Edge-LLM-XAI-IDS: Explainable LLM-XAI Framework for Edge IDS (v1.1)

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Authors: Charles Stolz, Jielun Zhang
Cited by: 0

Abstract

This release provides the reproducible implementation used in the experimental evaluation of the paper: “An Explainable LLM-XAI Framework for Signature Generation in Edge Intrusion Detection Systems.” The framework introduces a lightweight, edge-deployable architecture that leverages: Large Language Models (LLMs) for automated signature generation Explainable AI (XAI) techniques to improve transparency and analyst trust Hybrid IDS integration combining signature-based and anomaly-based detection Edge deployment compatibility for resource-constrained IoT devices This release (v1.1-conference) corresponds exactly to the version evaluated for the conference submission and is archived to ensure experimental reproducibility and long-term citation stability.

Fields of Study & Subjects

Network Security and Intrusion Detection Network Packet Processing and Optimization Adversarial Robustness in Machine Learning

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
18 February 2026
Language
EN