Optimizing Cloud Data Security: Leveraging Homomorphic Encryption and Cuckoo Search Algorithm

Therefore, the following research proposal to develop an enhanced cloud data security using Homomorphic Encryption and Cuckoo Search Algorithm. While using cloud computing environment increases, how to protect the security of data during the storing and computation is still a challenge. They deal with computation processes that can be carried out on encrypted information with aer modifying the content while still preserving confidentiality. However, its major drawback is high complexity in the computation process which may limit its applicability in large-scale clouds. To help address this problem, the Cuckoo Search Algorithm is presented as an optimization tool that mimics nature. The proposed work is derived from an optimization that is carried out using the Cuckoo Search Algorithm in order to enhance key management as well as the general encryption/decryption period and computational complexity of homomorphic encryption. This integration results in a reduction of the overhead cost of performing encryption while at the same time making it more secure. In this project the developed system is to offer a large-scale, modular and secure application paradigm particularly for data storage and processing, machine learning or similar tasks on the cloud. Through the use of both privacy-preserving homomorphic encryption and the optimization features of the Cuckoo Search Algorithm the project combines data confidentiality with productivity delivering a solution of cloud computing that improves security in sectors like healthcare, finance, and government.