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Abstract
With the development of Internet technology, the amount of enterprise data has surged and become a core asset. In e-commerce, data security not only protects data, but also affects the ability of transforming data into assets, thus enhancing the competitiveness of enterprises. This study proposes a system framework based on distributed machine learning to enhance data integrity and network security. The system integrates advanced algorithms, effectively processes large-scale data sets, and performs well in cloud image classification tasks. Experiments show that the energy consumption of the system is reduced by 68.92% and the task processing speed is increased by 4.67 times. In addition, the data quality evaluation model is studied to provide decision support for e-commerce enterprises. These innovations provide a new perspective for data asset evaluation and security and also support the application of distributed machine learning in e-commerce.
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Details
1 Finance and Assets Department, State Grid Zhejiang Electric Power Co., Ltd., China
2 Strategy Research Center, Techno-Economic Research Institute of State Grid Zhejiang Electric Power Co., Ltd., China
3 Integrated Service Center, State Grid Zhejiang Electric Power Co., Ltd., China
4 Finance and Assets Department, Huzhou Power Supply Company of State Grid Zhejiang Electric Power Co., Ltd., China