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Found 5 papers, 2 papers with code
CBR - Boosting Adaptive Classification By Retrieval of Encrypted Network Traffic with Out-of-distribution
To summarize, the new method is a real-time classification, which can classify new classes without retraining.
Open-Source Framework for Encrypted Internet and Malicious Traffic Classification
Internet traffic classification plays a key role in network visibility, Quality of Services (QoS), intrusion detection, Quality of Experience (QoE) and traffic-trend analyses.
When a RF Beats a CNN and GRU, Together -- A Comparison of Deep Learning and Classical Machine Learning Approaches for Encrypted Malware Traffic Classification
Internet traffic classification is widely used to facilitate network management.
MaMaDroid2.0 -- The Holes of Control Flow Graphs
The changes in the ratio between benign and malicious samples have a clear effect on each one of the models, resulting in a decrease of more than 40% in their detection rate.
Improving Robustness of ML Classifiers against Realizable Evasion Attacks Using Conserved Features
A conventional approach to evaluate ML robustness to such attacks, as well as to design robust ML, is by considering simplified feature-space models of attacks, where the attacker changes ML features directly to effect evasion, while minimizing or constraining the magnitude of this change.
