Research Article
Network Dynamic Bad Information Security Filtering Algorithms Based on Large Data Analysis
@INPROCEEDINGS{10.1007/978-3-030-67874-6_11, author={Wenchao Zheng and Yin-zhu Cheng and Ze-yu Zhang and Yong-qing Miao}, title={Network Dynamic Bad Information Security Filtering Algorithms Based on Large Data Analysis}, proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part II}, proceedings_a={ADHIP PART 2}, year={2021}, month={1}, keywords={Big data Network dynamics Bad information Filtering}, doi={10.1007/978-3-030-67874-6_11} }- Wenchao Zheng
Yin-zhu Cheng
Ze-yu Zhang
Yong-qing Miao
Year: 2021
Network Dynamic Bad Information Security Filtering Algorithms Based on Large Data Analysis
ADHIP PART 2
Springer
DOI: 10.1007/978-3-030-67874-6_11
Abstract
In view of the low filtering accuracy of traditional bad information in the massive data environment, the security filtering algorithm of network dynamic bad information is innovated and improved in the big data environment. Combining the data set analysis algorithm with the grey statistics theory, this paper evaluates the dynamic information security status of the network structure, extracts the information security features in the evaluation results, compares the data features in the network structure, detects the dynamic time domain range of bad information, and filters and corrects the information in the time domain by nodes and channels, so as to realize the security of the dynamic bad information of the network The experimental results show that the dynamic bad network information security filtering algorithm based on big data analysis is more accurate and effective than the traditional algorithm, with high accuracy and the shortest time, and can be used in the network dynamic bad information security effectively, which meets the research requirements.
