Research Article
A Stackleberg Game Theory and Improved Fuzzy Based Intrusion Detection Approach for Virtual Machine Migration Timing Problem in Cloud Computing
@ARTICLE{10.4108/eai.12-10-2020.166552, author={Balamurugan E and Md. Shawakat Akbar Almamum and Md. Shahidul Hasan and Sangeetha K}, title={A Stackleberg Game Theory and Improved Fuzzy Based Intrusion Detection Approach for Virtual Machine Migration Timing Problem in Cloud Computing}, journal={EAI Endorsed Transactions on Cloud Systems}, volume={6}, number={19}, publisher={EAI}, journal_a={CS}, year={2020}, month={10}, keywords={Intrusion Detection System, Improved Fuzzy Logic, Stackleberg Game Theory, Migration Timing Problem,Virtual Machine Migration, Cloud Computing}, doi={10.4108/eai.12-10-2020.166552} }- Balamurugan E
Md. Shawakat Akbar Almamum
Md. Shahidul Hasan
Sangeetha K
Year: 2020
A Stackleberg Game Theory and Improved Fuzzy Based Intrusion Detection Approach for Virtual Machine Migration Timing Problem in Cloud Computing
CS
EAI
DOI: 10.4108/eai.12-10-2020.166552
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.
Copyright © 2020 Balamurugan E et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.