Evaluating the Effectiveness of Shuffle and Redundancy MTD Techniques in the Cloud

Hooman Alavizadeh, Jin Hong, Dong Seong Kim, Julian Jang-Jaccard

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

Moving Target Defense (MTD) is a defensive strategy to thwart adversaries by continuously shifting the attack surface. The MTD techniques can be applied to the cloud computing to make the cloud more unpredictable, hence more difficult to exploit. There are many MTD techniques proposed, and various metrics are used to measure their effectiveness. However, it is difficult to assess when MTD techniques are used in combinations. In this paper, we propose a formal security assessment approach to evaluate the effectiveness of combined MTD techniques using security modeling. We use security metrics, such as System Risk and Reliability, to evaluate those MTD techniques. In particular, we investigate how the security of the cloud change when two categories of MTD techniques, Shuffle and Redundancy, are used in combinations. We also explore approaches to find important components in the cloud using Network Centrality Measures and the size of the cloud and evaluate the trade-off between security and dependability in terms of the system Risk and Reliability, respectively. We show that combining the shuffle and redundancy MTD techniques could enhance the security of the cloud with the trade-off between the Risk and Reliability, which can be managed using the proposed security assessment approach.
Original languageEnglish
Article number102091
JournalComputers & Security
Volume102
Early online date28 Oct 2020
DOIs
Publication statusPublished - Mar 2021

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