| Title | Quantitative matching method for network traffic features |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Hu, Zhihui, Liu, Caiming |
| Conference Name | 2022 18th International Conference on Computational Intelligence and Security (CIS) |
| Date Published | dec |
| Keywords | composability, compositionality, Computational Intelligence, cryptography, heterogeneous networks, Matching Method, network traffic, pubcrawl, Quantitative Matching, security, Segment Calculation, Similarity of Features, Soft sensors, telecommunication traffic |
| Abstract | The heterogeneity of network traffic features brings quantitative calculation problems to the matching between network data. In order to solve the above fuzzy matching problem between the heterogeneous network feature data, a quantitative matching method for network traffic features is proposed in this paper. By constructing the numerical expression method of network traffic features, the numerical expression of key features of network data is realized. By constructing the suitable section calculation methods for the similarity of different network traffic features, the personalized quantitative matching for heterogeneous network data features is realized according to the actual meaning of different features. By defining the weight of network traffic features, the quantitative importance value of different features is realized. The weighted sum mathematical method is used to accurately calculate the overall similarity value between network data. The effectiveness of the proposed method through experiments is verified. The experimental results show that the proposed matching method can be used to calculate the similarity value between network data, and the quantitative calculation purpose of network traffic feature matching with heterogeneous features is realized. |
| DOI | 10.1109/CIS58238.2022.00089 |
| Citation Key | hu_quantitative_2022 |
Quantitative matching method for network traffic features