Secured Storage of Big Data in Cloud
Melbin J Reena1, A. Shajin Nargunam2

1Melbin J Reena, Research Scholar, Noorul Islam Centre for Higher Education, Kumaracoil (Tamil Nadu), India.
2Dr. A. Shajin Nargunam, Director Academics, Noorul Islam Centre for Higher Education Kumaracoil (Tamil Nadu), India.
Manuscript received on 16 July 2019 | Revised Manuscript received on 01 August 2019 | Manuscript Published on 10 August 2019 | PP: 6-10 | Volume-8 Issue-2S3 July 2019 | Retrieval Number: B10020782S319/2019©BEIESP | DOI: 10.35940/ijrte.B1002.0782S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: Big Data refers to large volume of data and necessitates the usage of cloud for storage and processing. Cloud tenants data is not only stored in the cloud, but it is also shared among multiple users. The data stored in cloud must be well protected as it is prone to malicious attacks and hardware failures. Also, user’s data on cloud contain sensitive information that must be protected and highly restricted from unauthorized access. Cloud deployment models such as public cloud, private cloud, and hybrid cloud can be used for storing data of cloud tenants. This paper proposes a secured storage approach for protecting data in cloud by partitioning big dataset into blocks containing user’s sensitive data, insensitive data, and public data. Sensitive data is moved to private cloud and is well protected using proxy re encryption. Insensitive data is stored in public cloud and some data blocks are randomly encrypted. Also, the storage index information of insensitive data blocks on cloud is encrypted and shared among authorized users. Public data is also moved to public cloud and to protect it the storage path information is only encrypted and shared. The proposed approach shows better results with reduced computation overhead and improved security.
Keywords: Big Data, Proxy Re-encryption, Storage Path, Cloud Storage, Sensitive Data.
Scope of the Article: Big Data Security