Xen and the art of virtualization
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Snort - Lightweight Intrusion Detection for Networks
LISA '99 Proceedings of the 13th USENIX conference on System administration
Security and privacy threats in IoT architectures
Proceedings of the 7th International Conference on Body Area Networks
| Hi-index | 0.00 |
Computer worms are very active and new sophisticated versions continuously appear. Signature-based detection methods work with a low false-positive rate, but previously knowledge about the threat is needed. Anomaly-based intrusion detection methods are able to detect new and unknown threats, but meaningful information for correct results is necessary. We propose an anomaly-based intrusion detection mechanism for the cloud which directly profits from the virtualization technologies in general. Our proposed anomaly detection system is isolated from spreading computer worm infections and it is able to detect unknown and new appearing computer worms. Using our approach, a spreading computer worm can be detected on the spreading behavior itself without accessing or directly influencing running virtual machines of the cloud.