Title: Block level time variant dynamic encryption algorithm for improved cloud security and de-duplication using block level topical similarity

Authors: S. Sabeetha Saraswathi; N. Malarvizhi

Addresses: Department of CSE, School of Computing, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, 400 Feet Outer Ring Road, Avadi, Chennai, Tamil Nadu 600062, India ' Department of CSE, School of Computing, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, 400 Feet Outer Ring Road, Avadi, Chennai, Tamil Nadu 600062, India

Abstract: The problem of security and memory management has been well studied. A number of approaches has been discussed for the data security in cloud environment. However, the method does not produce higher security and introduces higher data duplication in the cloud which affects the data management performance. To overcome these issues, an efficient block level encryption and de-duplication scheme has been presented in this paper. The method represents the data into a number of blocks and stores them in the cloud storage. For each block considered, a dynamic encryption/decryption keys has been generated at each time window. The user has been validated with different public/private key approach. For the data access, the algorithm generates different keys for different blocks which restrict the access of users. Based on the key being generated, the data has been encrypted by the system to be decrypted by the cloud user upon access. The method maintains a block key table which contains the keys to be used for the particular time window. The method produces higher efficient results on data security and improves the performance of data management.

Keywords: cloud computing; data security; block level encryption; time variant keys; deduplication; block level topical similarity; BLTS.

DOI: 10.1504/IJAIP.2021.116360

International Journal of Advanced Intelligence Paradigms, 2021 Vol.19 No.3/4, pp.271 - 283

Received: 29 Mar 2018
Accepted: 25 Apr 2018

Published online: 09 Jul 2021 *

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