Mis-Configuration Investigation for the Cloud Computing Based on the Fuzzy Pattern Recognition

Abstract:

The mis-configuration investigation is an important field in the security of cloud computing. However, the common method of investigating mis-configuration is a post-processing way. In order to find errors in the process of the cloud service management timely, we analyze the relationship between indicators of the cloud computing and locations of configuration items in this paper. According to this relationship, we construct a solution model based on the fuzzy pattern recognition. The lattice degree of nearness is used to determined locations of the mis-configuration. We further test the validity and accuracy of the model under the cloud simulation environment. The results show that the model is more effective and accurate to find the location of the mis-configuration rapidly.

• Periodical: Applied Mechanics and Materials (Volumes 336-338)
• Pages: 2369-2375
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.336-338.2369
• Online since: July 2013
• Authors: Bin Wu, Ji Tao Ma, Ping Wu
• Keywords: Fuzzy Pattern Recognition, Lattice Degree of Nearness, Membership Function, Mis-Configuration Investigation

References

[1] Ellen Messmer 2009 Are security issues delaying adoption of cloud computing network world, http://www.networkworld.com/news/2009/042709-burning-security-cloud-comp-uting.html.

[2] G. Reese November 2008 Ky Scurity Issues for the Amazon Cloud Oeilly Inc, http://broadcast.oreilly.com/2008/11/key-security-issues-for-the-am.html.

[3] Kandukuri, B.R.; Paturi, V.R.; Rakshit, A. 2009 Cloud Security Issues Services Computing, SCC '09, IEEE International Conference 517-520.

DOI: 10.1109/scc.2009.84

[4] Delaet T.; Wouter J. 2008 High-level system configuration Proceedings of the First R2D2 Workshop, Microsoft Technical Report, 1-3.

[5] Child.D et al. 2008 Develved Management of Distributed Infrastructures Quattor 22nd Large Installation System Administration Conference (LISA'08).

[6] Jianzong Wang; Varman P. et al. 2010 Avoiding performance fluctuation in cloud storage High Performance Computing (HiPC), 2010 International Conference 1-9.

DOI: 10.1109/hipc.2010.5713182

[7] Somani G; Chaudhary S. 2009 Application Performance Isolation in Virtualization Cloud'09 IEEE International Conference 41-48.

DOI: 10.1109/cloud.2009.78

[8] Cardosa, M., et al., 2011 Exploring MapReduce efficiency with highly-distributed data in Proceedings of the second international workshop on MapReduce and its applications. 2011, ACM: San Jose, California, USA 27-34.

DOI: 10.1145/1996092.1996100

[9] Mao, H., et al., 2011 Towards Deploying Elastic Hadoop in the Cloud in Proceedings of the 2011 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery. 2011, IEEE Computer Society 476-482.

DOI: 10.1109/cyberc.2011.83

[10] Barham P; Dragovic B. et al. 2003 Xen and the art virtualization SOSP'03:Proceedings of the nineteenth ACM symposium on Operating systems principles ACM 2003 164-177.

DOI: 10.1145/945445.945462

[11] Evered M; Bogeholz S. 2004 A case study in access control requirements for a Health Information Proceedings of the second workshop on Australasian information Security ACSW Frontiers'04 vol(32) 53-61.

[12] Cao X; Iverson L. 2006 intentional access management: making access control usable for end-users Proceedings of the second symposium on Usable privacy and security SOUPS'06 20-31.

DOI: 10.1145/1143120.1143124

[13] Devarshi Ghoshal; Richard Shane Canon; et al. 2011 I/O performance of virtualized cloud environments DataCloud-SC'11 Proceedings of the second international workshop on Data intensive computing in the clouds 71-80.

DOI: 10.1145/2087522.2087535

[14] Ongaro D; Cox A L; et al. 2008 Scheduling I/O in virtual machine monitors VEE, ACM 2008,1-10.

[15] Evan Martin; Tao Xie. 2007 A fault model and mutation testing of access control policies Proceedings of the 16th international conference on World Wide Web WWW'07 667-676.

DOI: 10.1145/1242572.1242663

[16] Khazaei H; Misic J; et al. 2011 Performance Analysis of Cloud Computing Centers Using M/G/m/m+r Queueing Systems Parallel Distributed Systems, IEEE Transactions vol(99),1-1.

DOI: 10.1109/tpds.2011.199