Collaborative System for Scheduling the Cloud Services in MVM

International Journal of Mobile Computing and Application

© 2015 by SSRG - IJMCA Journal

Volume 2 Issue 1

Year of Publication : 2015

Authors : S.Sarathkumar, C.Vinoth

10.14445/23939141/IJMCA-V2I2P102

How to Cite?

S.Sarathkumar, C.Vinoth, "Collaborative System for Scheduling the Cloud Services in MVM," SSRG International Journal of Mobile Computing and Application, vol. 2,  no. 1, pp. 13-16, 2015. Crossref, https://doi.org/10.14445/23939141/IJMCA-V2I2P102

Abstract:

Data mining technique has become interesting because of identifying patterns and trends from large collections of data. It is known that the collection and analysis of data that includes personal information of an individual may violate privacy of to whom the information refers. After obtaining this data pattern it is shared among various organizations to improve its services. While sharing the information among the organizations, it may be misused. To overcome this, Access Control Mechanism is used to protect sensitive information from unauthorized user. But still privacy preserving mechanisms is not applied to ensure the privacy of shared information. To ensure the privacy, Top-Down heuristic is applied with kd -tree partitioning. This approach is limited only to static data release not for incremental data. That is it is assumed that a whole dataset is available at the time of data release. To address this issue anonymization approach with generalization and range tree partitioning is applied on incremental data which can enhance security and privacy policies.

Keywords:

Access Control, Privacy, Mondrian, Imprecision Bound.

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