%0 Journal Article %A KANG Peng %A YANG Wenzhong %A MA Hongqiao %T TLS Malicious Encrypted Traffic Identification Research %D 2022 %R 10.3778/j.issn.1002-8331.2110-0029 %J Computer Engineering and Applications %P 1-11 %V 58 %N 12 %X With the advent of the 5G era and the increasing public awareness of the Internet, the public has paid more and more attention to the protection of personal privacy. Due to malicious communication in the process of data encryption, to ensure data security and safeguard social and national interests, the research work on encrypted traffic identification is particularly important. Therefore, this paper describes the TLS traffic in detail and analyzes the improved technology of early identification method, including common traffic detection technology, DPI detection technology, proxy technology, and certificate detection technology. It also introduces machine learning models for selecting different TLS encrypted traffic characteristics, as well as many recent research results of deep learning models without feature selection. The deficiencies of the related research work are summarized, and the future research work and development trend of the technology have been prospected. %U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2110-0029