Machine Learning for Encrypted Malicious Traffic Detection: Approaches, Datasets and Comparative Study

17 March 2022

Papers citing "Machine Learning for Encrypted Malicious Traffic Detection: Approaches, Datasets and Comparative Study"

8 / 8 papers shown

Title
Network Attack Traffic Detection With Hybrid Quantum-Enhanced Convolution Neural Network Zihao Wang K. Fok V. Thing 34 0 0 29 Apr 2025
Leveraging Machine Learning Techniques in Intrusion Detection Systems for Internet of Things Saeid Jamshidi Amin Nikanjam Nafi Kawser Wazed Foutse Khomh 29 0 0 09 Apr 2025
Exploring Emerging Trends in 5G Malicious Traffic Analysis and Incremental Learning Intrusion Detection Strategies Zihao Wang K. Fok V. Thing 25 2 0 22 Feb 2024
Feature Analysis of Encrypted Malicious Traffic A. S. Shekhawat Fabio Di Troia Mark Stamp AAML 16 56 0 06 Dec 2023
Feature Mining for Encrypted Malicious Traffic Detection with Deep Learning and Other Machine Learning Algorithms Zihao Wang V. Thing 14 25 0 07 Apr 2023
A Multi-Agent Adaptive Deep Learning Framework for Online Intrusion Detection Mahdi Soltani Khashayar Khajavi M. J. Siavoshani A. Jahangir 18 7 0 05 Mar 2023
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 A. Dvir Chen Hajaj 24 29 0 16 Jun 2022
An Adaptable Deep Learning-Based Intrusion Detection System to Zero-Day Attacks Mahdi Soltani Behzad Ousat M. J. Siavoshani A. Jahangir AAML 13 42 0 20 Aug 2021