Confidentiality and Privacy in Cloud Computing using Hybrid Execution Method
B. Jaswanthi1, M. NaliniSri2
1B. Jaswanthi, Electronics& Computer Engineering, K. L. University, Vijayawada (A.P.), India.
2M. Nainisri, Electronics& Computer Engineering, K. L. University, Vijayawada (A.P.), India.
Manuscript received on April 05, 2013. | Revised Manuscript received on April 11, 2013. | Manuscript published on April 15, 2013. | PP: 84-89 | Volume-1 Issue-5, April 2013. | Retrieval Number: E0247041513/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Today cloud computing has become ubiquitous and we see everybody lot of data being transferred and being accessed from the cloud. At the same time this phenomenon presents us with a great risk of data theft and privacy issues .Among these privacy is the main reason that many companies and also individuals to some extent are avoiding the cloud, which also needs be addressed. For this purpose we are proposing a new model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This report analyses the challenges posed by cloud computing and the standardization work being done by various standards development organizations (SDOs) to mitigate privacy risks in the cloud, including the role of privacy-enhancing technologies (PETs).And a new execution model for confidentiality and privacy in cloud computing, called the Hybrid Execution model. This model provides a seamless way for an organization to utilize their own infrastructure for sensitive, private data and computation, while integrating public clouds for non-sensitive, public data and computation. We outline how to realize this model in one specific execution environment, Map Reduce over Big table.
Keywords: Networks, servers, storage, applications, and services.