Visible to the public Modeling Virtual Machine Migration as a Security Mechanism by using Continuous-Time Markov Chain Model

TitleModeling Virtual Machine Migration as a Security Mechanism by using Continuous-Time Markov Chain Model
Publication TypeConference Paper
Year of Publication2019
AuthorsKandoussi, El Mehdi, El Mir, Iman, Hanini, Mohamed, Haqiq, Abdelkrim
Conference Name2019 4th World Conference on Complex Systems (WCCS)
Date PublishedApril 2019
PublisherIEEE
ISBN Number978-1-7281-1232-9
KeywordsAdaptation models, cloud computing, cloud computing environment, cloud environment, complex network, complex networks, Computational modeling, continuous-time Markov Chain model, Destination Server, destination server parameters, dynamic attack surface, dynamic security, dynamic security measure, intrusion, Markov processes, Migration, model migration, Network topology, probability, pubcrawl, security, security mechanism, security of data, Servers, sophisticated methods, static security measures, virtual machine migration modeling, virtual machine security, virtual machines, Virtual machining, VM migration
Abstract

In Cloud Computing Environment, using only static security measures didn't mitigate the attack considerably. Hence, deployment of sophisticated methods by the attackers to understand the network topology of complex network makes the task easier. For this reason, the use of dynamic security measure as virtual machine (VM) migration increases uncertainty to locate a virtual machine in a dynamic attack surface. Although this, not all VM's migration enhances security. Indeed, the destination server to host the VM should be selected precisely in order to avoid externality and attack at the same time. In this paper, we model migration in cloud environment by using continuous Markov Chain. Then, we analyze the probability of a VM to be compromised based on the destination server parameters. Finally, we provide some numerical results to show the effectiveness of our approach in term of avoiding intrusion.

URLhttps://ieeexplore.ieee.org/document/8930781
DOI10.1109/ICoCS.2019.8930781
Citation Keykandoussi_modeling_2019