Title: Anti-tampering method of private data in industrial internet for intelligent manufacturing

Authors: Yafan Men; Jie Lu

Addresses: Department of Software Technology, Zhengzhou Vocational College of Industrial Safety, Zhengzhou, 451192, China ' Department of Computer Technology, Henan Information Engineering School, Zhengzhou, 450011, China

Abstract: In order to improve the integrity of industrial internet privacy data and reduce the tamper response time, an intelligent manufacturing oriented industrial internet privacy data tamper prevention method was proposed. Firstly, in the context of intelligent manufacturing, through association rule mining methods, analyse the characteristics and relationships of industrial internet privacy datasets, and mine industrial internet privacy data. Secondly, through sparse fraction method and L1 norm minimisation strategy, key features of industrial internet privacy data are extracted, and feature selection process is optimised to improve the accuracy and efficiency of data processing. Finally, by deploying monitoring scripts, encryption processing and key generation algorithms, an industrial internet privacy data tamper prevention system is built to ensure data integrity, improve security, and prevent unauthorised tampering. The experimental results show that compared to existing tamper proof methods, the data integrity of our method is higher and the response time is the shortest.

Keywords: intelligent manufacturing; industrial internet; privacy data; anti-tampering.

DOI: 10.1504/IJISTA.2025.151545

International Journal of Intelligent Systems Technologies and Applications, 2025 Vol.23 No.4, pp.395 - 408

Received: 02 Sep 2024
Accepted: 30 Oct 2024
Published online: 05 Feb 2026 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article