Encrypted Traffic Classification

Encrypted traffic classification (ETC) aims to identify the applications or services used within encrypted network traffic, a crucial task for network security and management given the widespread adoption of encryption. Current research focuses on improving the accuracy and efficiency of ETC using machine learning (ML) and deep learning (DL) models, including transformers, graph neural networks, and ensemble methods, often incorporating techniques like data augmentation, contrastive learning, and hyperparameter optimization to address challenges posed by limited labeled data and evolving traffic patterns. Advances in ETC have significant implications for network security, enabling improved threat detection, quality of service management, and resource allocation, while also informing the development of more robust and adaptable security systems.

Papers

August 20, 2024

ETGuard: Malicious Encrypted Traffic Detection in Blockchain-based Power Grid Systems
Peng Zhou, Yongdong Liu, Lixun Ma, Weiye Zhang, Haohan Tan, Zhenguang Liu, Butian Huang
Smart Grid Malicious Client Encrypted Traffic Encrypted Traffic Classification

July 23, 2024

Enhancing Encrypted Internet Traffic Classification Through Advanced Data Augmentation Techniques
Yehonatan Zion, Porat Aharon, Ran Dubin, Amit Dvir, Chen Hajaj
Data Augmentation Data Augmentation Technique Traffic Classification Encrypted Traffic Encrypted Traffic Classification

June 3, 2024

Non-uniformity is All You Need: Efficient and Timely Encrypted Traffic Classification With ECHO
Shilo Daum, Tal Shapira, Anat Bremler-Barr, David Hay
Hyperparameter Optimization Non Uniform Encrypted Traffic Classification Fast Classification Traffic Representation Hyperparameter OPtimization

March 17, 2024

CBR -- Boosting Adaptive Classification By Retrieval of Encrypted Network Traffic with Out-of-distribution
Amir Lukach, Ran Dubin, Amit Dvir, Chen Hajaj
Deep Learning App to App Retrieval Distribution Data Encrypted Traffic Encrypted Traffic Classification Adaptive Classification Real Time Classification

February 12, 2024

One Train for Two Tasks: An Encrypted Traffic Classification Framework Using Supervised Contrastive Learning
Haozhen Zhang, Xi Xiao, Le Yu, Qing Li, Zhen Ling, Ye Zhang
New Task Supervised Contrastive Learning High Speed Train System Discrete Representation Traffic Classification Temporal Encoder Encrypted Traffic Classification Packet Level

August 31, 2023

Listen to Minority: Encrypted Traffic Classification for Class Imbalance with Contrastive Pre-Training
Xiang Li, Juncheng Guo, Qige Song, Jiang Xie, Yafei Sang, Shuyuan Zhao, Yongzheng Zhang
Class Imbalance Encrypted Traffic Classification Heterogeneous Traffic Minority Inclusion Vehicle Flow

August 4, 2023

AutoML4ETC: Automated Neural Architecture Search for Real-World Encrypted Traffic Classification
Navid Malekghaini, Elham Akbari, Mohammad A. Salahuddin, Noura Limam, Raouf Boutaba, Bertrand Mathieu, Stephanie Moteau, Stephane Tuffin
Deep Learning Online autoML Traffic Classification Encrypted Traffic Encrypted Traffic Classification

July 31, 2023

TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic Classification
Haozhen Zhang, Le Yu, Xi Xiao, Qing Li, Francesco Mercaldo, Xiapu Luo, Qixu Liu
Graph Neural Network Traffic Classification Temporal Encoder M2m GNN Encrypted Traffic Classification

May 21, 2023

Many or Few Samples? Comparing Transfer, Contrastive and Meta-Learning in Encrypted Traffic Classification
Idio Guarino, Chao Wang, Alessandro Finamore, Antonio Pescape, Dario Rossi
Deep Learning Contrastive Learning Transfer Learning Formality Transfer Traffic Classification Machine Learning Library Encrypted Traffic Classification

September 2, 2022

Tweaking Metasploit to Evade Encrypted C2 Traffic Detection
Gonçalo Xavier, Carlos Novo, Ricardo Morla
Backdoor Attack Encrypted Traffic Classification Structural Attack

June 16, 2022

When a RF Beats a CNN and GRU, Together -- A Comparison of Deep Learning and Classical Machine Learning Approaches for Encrypted Malware Traffic Classification
Adi Lichy, Ofek Bader, Ran Dubin, Amit Dvir, Chen Hajaj
Deep Learning CNN Network Intrusion Detection Traffic Classification Malware Family Classical Machine Learning Novel RF Editing Pipeline Malicious Traffic Encrypted Traffic Classification

May 11, 2022

Extensible Machine Learning for Encrypted Network Traffic Application Labeling via Uncertainty Quantification
Steven Jorgensen, John Holodnak, Jensen Dempsey, Karla de Souza, Ananditha Raghunath, Vernon Rivet, Noah DeMoes, Andrés Alejos, Allan Wollaber
Uncertainty Quantification Encrypted Traffic Encrypted Traffic Classification

March 25, 2022

Deep Learning for Encrypted Traffic Classification and Unknown Data Detection
Madushi H. Pathmaperuma, Yogachandran Rahulamathavan, Safak Dogan, Ahmet M. Kondoz, Rongxing Lu
Deep Learning Deep Neural Network Encrypted Traffic Classification Unknown Detection

February 24, 2022

Fine-grained TLS services classification with reject option
Jan Luxemburk, Tomáš Čejka
Network Flow Encrypted Traffic Encrypted Traffic Classification Reject Option Packet Level

February 13, 2022

ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic Classification
Xinjie Lin, Gang Xiong, Gaopeng Gou, Zhen Li, Junzheng Shi, Jing Yu
Transformer Megatron Decepticons Contextual Representation Bidirectional Encoder Representation Traffic Classification Encrypted Traffic Classification Traffic Representation

Encrypted Traffic Classification

Papers

ETGuard: Malicious Encrypted Traffic Detection in Blockchain-based Power Grid Systems

Enhancing Encrypted Internet Traffic Classification Through Advanced Data Augmentation Techniques

Non-uniformity is All You Need: Efficient and Timely Encrypted Traffic Classification With ECHO

CBR -- Boosting Adaptive Classification By Retrieval of Encrypted Network Traffic with Out-of-distribution

One Train for Two Tasks: An Encrypted Traffic Classification Framework Using Supervised Contrastive Learning

Listen to Minority: Encrypted Traffic Classification for Class Imbalance with Contrastive Pre-Training

AutoML4ETC: Automated Neural Architecture Search for Real-World Encrypted Traffic Classification

TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic Classification

Many or Few Samples? Comparing Transfer, Contrastive and Meta-Learning in Encrypted Traffic Classification

Tweaking Metasploit to Evade Encrypted C2 Traffic Detection

When a RF Beats a CNN and GRU, Together -- A Comparison of Deep Learning and Classical Machine Learning Approaches for Encrypted Malware Traffic Classification

Extensible Machine Learning for Encrypted Network Traffic Application Labeling via Uncertainty Quantification

Deep Learning for Encrypted Traffic Classification and Unknown Data Detection

Fine-grained TLS services classification with reject option

ET-BERT: A Contextualized Datagram Representation with Pre-training Transformers for Encrypted Traffic Classification