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

arXiv:2608.04602 · cs.CR · Submitted 2026-08-05 · Read on arXiv

Azizi Ariffin, Afif Haris, Faiz Zaki, Hazim Hanif, Nor Badrul Anuar

cs.CR

Submitted: 2026-08-05

Code: https://github.com/um-csnet/ReplayIDS

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 118× in this paper · explained in 1 episode
• Transformer — 65× in this paper · explained in 2 episodes
• Continual Learning — 49× in this paper · explained in 3 episodes
• Transformers — 25× in this paper · explained in 2 episodes
• Benchmark — 22× in this paper · explained in 2 episodes
• Catastrophic Forgetting — 11× in this paper · explained in 9 episodes
• Fine-Tuning — 11× in this paper · explained in 5 episodes
• Transformer Encoder — 10× in this paper · explained in 2 episodes
• Distillation — 6× in this paper · explained in 2 episodes
• Elastic Weight Consolidation — 5× in this paper
• Embeddings — 3× in this paper · explained in 2 episodes
• Attention Mechanism — 2× in this paper · explained in 3 episodes
• Class Imbalance — 2× in this paper · explained in 3 episodes
• Composition — 2× in this paper · explained in 2 episodes
• Concept Drift — 2× in this paper · explained in 6 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Hyperparameters — 2× in this paper · explained in 2 episodes
• Inductive Bias — 2× in this paper · explained in 3 episodes
• Representation Learning — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 6 episodes
• Weight Decay — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Absorb — 1× in this paper · explained in 1 episode
• Attack Success Rate (ASR) — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Feature Selection — 1× in this paper · explained in 4 episodes
• Knowledge Distillation — 1× in this paper · explained in 15 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• MARA Geran Penyelidikan MyRA — 1× in this paper
• Meta-learning — 1× in this paper · explained in 3 episodes
• Residual Connections — 1× in this paper · explained in 3 episodes
• Scoring Function — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 4 episodes

Sources

• TabTransformer: Tabular Data Modeling Using Contextual Embeddings
• SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training
• On Tiny Episodic Memories in Continual Learning
• An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks
• Persistent Backdoor Attacks in Continual Learning

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