C4.5: programs for machine learning
C4.5: programs for machine learning
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Remus: a security-enhanced operating system
ACM Transactions on Information and System Security (TISSEC)
Self-Organizing Maps
Network Intrusion Detection: An Analyst's Handbook
Network Intrusion Detection: An Analyst's Handbook
Efficient greedy learning of Gaussian mixture models
Neural Computation
A framework for classifying denial of service attacks
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Xen and the art of virtualization
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Basic Concepts and Taxonomy of Dependable and Secure Computing
IEEE Transactions on Dependable and Secure Computing
HOTOS'05 Proceedings of the 10th conference on Hot Topics in Operating Systems - Volume 10
Automated response using system-call delays
SSYM'00 Proceedings of the 9th conference on USENIX Security Symposium - Volume 9
Quantification of Security for Compute Intensive Workloads in Clouds
ICPADS '09 Proceedings of the 2009 15th International Conference on Parallel and Distributed Systems
A mission-impact-based approach to INFOSEC alarm correlation
RAID'02 Proceedings of the 5th international conference on Recent advances in intrusion detection
Defending against flooding-based distributed denial-of-service attacks: a tutorial
IEEE Communications Magazine
Taxonomy and proposed architecture of intrusion detection and prevention systems for cloud computing
CSS'12 Proceedings of the 4th international conference on Cyberspace Safety and Security
Pragmatic assessment of research intensive areas in cloud: a systematic review
ACM SIGSOFT Software Engineering Notes
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Cloud computing presents exciting opportunities to foster research for scientific communities; virtual machine technology has a profound role in this. Among other benefits, virtual machine technology enables Clouds to offer large scale and flexible computing infrastructures that are available on demand to address the diverse requirements of scientific research. However, Clouds introduce novel security challenges which need to be addressed to facilitate widespread adoption. This paper is focused on one such challenge-intrusion severity analysis. In particular, we highlight the significance of intrusion severity analysis for the overall security of Clouds. Additionally, we present a novel method to address this challenge in accordance with the specific requirements of Clouds for intrusion severity analysis. We also present rigorous evaluation to assess the effectiveness and feasibility of the proposed method to address this challenge for Clouds.