Research on secure and trustworthy cross domain collaborative computing methods for data

Xinlin Liu; Jian Zhang; Wei Deng

doi:10.1117/12.3032067

8 June 2024 Research on secure and trustworthy cross domain collaborative computing methods for data

Xinlin Liu, Jian Zhang, Wei Deng

Proceedings Volume 13171, Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024); 131710S (2024) https://doi.org/10.1117/12.3032067
Event: 3rd International Conference on Algorithms, Microchips and Network Applications (AMNA 2024), 2024, Jinan, China

Abstract

With the advancement of mobile cloud computing technology, the demand for collaborative operation and maintenance technology is constantly increasing. Therefore, this article proposes a model that combines multi feature collaborative knowledge graph and blockchain technology to achieve secure and trustworthy collaborative operation and maintenance computing in cross domain environments. The model focuses on addressing data privacy and security issues, and improving the accuracy of collaborative operations. By introducing a multi feature collaborative knowledge graph, secure fusion of multi-source feature data can be achieved. Meanwhile, design a blockchain based trust verification mechanism to ensure the traceability of anonymous data sources, prevent data tampering, and ensure data authenticity. In addition, an adaptive recommendation algorithm based on MKGCN is proposed, which utilizes multi feature collaborative knowledge graph data to achieve secure and accurate collaborative computing. The experimental results show that this method improves the accuracy of recommendation calculation while ensuring privacy and security, promoting the development and practical application of cross domain operation and maintenance computing technology.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xinlin Liu, Jian Zhang, and Wei Deng "Research on secure and trustworthy cross domain collaborative computing methods for data", Proc. SPIE 13171, Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024), 131710S (8 June 2024); https://doi.org/10.1117/12.3032067

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