Advancing Malware Detection in Network Traffic With Self-Paced Class Incremental Learning

Detecting the cyber-physical-social cooperated APTs in high-DER-penetrated smart grids: Threats, current work and challenges

Q Lu, Z Peng, L Wu, M Ni, J Luo - Computer Networks, 2024 - Elsevier
Large-scale renewable distributed energy sources (DERs) penetrating into smart grids
(SGs) is an inevitable trend. Such high-DER-penetrated SGs entail heavy reliance on …
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A Cascaded Broad Learning Network Embedded Image Features for Malware Traffic Classification

J Xu, Y Zhang, K Zhou, Q Wang, M Hua… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Malware traffic classification (MTC) is a critical technology in network security, Internet of
Things (IoT) devices, and big data traffic, and has been mainly used for encrypted malicious …
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VC-SEI: Robust Variable-Channel Specific Emitter Identification Method Using Semi-Supervised Domain Adaptation

H Wan, Q Wang, X Fu, Y Wang, H Zhao… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Specific emitter identification (SEI) uses advanced techniques to identify radio equipment by
analyzing unique characteristics in radio frequency signals. Recently, deep learning (DL) …
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Federated continual representation learning for evolutionary distributed intrusion detection in Industrial Internet of Things

Z Zhang, Y Zhang, H Li, S Liu, W Chen, Z Zhang… - … Applications of Artificial …, 2024 - Elsevier
As a promising paradigm, Federated Learning (FL)-based distributed intrusion detection
offers potent protection for the network security of Industrial Internet of Things (IIoT) systems …
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