Nature inspired computational intelligence implementation for privacy preservation in MapReduce framework. (25th August 2020)

• Record Type: Journal Article
• Authors: Madan, Suman; Goswami, Puneet
• Is Part Of: International journal of intelligent information and database systems. Volume 13:Number 2/4(2020)
• Page Start: 191
• Page End: 207
• Publication Date: 2020-08-25
• Subjects: privacy preservation -- grey wolf optimiser -- cat swarm optimisation; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

Abstract

The next generation technologies made huge impact on the extent of data usage and motivated researches in data-management field along-with the advances in the automation in machine-human interactions. Cloud data storage plays significant role in handling big data. However, data security and data privacy-preservation are still very challenging issues. Several techniques are developed to do privacy preservation keeping in mind the data utility and data obfuscation; however, the trade-off among the privacy of data and its utility is not properly tackled. To solve many optimisation problems, the current trend is use of nature-inspired optimisation algorithms. This paper proposes implementation of two nature inspired optimisation algorithms; cat swarm optimisation and grey wolf optimiser; along with adaptation of k-anonymisation criteria in the MapReduce framework for achieving privacy preservation goal. A fitness function is defined that maintains trade-off between privacy and utility of information given to end-user. Comparative analysis of proposed technique with established techniques is done on parameters: classification accuracy and information loss.