Researchers have developed an end-to-end framework designed to automate critical workflows within Security Operations Centers (SOCs). This system integrates an ensemble of large language models for threat detection, achieving 82.8% accuracy with a low false positive rate. It also features a novel architecture for generating precise queries across different SIEM platforms and enhances incident resolution by improving prediction accuracy from 78.3% to 90.0%. The framework significantly reduces incident triage time from hours to under 10 minutes, demonstrating the viability of domain-constrained LLMs in operational security. AI
影响 Automates SOC operations, reducing triage time and improving threat detection accuracy.
排序理由 Academic paper detailing a new LLM framework for security operations.
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