A Secure Data Classification Model for achieving Data Confidentiality and Integrity in Cloud Environment
Journal Title: International Journal on Computer Science and Engineering - Year 2016, Vol 8, Issue 9
Abstract
Cloud computing offers numerous benefits including scalability, availability and many services. It needs to address three main security issues: confidentiality, integrity and availability. It is on demand and pay per use service. But as this new technology expanding it also discovers new risks and vulnerabilities too. Security of the data in cloud computing is still an ultimatum to be achieved. The data owners must place their confidential information into the public cloud servers which are not within their trusted domains. Hence, security and privacy of knowledge is the major concern within the cloud computing. To overcome this, various security aspects of security issues has been analyzed and then a framework to mitigate security issues at the level authentication and storage level in cloud computing is proposed in this paper. Deciding data security approach for the data without understanding the security needs of the data is not a valid technical approach. Before applying any security on data in cloud, it is best to know the security needs of the data. That is, whether that kind of data need security or not. In this a data classification approach based on data confidentiality is proposed. The aim of classification technique is to classify the data based on the security needs into two classes confidential and nonconfidential. The proposed approach identifies that part of the dataset which must be encrypted using machine learning algorithm and other doesn’t which will save time and cost of privacy preserving. After that efficient security mechanisms should be deployed by means of encryption, authentication, and authorization or by some other method to ensure the privacy of consumer’s data on cloud storage.
Authors and Affiliations
Kulwinder Kaur , Vikas Zandu
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