Author

Azizi Ariffin

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#edge computing Open access Sep 2026

LiteNet: lightweight network traffic classification using explainable artificial intelligence and model compression

LiteNet is proposed, a lightweight model for real-time NTC in a resource-constrained environment to address the disparity between model complexity and edge device limitations, and Benchmarking results demonstrated that LiteNet outperformed the state-of-the-art method in terms of performance and efficiency.

A. Haris, Azizi Ariffin, Nor Badrul Anuar et al. · PeerJ Computer Science · 0 citations

Preprint Aug 2026

Adaptive Intrusion Detection System using Transformer-Based Neural Networks and Continual Learning Approach with Adversarial Investigation

This work presents an adaptive IDS framework coupling a tabular transformer encoder with a class balanced experience replay buffer that replays benign traffic at every update to stabilize decision boundaries, and investigates the buffer with overt label flipping and stealthy backdoor poisoning attacks.

Azizi Ariffin, A. Haris, F. Zaki et al. · 0 citations