Brain storm-based Whale Optimization Algorithm for privacy-protected data publishing in cloud computing

• Published in: Cluster computing Vol. 22; no. Suppl 2; pp. 3521 - 3530
• Main Authors: Thanga Revathi, S., Ramaraj, N., Chithra, S.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.03.2019; Springer Nature B.V
• Subjects: Algorithms; Cloud computing; Computer Communication Networks; Computer Science; Construction; Data encryption; Data structures; Information retrieval; Operating Systems; Optimization; Optimization algorithms; Privacy; Processor Architectures; Retrievable data perturbation; WOA; Cloud computing; Privacy preservation; BSO
• ISSN: 1386-7857; 1573-7543
• DOI: 10.1007/s10586-018-2200-5

Cloud computing serves as a major boost for the digital era since it handles data from a large number of users simultaneously. Besides the several useful characteristics, providing security to the data stored in the cloud platform is a major challenge for the service providers. Privacy preservation schemes introduced in the literature trying to enhance the privacy and utility of the data structures by modifying the database with the secret key. In this paper, an optimization scheme, Brain Storm based Whale Optimization Algorithm (BS-WOA), is introduced for identifying the secret key. The database from the data owner is modified with the optimal secret key for constructing the retrievable perturbation data for preserving the privacy and utility. The proposed BS-WOA is designed through the hybridization of Brain Storm Optimization and Whale Optimization Algorithm. Simulation of the proposed technique with the BS-WOA is done in the three standard databases, such as chess T10I4D100 K, and the retail databases. When evaluated for the key size of 256, the proposed BS-WOA achieved privacy value of 0.186 and utility value of 0.8777 for the chess database, and thus, has improved performance.