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Behind the Bait: Delving into PhishTank's hidden data.

Affan Yasin1, Rubia Fatima2, Javed Ali Khan3

  • 1School of Software, Northwestern Polytechnical University, Xian 710072, Shaanxi, China.

Data in Brief
|December 28, 2023
PubMed
Summary

This study collected over 190,000 phishing URLs from PhishTank using a Python script. The data aids in developing better phishing filters and security defenses.

Keywords:
Artificial intelligenceComputer securityDatasetEmail securityPhished URLSocial engineeringWeb security

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Area of Science:

  • Computer Science
  • Cybersecurity
  • Information Security

Background:

  • Phishing is a prevalent social engineering attack vector using deceptive emails and disguised URLs.
  • Organizational networks are frequent targets of phishing attacks, necessitating robust defense mechanisms.

Purpose of the Study:

  • To create a comprehensive dataset of phishing URLs for research and practical applications.
  • To support the development of enhanced cybersecurity tools and strategies.

Main Methods:

  • Data extraction from the PhishTank website using a custom Python script.
  • Aggregation of a large-scale dataset comprising over 190,000 phishing URLs.

Main Results:

  • A substantial dataset of verified phishing URLs was successfully compiled.
  • The dataset provides a valuable resource for cybersecurity research and development.

Conclusions:

  • The collected phishing URL dataset can significantly improve phishing filters and security training models.
  • This resource empowers researchers and practitioners to bolster defenses against phishing attacks.