Replication Data for: Knowing When to Escalate: Prompt-Based Uncertainty Quantification for Selective Automation of LLM-Based Intrusion Detection
Abstract
Complete replication package for Phase 0 (Foundation Validation) of the IDS uncertainty estimation study. Includes raw experiment results from 50 LLM-based intrusion detection experiments across 5 uncertainty quantification methods, 5 models, and 2 CIC-IDS benchmark datasets, along with the full experiment code, evaluation scripts, and pre-computed metrics.
Fields of Study & Subjects
Network Security and Intrusion Detection
Adversarial Robustness in Machine Learning
Information and Cyber Security
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 16 February 2026
- Language
- EN