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A Comprehensive Measurement Study of Domain Generating Malware

Talkat USENIX Security '16 · 2016-08-10..08-12· [security, data-engineering]
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Reimplemented 43 DGAs and extracted 253 seeds to precompute about 160 million domains, then queried historical WHOIS/DomainTools records for up to 18 million of those names. Findings: only ~115,000 (≈0.6% registered) show up, GameOver P2P registers ~74k/260k (~30%), and global collisions are vanishingly rare (≈3,000 hits across the entire set), so pre-computed blocklists reliably tag families with minimal false positives; a shared dataset and web service ingest feeds for automated labeling and blocking and is already in operational use.

AI-written summary · about

  1. 0:00Introduction
  2. 0:27Who thinks this domain is automatically generated
  3. 1:02Outline
  4. 1:31Domain Generation Algorithms
  5. 2:31Why Use Domain Generation Algorithms
  6. 3:45Key Findings
  7. 7:40Data Set
  8. 8:24Reverse Engineering
  9. 10:47Data Source
  10. 11:22Taxonomy
  11. 13:42How are domains used
  12. 16:40Data visualization
  13. 17:00Number of generated domains
  14. 18:05Registration numbers
  15. 19:33Domain takedowns
  16. 20:53Collisions
  17. 22:03Preregistrations
  18. 24:47Registration Log Ahead
  19. 27:17Conclusion
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