USTC-TFC2016

For more information about this dataset, please refer to: 1) Wei Wang， Ming Zhu， Xuewen Zeng， Xiaozhou Ye and Yiqiang Sheng， “Malware traffic classification using convolutional neural network for representation learning”ICOIN 2017，pp712-717; 2) Wang Wei, Research on Network Traffic Classification and Anomaly Detection

Methods

Based on Deep Learning, Ph.D. Thesis, University of Science and Technology of China, 2018. This dataset and preprocessing tool were released in 2018 github.com/echowei/ Many domestic and foreign researchers are using this dataset. Due to bandwidth and capacity constraints, it is often unable to download.

Upload it to the "Science Database" website of the Chinese Academy of Sciences for long-term storage and easy download. At the same time, we look forward to relevant researchers uploading and sharing new malicious traffic and encrypted traffic using domestic cryptographic protocols, as well as expanding this dataset to include more types of malicious and normal traffic (such as 100 each), forming a richer and more comprehensive dataset to approach the actual network traffic situation.