An Efficient Framework for Information Security in Cloud Computing Using Auditing Algorithm Shell (AAS)
International Journal of Computer Science and Information Security (IJCSIS), Vol. 14, No. 11, November 2016 There is a dynamic escalation and extension in the new infrastructure, educating personnel and licensing new computer programs in the field of IT, due to the emergence of Cloud Computing (CC)...
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Zusammenfassung: | International Journal of Computer Science and Information Security
(IJCSIS), Vol. 14, No. 11, November 2016 There is a dynamic escalation and extension in the new infrastructure,
educating personnel and licensing new computer programs in the field of IT, due
to the emergence of Cloud Computing (CC) paradigm. It has become a quick
growing segment of IT business in last couple of years. However, due to the
rapid growth of data, people and IT firms, the issue of information security is
getting more complex. One of the major concerns of the user is, at what degree
the data is safe on Cloud? In spite of all promotional material encompassing
the cloud, consortium customers are not willing to shift their business on the
cloud. Data security is the major problem which has limited the scope of cloud
computing. In new cloud computing infrastructure, the techniques such as the
Strong Secure Shell and Encryption are deployed to guarantee the authenticity
of the user through logs systems. The vendors utilize these logs to analyze and
view their data. Therefore, this implementation is not enough to ensure
security, privacy and authoritative use of the data. This paper introduces quad
layered framework for data security, data privacy, data breaches and process
associated aspects. Using this layered architecture we have preserved the
secrecy of confidential information and tried to build the trust of user on
cloud computing. This layered framework prevents the confidential information
by multiple means i.e. Secure Transmission of Data, Encrypted Data and its
Processing, Database Secure Shell and Internal/external log Auditing. |
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DOI: | 10.48550/arxiv.1702.07140 |