CICIDS: Network Traffic Data for Intrusion Detection

CICIDS is a real-world cybersecurity dataset containing network flow data. It is intended for building and testing machine learning models for intrusion detection. The dataset is hosted on Kaggle.

Use Cases

• Train supervised machine learning models for intrusion detection based on network flow data.
• Benchmark anomaly detection algorithms on real-world network traffic.
• Analyze patterns of malicious network activity for threat intelligence.

Strengths

• Data is described as real-world, suggesting practical relevance for model training.
• The dataset is hosted on Kaggle, which typically provides a platform for community validation and discussion.

Limitations

• Row count and file size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Collection Method

Likely contains network flow data gathered from a monitored environment.