Enhancing IoT Security: Design and Evaluation of a Raspberry Pi-Based Intrusion Detection System
Toghrul Garalov, Mohammed El‐Hajj
Abstract
With the increasing number of IoT devices, safe-guarding them against cyber attacks has become a complex task. Traditional intrusion detection system (IDS) solutions are often impractical for resource-constrained IoT devices. To address this challenge, this research proposes and evaluates a Raspberry Pi-based IDS specifically designed to secure IoT devices. The study aims to analyze the effectiveness of the Pi-based IDS in detecting various network attacks, identify configuration changes to enhance its performance, and assess any potential vulnerabilities. The methodology involves conducting attacks on an IoT environment consisting of a Raspberry Pi with IDS, a temperature sensor transmitting data to a web server, and a background traffic generator. The study analyzes and presents metrics data extracted from log files. The expected outcome is to demonstrate the efficacy of the Raspberry Pi-based IDS and provide insights into its potential advantages for securing IoT devices by detecting network attacks. The findings of this research will contribute to the existing IoT security literature and offer recommendations for optimizing the Snort IDS on the Raspberry Pi platform.