N-BaIoT: Benign and Botnet Network Traffic for Attack Detection

Network traffic data from IoT devices designed for botnet attack detection. The dataset includes traffic labeled as benign, Mirai, and Gafgyt. It was sourced from Kaggle, but specific details about its creation, size, and update frequency are not provided.

Use Cases

• Train supervised classification models to distinguish between benign and malicious IoT traffic.
• Benchmark anomaly detection algorithms using labeled attack traffic from the Mirai and Gafgyt botnets.
• Study the network behavior patterns of specific IoT botnets for threat intelligence.

Strengths

• Includes labeled data for two major IoT botnets, Mirai and Gafgyt, which are relevant for real-world attack detection.
• Focuses on a specific and critical domain of IoT cybersecurity.

Limitations

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

Provenance

Source

Kaggle