基于机器学习的网络大数据安全集成算法研究

Jin-zhou Liu
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引用次数: 1

摘要

为了提高基于融合网络结构的物联网接入控制的大数据管理能力,提出了一种基于机器学习和融合网络结构的物联网接入控制安全集成模型。结合特征分析方法,建立了存储结构分配模型,利用空间节点旋转控制实现了大数据的特征提取和模糊聚类分析,构建了模糊信息融合参数分析模型,实现了频率耦合参数分析,建立了虚拟惯性参数分析模型。并根据机器学习分析结果实现对大数据的集成处理。测试结果表明,该方法具有良好的聚类效果,降低了存储开销,提高了大数据的可靠性管理能力。
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 Network Big Data Security Integration Algorithm Based on Machine Learning
In order to improve the big data management ability of IOT access control based on converged network structure, a security integration model of IOT access control based on machine learning and converged network structure is proposed. Combined with the feature analysis method, the storage structure allocation model is established, the feature extraction and fuzzy clustering analysis of big data are realized by using the spatial node rotation control, the fuzzy information fusion parameter analysis model is constructed, the frequency coupling parameter analysis is realized, the virtual inertia parameter analysis model is established, and the integrated processing of big data is realized according to the machine learning analysis results. The test results show that the method has good clustering effect, reduces the storage overhead, and improves the reliability management ability of big data.
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