partially funded by the National Natural Science Foundation of China (No. 61272447);the National Entrepreneurship&Innovation Demonstration Base of China (No. C700011);the Key Research&Development Project of Sichuan Province of China (No.2018G20100)。
Botnets based on the Domain Generation Algorithm(DGA) mechanism pose great challenges to the main current detection methods because of their strong concealment and robustness. However, the complexity of the DGA family...
partially funded by the National Natural Science Foundation of China (Grant No. 61272447);National Entrepreneurship & Innovation Demonstration Base of China (Grant No. C700011);Key Research & Development Project of Sichuan Province of China (Grant No. 2018G20100)
The limited labeled sample data in the field of advanced security threats detection seriously restricts the effective development of research work.Learning the sample labels from the labeled and unlabeled data has rec...
supported by the National Natural Science Foundation of China (No. 61272447);Sichuan Province Science and Technology Planning (Nos. 2016GZ0042, 16ZHSF0483, and 2017GZ0168);Key Research Project of Sichuan Provincial Department of Education (Nos. 17ZA0238 and 17ZA0200);Scientific Research Staring Foundation for Young Teachers of Sichuan University (No. 2015SCU11079)
Extracting and analyzing network traffic feature is fundamental in the design and implementation of network behavior anomaly detection methods. The traditional network traffic feature method focuses on the statistical...