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.
Men et al. (Wed,) studied this question.