An LLM-Assisted AutoML Framework for Intrusion Detection in IoT Networks
cs.CR, cs.LG
Submitted: 2026-09-19
Updated: 2026-09-19
Comments: Submitted to an IEEE Journal. Code will be released at: https://github.com/LiYangHart/LLM-Assisted-AutoML-For-Intrusion-Detection
Code: https://github.com/LiYangHart/LLM-Assisted-AutoML-For-Intrusion-Detection
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Related papers
- SoK: AI-Augmented Binary Reversing
- Relaxed Sender Anonymity for CBDC Interbank Settlement: A Zero-Knowledge Approach on Permissioned EVM
- Calibration-Family Overfit: Why Trusted Sabotage Monitors Don't Transfer Across Lineages
- Efficient Fuzzy PSI under One-Sided Assumptions
- Sealing the Audit-Runtime Gap for LLM Skills
- Token Composition: A Graph Based on EVM Logs