Cloud services, vital in private, public, and commercial sectors, demand unwavering security and resilience. This paper introduces online cloud anomaly detection, emphasizing one-class SVMs at the hypervisor level, showcasing high detection accuracy exceeding 90% against malware and DoS attacks, while highlighting the importance of system and network data in versatile detection. This approach, involving dedicated monitoring components per VM, adapts adeptly to cloud scenarios, even with unknown malware strains.

• Cloud Security and Resilience
• One-Class SVM for Malware and DoS Detection
• Online Cloud Anomaly Detection