AIP Conference Proceedings has published an article written by Rippika Nethravathi, Sravanthi Thota, Sumathi Reddy Institute of Technology for Women, Warangal, India.-506371, S. Naresh Kuma, SR University, Warangal,Telangana, India, Bonthala Prabhanjan Yadav, N. Swathi, Sumathi Reddy Institute of Technology for Women, Warangal, India.-506371, and Ch. Meena, TSWRDCW Kamareddy, Telangana, India.
Abstract: “Data de-duplication would greatly reduce the overhead of cloud computing services for storage and transfer, and it has possible applications in this big data-driven environment. Current systems that de-duplication of data are typically designed either to tackle brute-force threats or increase the accessibility of quality and data, but not all situations. In the context of shortening redundant data disclosure in this publication, we tend to evaluate 3-tier cross-domain architecture, degree program suggest an accurate and confidentiality issues saving big data de-duplication in the cloud, we also tend not to be aware of any current theme that attains authority. Both confidentiality and data de-duplication is accomplished by EPCDD and brute-force attacks are countered. In general, we generally take accountability into evaluation for having greater safeguards of privacy than current schemes. We appear to show that, in terms of computing, interactions and warehousing expenses, EPCDD performs better competitive processes. The dynamic operation user may also perform detailed update, data leakage & restoring through this project. Upon accessing it, the file is sent to the local distributor to verify de-duplication when the document is not reproduced, then the file will be saved on the cloud, and the replica file will obtain evidence of copyright. Authentication process and cross-domain de-duplication of big data in the cloud can be accomplished by this method. In addition, that time complexity of the EPCDD replication search is indexed.“