is evaluated based on detection accuracy, false alarm rate, and response time. The proposed approach enhances Kubernetes security by enabling precise resource consumption analysis and proactive attack detection.

Бархоом М. (науч. рук. Воробьева А.А.) Analyzing resource usage to detect attacks in kubernetes environments // Сборник тезисов докладов конгресса молодых ученых. Электронное издание. – СПб: Университет ИТМО, [2025]. URL: https://kmu.itmo.ru/digests/article/15106