Lightweight-IDS

Lightweight IDS on Raspberry Pi Using Machine Learning

Project Overview

This project implements a hybrid Intrusion Detection System (IDS) for resource-constrained platforms like Raspberry Pi. It combines:

• Signature-based detection using Snort
• Anomaly-based detection using a lightweight machine learning model

Targeted attacks include:

• ICMP Ping (Ping of Death)
• SYN Flood
• SSH Brute-Force

The system is optimized for low-latency, real-time detection with minimal CPU overhead.

Project Presentation Video

A recorded presentation of this project is available on YouTube:
https://www.youtube.com/watch?v=ggy3CH8KAy8

Conference Presentation

View the slide deck presented at the 2024 IEEE Cyber Awareness and Research Symposium (CARS):
CARS 2024 Slide Deck (PDF)

References

• Stolz, C., Li, F., & Zhang, J. (2024). Lightweight Intrusion Detection System on Resource-Constrained Devices. 2024 IEEE 4th Cyber Awareness and Research Symposium (CARS). IEEE Xplore

Team

Author	Email
Charles Stolz	[email protected]
Fuhao Li	[email protected]
Jielun Zhang	[email protected]