A Stackleberg Game Theory and Improved Fuzzy Based Intrusion Detection Approach for Virtual Machine Migration Timing Problem in Cloud Computing

E, Balamurugan and Almamum, Shawakat Akbar and Hasan, Shahidul and K, Sangeetha (2020) A Stackleberg Game Theory and Improved Fuzzy Based Intrusion Detection Approach for Virtual Machine Migration Timing Problem in Cloud Computing. EAI Endorsed Transactions on Cloud Systems, 6 (19). p. 166552. ISSN 2410-6895

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Abstract

Current computing concepts are migrated to a an emerging technology called cloud computing. Self-adaptive resource allocation framework and intelligent machine learning framework are proposed in various research work for providing optimized resource allocation. Privacy and security are the major concerns which restricts it’s adoption to clouds. Outsourcing, resource sharing and multi-tenancy are introduced by cloud to overcome security concerns. Stackelberg Game Theory Framework (SGTF) is used in proposed security model for enhancing data’s confidentiality level and over cloud environment. For multiple correlated VMs (migration requests), migration problem is studied in this work and for solving the same, an Enhanced Artificial Neural Network (EANN) and IDS based on fuzzy is introduced. In this method, migration request is included with correlations between VMs and these correlated VMs are treated integrally rather than separate treatment.

Item Type: Article
Uncontrolled Keywords: Intrusion Detection System, Improved Fuzzy Logic, Stackleberg Game Theory, Migration Timing Problem,Virtual Machine Migration, Cloud Computing
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 21 Jan 2021 06:54
Last Modified: 21 Jan 2021 06:54
URI: https://eprints.eudl.eu/id/eprint/802

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