研究安全可信的跨域数据协作计算方法

Xinlin Liu, Jian Zhang, Wei-Ping Deng
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引用次数: 0

摘要

随着移动云计算技术的发展,人们对协同运维技术的需求不断增加。因此,本文提出了一种结合多特征协同知识图谱和区块链技术的模型,以实现跨域环境下安全可信的协同运维计算。该模型重点解决数据隐私和安全问题,提高协同操作的准确性。通过引入多特征协同知识图谱,可以实现多源特征数据的安全融合。同时,设计基于区块链的信任验证机制,确保匿名数据源的可追溯性,防止数据被篡改,保证数据的真实性。此外,还提出了一种基于MKGCN的自适应推荐算法,利用多特征协同知识图谱数据实现安全、精准的协同计算。实验结果表明,该方法在保证隐私和安全的前提下,提高了推荐计算的准确性,促进了跨域运维计算技术的发展和实际应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on secure and trustworthy cross domain collaborative computing methods for data
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.
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