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Submitted URL: https://doi.org/10.1109/TETC.2022.3155272
Effective URL: https://ieeexplore.ieee.org/document/9733785/
Submission: On April 13 via api from US — Scanned from DE
Effective URL: https://ieeexplore.ieee.org/document/9733785/
Submission: On April 13 via api from US — Scanned from DE
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IEEE websites place cookies on your device to give you the best user experience. By using our websites, you agree to the placement of these cookies. To learn more, read our Privacy Policy. Accept & Close Skip to Main Content * IEEE.org * IEEE Xplore * IEEE-SA * IEEE Spectrum * More Sites SUBSCRIBE SUBSCRIBE Cart Create AccountPersonal Sign In * Browse * My Settings * Help Institutional Sign In Institutional Sign In AllBooksConferencesCoursesJournals & MagazinesStandardsAuthorsCitations ADVANCED SEARCH Journals & Magazines >IEEE Transactions on Emerging... >Early Access EVALUATING THE SECURITY AND ECONOMIC EFFECTS OF MOVING TARGET DEFENSE TECHNIQUES ON THE CLOUD Publisher: IEEE Cite This PDF Hooman Alavizadeh; Samin Aref; Dong Seong Kim; Julian Jang-Jaccard All Authors Sign In or Purchase to View Full Text 17 Full Text Views * * * * * Alerts ALERTS Manage Content Alerts Add to Citation Alerts -------------------------------------------------------------------------------- Abstract Authors Keywords Metrics More Like This * Download PDF * View References * * Request Permissions * Save to * Alerts Abstract:Moving Target Defense (MTD) is a proactive security mechanism that changes the attack surface with the aim of confusing attackers. Cloud computing leverages MTD technique...View more Metadata Abstract: Moving Target Defense (MTD) is a proactive security mechanism that changes the attack surface with the aim of confusing attackers. Cloud computing leverages MTD techniques to enhance the cloud security posture against cyber threats. While many MTD techniques have been applied to cloud computing, there has so far been no joint evaluation of the effectiveness of MTD techniques with respect to security and economic metrics. In this paper, we first introduce mathematical definitions for the combination of three MTD techniques: Shuffle, Diversity, and Redundancy. Then, we utilize four security metrics-namely, system risk, attack cost, return on attack, and reliability-to assess the effectiveness of the combined MTD techniques applied to large-scale cloud models. Second, we focus on a specific context based on a cloud model for e-health applications to evaluate the effectiveness of the MTD techniques using security and economic metrics. We introduce (1) a strategy to effectively deploy the Shuffle MTD technique using a virtual machine placement technique, and (2) two strategies to deploy the Diversity MTD technique through operating system diversification. As deploying the Diversity technique incurs costs, we formulate the optimal diversity assignment problem (O-DAP), and solve it as a binary linear programming model to obtain the assignment that maximizes the expected net benefit. Published in: IEEE Transactions on Emerging Topics in Computing ( Early Access ) Page(s): 1 - 1 Date of Publication: 14 March 2022 ISSN Information: DOI: 10.1109/TETC.2022.3155272 Publisher: IEEE -------------------------------------------------------------------------------- Authors Keywords Metrics More Like This A New approach using redundancy technique to improve security in cloud computing Proceedings Title: 2012 International Conference on Cyber Security, Cyber Warfare and Digital Forensic (CyberSec) Published: 2012 A Security Threats Measurement Model for Reducing Cloud Computing Security Risk 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing Published: 2015 Show More IEEE PERSONAL ACCOUNT * Change username/password PURCHASE DETAILS * Payment Options * View Purchased Documents PROFILE INFORMATION * Communications Preferences * Profession and Education * Technical interests NEED HELP? * US & Canada: +1 800 678 4333 * Worldwide: +1 732 981 0060 * Contact & Support FOLLOW * * * About IEEE Xplore | Contact Us | Help | Accessibility | Terms of Use | Nondiscrimination Policy | IEEE Ethics Reporting | Sitemap | Privacy & Opting Out of Cookies A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. © Copyright 2022 IEEE - All rights reserved. IEEE ACCOUNT * Change Username/Password * Update Address PURCHASE DETAILS * Payment Options * Order History * View Purchased Documents PROFILE INFORMATION * Communications Preferences * Profession and Education * Technical Interests NEED HELP? * US & Canada: +1 800 678 4333 * Worldwide: +1 732 981 0060 * Contact & Support * About IEEE Xplore * Contact Us * Help * Accessibility * Terms of Use * Nondiscrimination Policy * Sitemap * Privacy & Opting Out of Cookies A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. © Copyright 2022 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.