CICDDoS-2019

The 'CICDDoS-2019' dataset is a benchmark that contains network traffic data specifically designed to evaluate network intrusion detection systems (NIDS) against Distributed Denial of Service (DDoS) attacks.

Papers using CICDDoS-2019 (9)

BARS: Benign-Anchored Ranking and Selection for False Alarm Reduction in Network Intrusion Detection2026nCMD: Benign-Anchored Feature Selection for Imbalanced Network Intrusion Detection2026SHIELD-IDS: Structurally Heterogeneous Ensemble with Integrated Layered Defense for Intrusion Detection Systems2026Enterprise Network Security Using Few‐Shot Meta‐Learning2026NEAT-ID: A Novel Method for Enhancing Threat Detection Process DDoS in Cybersecurity2026Sentinelsphere: Integrating Ai-powered Real-time Threat Detection With Cybersecurity Awareness Training2026Machine Learning for Network Attacks Classification and Statistical Evaluation of Adversarial Learning Methodologies for Synthetic Data Generation2026AI-Powered Hybrid Intrusion Detection Framework for Cloud Security Using Novel Metaheuristic Optimization2026Holmes: An Evidence-Grounded LLM Agent for Auditable DDoS Investigation in Cloud Networks2026