A Comprehensive Evaluation of GWO and FHE in Achieving Security and Privacy for Big Data

In light of the fast-paced development of big data applications, ensuring security and privacy in the processing of large-scale data has become a critical concern. The paper proposes a novel approach with the aim of improving security and privacy in big data processing by combining the Grey Wolf Optimization (GWO) algorithm with the Fully Homomorphic Encryption (FHE) scheme. The GWO algorithm is utilized for optimizing the allocation and distribution of data across multiple computing nodes, while the FHE scheme is utilized for data encryption and performs computations on the encrypted data without revealing sensitive information. By leveraging the GWO algorithm, the proposed approach aims to optimize the data allocation process, ensuring efficient utilization of computing resources while maintaining data confidentiality. Furthermore, the integration of the FHE scheme facilitates the secure computation on encrypted data, thereby protecting the privacy of sensitive information. The findings of research Contribute to the progress of secure and privacy-preserving techniques in the field of big data processing, creating opportunities for the rise of additional secure and privacy-aware systems in the future.