Title: An improved privacy aware secure multi-cloud model with proliferate ElGamal encryption for big data storage

Authors: G. Prabu Kanna; V. Vasudevan

Addresses: Department of Information Technology, Kalasalingam Academy of Research and Education, Krishnankoil, Tamil Nadu, India ' Department of Information Technology, Kalasalingam Academy of Research and Education, Krishnankoil, Tamil Nadu, India

Abstract: The isolation of sensitive attributes in the customer profile and the uploading of encrypted data to the multi-server-based cloud are the major issues in the existing applications. This paper proposes the novel rule-based statistical disclosure method (RSDM) and access control policy-based access restriction (ACPAR) to integrate the activities of sensitive attribute prediction and the data uploading stages in cloud computing. Initially, the normalisation based on the hide and visibility metric assignment to the fields in the dataset used to isolate the sensitive and normal attributes in the customer profile. Then, the data encryption is performed through proliferate ElGamal algorithm sequentially and stored into the cloud. The RSDM serves as the base for sensitive data isolation. Then, the access control policy is designed to control the profile-viewing ability to assure the security. The proposed work decrypts the data associated with the denormalised profile for integrity.

Keywords: big data storage; security; rule-based statistical disclosure control; RSDC method; multi-cloud model; proliferate ElGamal encryption and decryption; cloud service provider; CSP; access control policy.

DOI: 10.1504/IJICS.2022.121288

International Journal of Information and Computer Security, 2022 Vol.17 No.1/2, pp.1 - 20

Received: 17 Aug 2018
Accepted: 26 Jan 2019

Published online: 04 Mar 2022 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article