Phishing Dataset for URL Classification

Phishing Dataset for URL Classification is a Kaggle-hosted resource for machine learning in cybersecurity. The dataset's specific size, features, and collection methodology are not detailed in the provided metadata. Its primary purpose appears to be training models to distinguish malicious URLs from legitimate ones.

Use Cases

• Train a binary classifier to detect phishing URLs (inferred from domain, verify after download)
• Benchmark feature engineering techniques for URL security analysis (inferred from domain, verify after download)
• Develop educational tools for cybersecurity awareness (inferred from domain, verify after download)

Strengths

• Published on Kaggle, a platform with established data sharing and versioning.
• Platform tags indicate a clear focus on URL Classification and Phishing Detection.

Limitations

• Metadata is minimal; actual content requires verification after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count, file format, and license are unknown, which may limit suitability assessment.

Provenance

Source

Kaggle

Collection Method

How gathered is unknown.

Time Range

Temporal coverage is unknown.

Freshness

Last updated date is unknown; freshness unverified.

Geography

Spatial coverage is unknown.