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CAM-LDS: Cyber Attack Manifestations for Automatic Interpretation of System Logs and Security Alerts
arXiv β CS AI|Max Landauer, Wolfgang Hotwagner, Thorina Boenke, Florian Skopik, Markus Wurzenberger|
π€AI Summary
Researchers introduce CAM-LDS, a new dataset covering 81 cyber attack techniques to improve automated log analysis using Large Language Models. The study shows LLMs can correctly identify attack techniques in about one-third of cases, with adequate performance in another third, demonstrating potential for AI-powered cybersecurity analysis.
Key Takeaways
- βCAM-LDS dataset provides comprehensive coverage of 81 distinct attack techniques across 13 tactics from 18 sources.
- βLarge Language Models show promise for automated interpretation of system logs and security alerts without domain-specific configurations.
- βLLMs correctly predicted attack techniques in approximately one-third of attack steps with adequate performance in another third.
- βThe dataset addresses the scarcity of publicly available labeled data for cybersecurity research.
- βTraditional automated log analysis methods are limited by their inability to semantically understand logs and explain underlying causes.
#cybersecurity#large-language-models#dataset#log-analysis#intrusion-detection#ai-security#automation#research
Read Original βvia arXiv β CS AI
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