| Title | Research on Network Big Data Security Integration Algorithm Based on Machine Learning |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Liu, Jin-zhou |
| Conference Name | 2021 International Conference of Social Computing and Digital Economy (ICSCDE) |
| Keywords | Access Control, Analytical models, Big Data, composability, feature extraction, fuzzy clustering, machine learning, Network big data, privacy, pubcrawl, resilience, Resiliency, Security integration, social computing, statistical analysis |
| Abstract | 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. |
| DOI | 10.1109/ICSCDE54196.2021.00067 |
| Citation Key | liu_research_2021 |
Research on Network Big Data Security Integration Algorithm Based on Machine Learning