UNSW-NB15

Source https://www.kaggle.com/datasets/dhoogla/unswnb15?resource=download Dataset This is an academic intrusion detection dataset. All the credit goes to the original authors: dr. Nour Moustafa and dr. Jill Slay. Please cite their original paper and all other appropriate articles listed on the UNSW-NB15 page. The full

Papers using UNSW-NB15 (28)

Adversarial Machine Learning In Network Intrusion Detection Systems2020 · 186 citesAnomaly-based intrusion detection on benchmark datasets for network security: a comprehensive evaluation2026 · 5 citesCAGN-GAT Fusion: A Hybrid Contrastive Attentive Graph Neural Network For Network Intrusion Detection2025 · 9 citesAgentic Intelligence for Unified Cyber Defense: A Self-Adaptive Framework for Threat Detection Across Cloud, Edge, and IoT Systems2026 · 2 citesAn Investigation Into The Performance Of Non-contrastive Self-supervised Learning Methods For Network Intrusion Detection2025 · 3 citesA Defensive Framework Against Adversarial Attacks On Machine Learning-based Network Intrusion Detection Systems2025 · 4 citesEnhancing Autonomous Online Intrusion Detection for IoT with Balanced Learning, Reliable Pseudo-Labels, and Lightweight Architectures2026Quantum transfer learning for cross-domain cybersecurity threat detection and categorization2026 · 1 citesCritical Minority-Class Attack Detection for Industrial Internet Based on Improved Conditional Generative Adversarial Networks2026 · 1 citesFlow Exporter Impact On Intelligent Intrusion Detection Systems2024 · 1 citesAssessing Generalisation Capability Of Machine Learning Models For Intrusion Detection2026Liteshield: Hybrid Feature Selection-driven Lightweight Intrusion Detection For Resource-constrained Iot Networks2026Empirical Analysis Of Adversarial Robustness And Explainability Drift In Cybersecurity Classifiers2026CRYPTOGRAPHIC MODELS FOR ADAPTIVE THREAT DETECTION IN CLOUD-BASED INFRASTRUCTURES2026Network Security Posture Assessment Algorithm Based on Multilayer Perceptron of Graph Convolutional Neural Networks2026AnomalyX: An Adaptive Threat Detection System Using Retrieval-Augmented Generation and Advanced Time-Series Analytics2026Enhancing bidirectional gated recurrent unit with activation mechanism for anomaly classification for network security2026Quantum-AI Models for Real-Time Cybersecurity Threat Detection and Adaptive Defense2026Enterprise Network Security Using Few‐Shot Meta‐Learning2026Emerging Trends in Malware Detection: The Role of Generative AI in Cyber Defense2026Beyond performance metrics: evaluating the unique value of generative AI in hybrid cybersecurity threat detection2026Machine Learning For Network Attacks Classification And Statistical Evaluation Of Adversarial Learning Methodologies For Synthetic Data Generation2026Attention Augmented GNN Rnn-attention Models For Advanced Cybersecurity Intrusion Detection2025A Novel Approach To Network Traffic Analysis: The HERA Tool2025Machine Learning-based Network Intrusion Detection For Big And Imbalanced Data Using Oversampling, Stacking Feature Embedding And Feature Extraction2024 · 200 citesNetwork Intrusion Detection Using Wrapper-based Decision Tree For Feature Selection2020 · 32 citesBridging The Gap To Real-world For Network Intrusion Detection Systems With Data-centric Approach2021 · 4 citesSdn Intrusion Detection Using Machine Learning Method2024 · 2 cites