Lightweight-IDS: Reproducible Edge Intrusion Detection Framework

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Authors: Charles Stolz, Jielun Zhang, Fuhao Li
Cited by: 0

Abstract

This software provides the reproducible implementation accompanying the publication: C. Stolz, F. Li, and J. Zhang,"Implementing Lightweight Intrusion Detection System on Resource Constrained Devices,"2024 Cyber Awareness and Research Symposium (CARS),Grand Forks, ND, USA, 2024, pp. 1–6.doi: 10.1109/CARS61786.2024.10778716 The framework implements a lightweight hybrid intrusion detection system (IDS) designed for deployment on resource-constrained IoT devices such as the Raspberry Pi. The system integrates signature-based detection (Snort) with machine learning-based anomaly detection to improve detection coverage while maintaining computational efficiency. If you use this software in academic work, please cite the above publication.

Fields of Study & Subjects

Network Security and Intrusion Detection Network Packet Processing and Optimization Artificial Immune Systems Applications

Publication details

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