Beyond Model Scaling: Rethinking Sequence Construction for Transformer-based Network Intrusion Detection

arXiv:2610.17725 · cs.CR, cs.NI · Submitted 2026-10-13 · Read on arXiv

cs.CR, cs.NI

Submitted: 2026-10-13

Updated: 2026-10-13

Comments: 10 pages, 8 figures, 5 tables. Reproducibility artifact: https://github.com/ZeeshanZulkiflShah/sequence-construction-nids-artifact/tree/arxiv-v1-artifact

Code: https://github.com/ZeeshanZulkiflShah/sequence-construction-nids-artifact

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

Terminology

• Transformer — 1× in this paper · explained in 2 episodes

Sources

• DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing
• PyTorch: An Imperative Style, High-Performance Deep Learning Library
• Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference
• Qwen2.5 Technical Report

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