Real recorded network traffic includes both benign and malicious activity. The dataset is hosted on Kaggle and is intended for building AI systems. The author, organization, and specific collection details are not provided.
Use Cases
- Train binary classifiers to detect malicious network flows based on traffic features.
- Develop anomaly detection systems for encrypted network traffic.
- Benchmark machine learning models for cybersecurity applications.
- Analyze patterns distinguishing benign from malicious encrypted sessions.
Strengths
- Contains real recorded network traffic, not simulated data.
- Includes both benign and malicious traffic categories for supervised learning.
Limitations
- Row count is 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
- Source
- Kaggle
- Collection Method
- Real recorded network traffic.
- Time Range
- null
- Freshness
- null
- Geography
- null