Design on Framework for Dynamic Monitoring of Virtual Machines

Ke Ming Chen

doi:10.4028/www.scientific.net/AMM.530-531.667

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 530-531Design on Framework for Dynamic Monitoring of...

Design on Framework for Dynamic Monitoring of Virtual Machines

Abstract:

In order to ensure that the cloud platform client runtime kernel virtual machine security, this paper proposes a new framework for dynamic monitoring of virtual machines, it is for the kernel rootkit attacks, study the cloud client virtual machine operating system kernel safety, presented Hyperchk virtual machine dynamic monitoring framework. This framework mainly for kernel rootkit attacks, ensure that customers running virtual machine kernel security.

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Periodical:

Applied Mechanics and Materials (Volumes 530-531)

Pages:

667-670

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.530-531.667

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Online since:

February 2014

Authors:

Ke Ming Chen

Keywords:

Cloud Computing, Data Security, Dynamic Monitoring, Virtual Machine

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References

[1] A. Meera, S. Swamynathan: Procedia Technology, Vol. 10 (2013), pp.200-207.

Google Scholar

[2] X. Desforges: Robotics and Computer-Integrated Manufacturing, Vol. 27 (2011), pp.963-976.

Google Scholar

[3] R.L.G. Monaro, A.L. Helleno, K. Schützer: Procedia CIRP, Vol. 7 (2013), pp.317-322.

DOI: 10.1016/j.procir.2013.05.054

Google Scholar

[4] Y. Altintas, C. Brechert: CIRP Annals - Manufacturing Technology, Vol. 54 (2005), pp.115-138.

Google Scholar

[5] J.C. Ponsart, D. Theilliol, C. Aubrun: Control Engineering Practice, Vol. 18 (2010), pp.1037-1044.

Google Scholar

[6] R. F. Garcia, J. L. C. Rolle Expert Systems with Applications, Vol. 40 (2013), pp.2975-2984.

Google Scholar

[7] M. C. Pan, P. C. Li, Y. R. Cheng: Measurement, Vol. 41 (2008), pp.912-921.

Google Scholar

[8] C. Bisu, L. Olteanu, R. Laheurte, Ph. Darnis, O. Cahuc: Procedia CIRP, Vol. 12 (2013), pp.73-78.

DOI: 10.1016/j.procir.2013.09.014

Google Scholar

[9] L. He, D. Zou, Z. Zhang, C. Chen: Future Generation Computer Systems, Vol. 32 (2014), pp.69-81.

Google Scholar

[10] M. Schumann, M. Witt, P. Klimant: Procedia CIRP, Vol. 7 (2013), pp.329-334.

Google Scholar