Lightweight-IDS: Reproducible Edge Intrusion Detection Framework
Lightweight-IDS: Reproducible Edge Intrusion Detection Framework
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.
Machine Learning, IoT, Monitoring, Internet of Things, Raspberry PI, Security, Computer architecture, Network intrusion, Threat assessment, Snort, Intrusion Detection
Machine Learning, IoT, Monitoring, Internet of Things, Raspberry PI, Security, Computer architecture, Network intrusion, Threat assessment, Snort, Intrusion Detection
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