SHAPE: A Simultaneous Header and Payload Encoding Model for Encrypted Traffic Classification

Many end-to-end deep learning algorithms seeking to classify malicious traffic and encrypted traffic have been proposed in recent years. End-to-end deep learning algorithms require a large number of samples to train a model. However, it is hard for existing methods fully utilizing the heterogeneous...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	IEEE eTransactions on network and service management Ročník 20; číslo 2; s. 1993 - 2012
Hlavní autori:	Dai, Jianbang, Xu, Xiaolong, Gao, Honghao, Wang, Xinheng, Xiao, Fu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.06.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms autoencoder Classification Classification algorithms Coders Coding Deep learning deep metric learning encrypted traffic Feature extraction Machine learning Payloads Shape Task analysis Traffic classification Traffic models transformer Transformers
ISSN:	1932-4537, 1932-4537
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!