A Novel Data Privacy-Preserving Protocol for Multi-data Users by using genetic algorithm.

In this research paper, the proposed work is to put forward a Novel Data Privacy-Preserving Protocol (NDPPP) for Multi-data Users by using genetic algorithm. The data owner outsources the files in the encrypted format to the cloud. The data users can efficiently download the encrypted files from the cloud service provider without any loss of data. To provide this facility, there are certain existing mechanisms in the literature. But the existing mechanisms will result high computation complexity. By means of minimizing the computation complexity, a NDPPP for multi-data users is proposed using genetic algorithm in this research work. Genetic algorithms are usually used to produce high-quality resolutions for optimization. A new trapdoor function is proposed to preserve the data privacy by using our Data Privacy-Preserving Protocol. With the aim of avoiding numerous attacks, a secure authentication protocol is moreover developed between the trusted third party and data user. Additionally, the security is improved. Provided the leakage of data, loss of data as well as the data modification can also be avoided. The proposed work is implemented, and the implementation results of NDPPP illustrate that our protocol is efficient through computation and communication complexity. Moreover, the proposed work NDPPP is secure against various attacks like impersonation attack, eavesdropping, man-in-the-middle attack as well as replay attack. [ABSTRACT FROM AUTHOR]