Micro-Segmentation Anomaly Detection in Zero-Trust Software-Defined Network Fabrics

arXiv:2608.02627 · cs.CR, cs.CV, cs.LG, cs.NI · Submitted 2026-07-24 · Read on arXiv

Ashly Joseph

cs.CR, cs.CV, cs.LG, cs.NI

Submitted: 2026-07-24

Journal ref: Proceedings of the 2025 Artificial Intelligence and Smart Technologies for Sustainability Conference (AISTS), Rajkot, India, 21-23 August 2025, Institute of Electrical and Electronics Engineers (IEEE), pp. 1-6

DOI: 10.1109/AISTS66100.2025.11233161

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

Terminology

• Transformer — 19× in this paper · explained in 2 episodes
• Accuracy — 14× in this paper · explained in 1 episode
• Software-Defined Networking — 7× in this paper
• AUC — 6× in this paper · explained in 2 episodes
• Zero Trust Architecture — 6× in this paper
• Verification — 4× in this paper · explained in 2 episodes
• Vision Transformer (ViT) — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Clustering — 2× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Intrusion Detection Systems — 2× in this paper
• Consistency — 1× in this paper · explained in 3 episodes
• Contextual Awareness — 1× in this paper · explained in 2 episodes
• Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes

Sources

• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
• Mathematical modelling of flow and adsorption in a gas chromatograph

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