Big Data Security Based Framework Using Metaheuristic Approaches in Cloud Environment

摘要

Security is the main concern in Big Data analysis. In the security analysis, most of the approaches that provide an effective security yet uses high amount of resources like memory or storage and time delay in order to increase the cost of processing. This paper emphasis on improvement based on utilization of resources by means of optimization of encryption approach. The optimisation approach uses a convex optimization with minimum amount of time or storage and such factors effects the total cost of processing. The proposed approach uses GWO optimization of Blow fish slices. The experiment involves the use of two types of dataset such as tweet and scientific workflow. The experimental analysis shows how effectively blow fish improves Grey wolf optimization (GWO). In addition, the other experiment uses particle swarm optimization (PSO) and flower pollination approach (FPA). Although the analysis represents that these approaches are not very much effective as compared to GWO.