Abstract
Moving Target Defense (MTD) is an emerging security solution based on continuously changing attack surface thus makes it unpredictable for attackers. Cloud computing could leverage such MTD approaches to prevent its resources and services being compromised from an increasing number of attacks. Most of the existing MTD methods so far have focused on devising subtle strategies for attack surface mitigation, and only a few have evaluated the effectiveness of different MTD techniques deployed in systems. We conducted an in-depth study, based on realistic simulations done on a cloud environment, on the effects of security and reliability for three different MTD techniques: (i) Shuffle, (ii) Redundancy, and (iii) the combination of Shuffle and Redundancy. For comparisons, we use a formal scalable security model to analyse the effectiveness of the MTD techniques. Moreover, we adopt Network Centrality Measures to enhance the performance of security analysis to overcome the exponential computational complexity which is often seen in a large networked mode.
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This paper was made possible by Grant NPRP 8-531-1-111 from Qatar National Research Fund (QNRF). The statements made herein are solely the responsibility of the authors.
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Alavizadeh, H., Kim, D.S., Hong, J.B., Jang-Jaccard, J. (2017). Effective Security Analysis for Combinations of MTD Techniques on Cloud Computing (Short Paper). In: Liu, J., Samarati, P. (eds) Information Security Practice and Experience. ISPEC 2017. Lecture Notes in Computer Science(), vol 10701. Springer, Cham. https://doi.org/10.1007/978-3-319-72359-4_32
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DOI: https://doi.org/10.1007/978-3-319-72359-4_32
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