Title: Privacy protection algorithms in mobile network design and innovation: enhancing security in next-generation wireless communication

Authors: Lili Qiu

Addresses: School of Laboratory and Equipment Management Office, Zhengzhou University of Science and Technology, Zhengzhou, Henan, 450064, China

Abstract: The integration of block chain technology into e-commerce has successfully addressed several critical challenges, including the lack of transaction transparency, potential data security risks, and high payment costs. Mobile edge computing (MEC) enhances block chain functionality by providing computational power while simultaneously meeting the stringent requirements for high real-time performance and low latency in e-commerce transaction systems. However, certain limitations persist within MEC-enabled e-commerce consortium block chains, such as breaches of user privacy, vulnerabilities in consensus algorithms, and other security concerns. This study proposes a secure transaction model specifically designed for MEC-enabled e-commerce consortium block chains. The proposed model employs a lightweight encryption algorithm to ensure the confidentiality of user information and transaction data, thereby preventing unauthorised disclosures. The simulation results indicate that the proposed solution effectively reduces classification accuracy from 91.1% to 1.42%, with only a 0.17% padding overhead when applied to a real dataset.

Keywords: TP; true positive; MCS; mobile crowd sensing; GAN; generative adversarial networks; SDK; software development kit; FN; false negative; TTAS; target tracking area selection; AHP; anonymous handover protocol.

DOI: 10.1504/IJMNDI.2026.152392

International Journal of Mobile Network Design and Innovation, 2026 Vol.12 No.1, pp.1 - 10

Received: 07 Mar 2025
Accepted: 07 May 2025
Published online: 18 Mar 2026 *

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