Research Article
Research on Anomaly Monitoring Algorithm of Uncertain Large Data Flow Based on Artificial Intelligence
@INPROCEEDINGS{10.1007/978-3-030-36405-2_12, author={Shuang-cheng Jia and Feng-ping Yang}, title={Research on Anomaly Monitoring Algorithm of Uncertain Large Data Flow Based on Artificial Intelligence}, proceedings={Advanced Hybrid Information Processing. Third EAI International Conference, ADHIP 2019, Nanjing, China, September 21--22, 2019, Proceedings, Part II}, proceedings_a={ADHIP PART 2}, year={2019}, month={11}, keywords={Artificial intelligence Uncertain large data stream Anomaly monitoring Clustering}, doi={10.1007/978-3-030-36405-2_12} }- Shuang-cheng Jia
Feng-ping Yang
Year: 2019
Research on Anomaly Monitoring Algorithm of Uncertain Large Data Flow Based on Artificial Intelligence
ADHIP PART 2
Springer
DOI: 10.1007/978-3-030-36405-2_12
Abstract
In order to improve the monitoring ability of uncertain large data stream, an uncertain large data flow monitoring algorithm based on artificial intelligence is proposed. The collected uncertain big data flow is constructed by low dimensional feature set, and the rough set model of uncertain large data stream distribution is constructed. The fuzzy C-means clustering method is used to analyze the uncertain big data flow by fusion clustering and adaptive grid partition analysis. All the abnormal samples of large data stream are sampled and trained, and the feature quantities of association rules of uncertain large data stream are extracted. Combined with artificial intelligence method, the monitoring of uncertain large data stream is realized. The simulation results show that the method has high accuracy and good ability to resist abnormal traffic interference, and the traffic security monitoring ability of the network is improved.
