Research Article | OPEN ACCESS
Data Classification Based on Confidentiality in Virtual Cloud Environment
Munwar Ali Zardari, Low Tang Jung and Mohamed Nordin B. Zakaria
Department of CIS, Universiti Teknologi PETRONAS, Malaysia
Research Journal of Applied Sciences, Engineering and Technology 2014 13:1498-1509
Received: November 23, 2013 | Accepted: March 08, 2014 | Published: October 05, 2014
Abstract
The aim of this study is to provide suitable security to data based on the security needs of data. It is very difficult to decide (in cloud) which data need what security and which data do not need security. However it will be easy to decide the security level for data after data classification according to their security level based on the characteristics of the data. In this study, we have proposed a data classification cloud model to solve data confidentiality issue in cloud computing environment. The data are classified into two major classes: sensitive and non-sensitive. The K-Nearest Neighbour (K-NN) classifier is used for data classification and the Rivest, Shamir and Adelman (RSA) algorithm is used to encrypt sensitive data. After implementing the proposed model, it is found that the confidentiality level of data is increased and this model is proved to be more cost and memory friendly for the users as well as for the cloud services providers. The data storage service is one of the cloud services where data servers are virtualized of all users. In a cloud server, the data are stored in two ways. First encrypt the received data and store on cloud servers. Second store data on the cloud servers without encryption. Both of these data storage methods can face data confidentiality issue, because the data have different values and characteristics that must be identified before sending to cloud severs.
Keywords:
Cloud computing, data classification, data confidentiality/sensitivity, distributed computing, K-NN, non-sensitive , RSA,
References
-
Cachin, C., R. Haas and M. Vukolic, 2010. Dependable Storage in the Intercloud. IBM Research Report RZ 3783.
-
Catteddu, D. and G. Hogben, 2009. Cloud Computing: Benefits, Risks and Recommendations for Information Security, ENISA, Crete, pp: 1-125.
CrossRef
-
Dasarathy, B.V., 1980. Nosing around the neighborhood: A new system structure and classification rule for recognition in partially exposed environments. IEEE T. Pattern Anal., PAMI-2(1): 67-71.
CrossRef
-
Deepanchakaravarthi, P. and S. Abburu, 2012. An approach for data storage security in cloud computing. IJCSI Int. J. Comput. Sci. Issues, 9(2): 1694-0814.
-
Duba, R.O. and P.E Hart, 1973. Pattern Classification and Scene Analysis. John Wily and Sons Inc., New York.
-
Etges, R. and K. McNeil, 2006. Understanding data classification based on business and security requirements. J. Online, 5: 1-8.
-
Forgey, E., 1965. Cluster analysis of multivariate data: Ef?ciency vs. Interpretability of classi?cation. Biometrics, 21: 768, 1965.
-
Friedman, H.P. and J. Rubin, 1967. On some invariant criteria for grouping data. J. Am. Stat. Assoc., 62: 1159-1178.
CrossRef
-
Hunt, E., 1975. Artificial Intelligence. Academic Press, New York.
-
Keller, J.M., M.R. Gray and J.A. Givens, 1985. A fussy-K-nearest neighbor algorithm. IEEE T. Syst. Man Cyb., SMC-15(4): 580-585.
CrossRef
-
Larose, D.T., 2005. Discovering Knowledge in Data: An Introduction to Data Mining. John Wiley and Sons, Inc., Hoboken, New Jersey, pp: 90-106.
PMCid:PMC1157106
-
Lloyd, S.P., 1957. Least squares quantization in PCM. Unpublished Bell Lab. Tech. Note, portions presented at the Institute of Mathematical Statistics Meeting Atlantic City, NJ, September 1957. Also, IEEE T. Inform Theory (Special Issue on Quantization), IT-28: 129-137.
-
McQueen, J., 1967. Some methods for classi?cation and analysis of multivariate observations. Proceeding of 5th Berkeley Symposium on Mathematical Statistics and Probability, 1: 281-296.
-
Michigan Technological University, 2011. Information Technology Services and Security, 2011. Data Classification and Handling Policy.
-
Patail, A. and S. Behal, 2012. RSA Algorithm achievement with federal information processing signature for data protection in cloud computing. Int. J. Comput. Technol., 3: 34-38.
-
Phyu, T.N., 2009. Survey of classification techniques in data mining. Proceeding of the International MultiConference of Engineers and Computer Scientists. Hong Kong, Vol. 1.
-
Ram, C.P. and G. Sreenivaasan, 2010. Security as a service (SasS): Securing user data by coprocessor and distributing the data. Proceeding of Trendz in Information Sciences and Computing (TISC, 2010), pp: 152-155.
-
Rawat, P.S., G.P. Saroha and V. Barthwal, 2012. Quality of service evaluation of Saas modeler (Cloudlet) running on virtual cloud computing environment using CloudSim. Int. J. Comput. Appl., 53(13): 35-38.
-
Rittinghouse, J.W. and J.F. Ransome, 2009. Cloud Computing Implementation, Management, Security. CRC Press by Taylor and Francis Group, LLC.
CrossRef
-
Song, D., E. Shi, I. Fischer and U. Shankar, 2012. Cloud data protection for the masses. IEEE Comput. Soc., 45(1): 39-45.
CrossRef
-
The California State University, 2011. Information Security Data Classification.
-
UTHSCSA, 2011. Protection by data classification security Standard. Data Classification Report.
-
Whitney, A. and S.J. Dwyer III, 1966. Performance and implementation of K-nearest neighbor decision rule with incorrectly identified training samples. Proceeding of 4th Allerton Conference Circuits Band System Theory.
-
Wu, X., V. Kumar, J.R. Quinlan, J. Ghosh, Q. Yang, H. Motoda, G.J. McLachlan, A. Ng, B. Liu, P.S. Yu, Z.H. Zhou, M. Steinbach, D.J. Hand and D. Steinberg, 2008. Top 10 algorithms in data mining. Knowl. Inf. Syst., 14: 1-37.
CrossRef
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
|
|
![](http://www.maxwellsci.com/images/RJASET-maxw.jpg) |
ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
![Submit Manuscript](../images/sub.jpg) |
Information |
|
|
|
Sales & Services |
|
|
|