Research Article
Research on Anonymous Reconstruction Method of Multi-serial Communication Information Flow Under Big Data
@INPROCEEDINGS{10.1007/978-3-030-67874-6_6, author={Ying Li and Feng Jin and Xiao-xia Xie and Bing Li}, title={Research on Anonymous Reconstruction Method of Multi-serial Communication Information Flow Under Big Data}, 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={Large data Information flow Multi-serial communication Reconstruction method Anonymous}, doi={10.1007/978-3-030-67874-6_6} }- Ying Li
Feng Jin
Xiao-xia Xie
Bing Li
Year: 2021
Research on Anonymous Reconstruction Method of Multi-serial Communication Information Flow Under Big Data
ADHIP PART 2
Springer
DOI: 10.1007/978-3-030-67874-6_6
Abstract
The existing methods of dynamic reconfiguration of network information flow have some drawbacks, such as security, reliability and bad influence on the performance of the original network. Therefore, an anonymous reconfiguration method of multi-serial communication information flow under large data is proposed. Firstly, the original information flow is acquired in the communication network, and the cooperative filtering of multi-serial communication is carried out. After filtering, the notification information of relay nodes is obtained in the information flow, and the communication status of the information flow is extracted. The characteristic information of the information flow is reconstructed and anonymized. Finally, the anonymous reconstruction of multi-serial communication information flow is completed. By analyzing and comparing the experimental results, it can be seen that the method proposed in this paper is superior to the traditional method in terms of both the effect of anonymity and the efficiency of operation when reconstructing the anonymous information flow of multi-serial communication, it effectively solves the shortcomings of traditional methods, such as poor anonymous effect of information flow and slow speed of information flow reconstruction. It shows that the method has a high degree of anonymity and has a strong practicability.
