Homoglyph Attack Detection Dataset for Cybersecurity

A cybersecurity dataset designed for detecting phishing and homoglyph attacks. The dataset's creator, size, and specific temporal coverage are not provided. It originates from Kaggle.

Use Cases

• Train classifiers to detect phishing URLs using textual features.
• Develop models to identify homoglyph substitutions in domain names.
• Benchmark anomaly detection algorithms on attack text patterns.
• Analyze character-level features for distinguishing malicious from benign text strings.

Strengths

• Focuses on a specific cybersecurity threat: homoglyph attacks.
• Designed for practical detection tasks like phishing.

Limitations

• Dataset size, row count, and column details are unknown.
• No sample data or file format information is available.
• Potential label noise or class imbalance cannot be assessed.

Provenance

Source

Kaggle