Title: Privacy information encryption for cross-border e-commerce users based on social network analysis

Authors: Na Wang; Feng Gao; Ji Zhang

Addresses: School of Management, Changchun University of Architecture and Civil Engineering, Chang'chun, 130607, China ' School of Art, Changchun University of Architecture and Civil Engineering, Chang'chun, 130607, China ' School of Electrical Engineering, Changchun University of Architecture and Civil Engineering, Chang'chun, 130607, China

Abstract: In order to protect the privacy information of cross-border e-commerce users, an encryption algorithm based on social network analysis is proposed in this paper. Firstly, the logical inference mapping method for blockchain identity data is used to encode public and private keys, and the asymmetric encryption method is applied to construct keys. Then, the social network analysis method is used to rearrange the user social network structure, and the user information fusion processing and optimised encryption are realised with the support of arithmetic coding, homomorphic encryption and other technologies. The simulation results show that this method has strong anti-attack ability and low time cost.

Keywords: social network analysis; cross-border e-commerce; privacy; information encryption; vector quantisation encoding.

DOI: 10.1504/IJNVO.2023.135961

International Journal of Networking and Virtual Organisations, 2023 Vol.29 No.3/4, pp.312 - 327

Received: 21 Apr 2023
Accepted: 06 Aug 2023
Published online: 10 Jan 2024 *

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