Research Article
Inferring the Stealthy Bridges Between Enterprise Network Islands in Cloud Using Cross-Layer Bayesian Networks
@INPROCEEDINGS{10.1007/978-3-319-23829-6_1, author={Xiaoyan Sun and Jun Dai and Anoop Singhal and Peng Liu}, title={Inferring the Stealthy Bridges Between Enterprise Network Islands in Cloud Using Cross-Layer Bayesian Networks}, proceedings={International Conference on Security and Privacy in Communication Networks. 10th International ICST Conference, SecureComm 2014, Beijing, China, September 24-26, 2014, Revised Selected Papers, Part I}, proceedings_a={SECURECOMM}, year={2015}, month={11}, keywords={Cloud Stealthy bridge Bayesian network Attack graph}, doi={10.1007/978-3-319-23829-6_1} }- Xiaoyan Sun
Jun Dai
Anoop Singhal
Peng Liu
Year: 2015
Inferring the Stealthy Bridges Between Enterprise Network Islands in Cloud Using Cross-Layer Bayesian Networks
SECURECOMM
Springer
DOI: 10.1007/978-3-319-23829-6_1
Abstract
Enterprise networks are migrating to the public cloud to acquire computing resources for promising benefits in terms of efficiency, expense, and flexibility. Except for some public services, the enterprise network islands in cloud are expected to be absolutely isolated from each other. However, some “stealthy bridges” may be created to break such isolation due to two features of the public cloud: virtual machine image sharing and virtual machine co-residency. This paper proposes to use cross-layer Bayesian networks to infer the stealthy bridges existing between enterprise network islands. Prior to constructing cross-layer Bayesian networks, cloud-level attack graphs are built to capture the potential attacks enabled by stealthy bridges and reveal hidden possible attack paths. The result of the experiment justifies the cross-layer Bayesian network’s capability of inferring the existence of stealthy bridges given supporting evidence from other intrusion steps in a multi-step attack.