Research Area:  Software Defined Networks

Abstract:

Moving Target Defense (MTD) is a proactive security solution, which can be utilized by cloud computing in order to thwart cyber attacks. Many MTD techniques have been proposed, but there is still a lack of systematic evaluation methods for assessing the effectiveness of the proposed MTD techniques, especially when multiple MTD techniques are to be used in combinations. In this paper, we aim to address the aforementioned issue by proposing an approach for modeling and analysis of MTD techniques. We consider four security metrics: system risk, attack cost, return on attack, and availability to quantify the security of the cloud before and after deploying MTD techniques. Moreover, we propose a Diversity MTD technique to deploy OS diversification with various variants on multiple VMs and also combined Shuffle, Diversity, and Redundancy MTD techniques to improve the security of the cloud. We analyze the security metrics before and after deploying the proposed techniques to show the effectiveness of them. We also utilize importance measures based on network centrality measures into security analysis phase to improve the scalability of the MTD evaluation.

Keywords:  
Security
Moving Target Defense (MTD) Techniques
Cloud

Author(s) Name:  Hooman Alavizadeh , Jin B. Hong , Julian Jang-Jaccard , Dong Seong Kim

Publisher name:  ACM

DOI:  10.1145/3268966.3268967

Volume Information:  

Paper Link:   https://dl.acm.org/doi/abs/10.1145/3268966.3268967