Unraveling IoT Network Security with Snort for Robust Intrusion Detection and Prevention

The Internet of Things (IoT) has brought unprecedented connectivity, transforming technology across industries. This interconnected landscape, however, presents unprecedented network security challenges. This paper examines Snort's role as a powerful tool for Intrusion Detection in the network and the ways to prevent the intrusion detection and thoroughly investigates the security challenges posed by IoT networks. In light of the growing number of connected devices, the study focuses on specific vulnerabilities, emphasizing issues such as resource constraints, diverse communication protocols, and the need for tailored security measures. The paper provides a thorough examination of Snort's architecture and its application through the development of custom rules for detecting IoT threats. Practical implementation strategies such as network segmentation and continuous monitoring are investigated. The conclusion emphasizes how critical it is to understand threats unique to the Internet of Things and how to use Snort to fortify network defenses in this complex and ever-changing ecosystem.