Title: A fast encryption method of large enterprise financial data based on adversarial neural network

Authors: Youwei Chu

Addresses: Department of Economics and Management, Harbin University, Harbin, 150086, China

Abstract: In order to overcome the high time cost of encrypting, decrypting and revocation attribute calculation existing in traditional encryption methods of financial data of large enterprises, this paper proposes a fast encryption method of financial data of large enterprises based on adversarial neural network. Adversarial neural network is used to build the financial data reorganisation model of large enterprises, and obtain the sparse and local characteristics of the reorganised financial data of large enterprises, so as to generate the encrypted initial key and sub-key, and complete the fast encryption of the financial data of large enterprises by combining matrix transformation. The simulation results show that the average time cost of encryption is 0.115 s, the average time cost of decryption is 0.05 s, and the average time cost of undo calculation is 0.616 s, which can realise the fast encryption of financial data of large enterprises.

Keywords: adversarial neural network; data encryption; enterprise financial data.

DOI: 10.1504/IJISE.2023.132269

International Journal of Industrial and Systems Engineering, 2023 Vol.44 No.3, pp.302 - 315

Received: 10 Jun 2021
Accepted: 20 Jul 2021
Published online: 14 Jul 2023 *

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