Comprehensive Analysis and Detection of IoT Network Attacks Using Recon Host Discovery Traffic Dataset

Abstract

The proliferation of Internet of Things (IoT) devices has introduced unparalleled interconnectivity and significant security challenges. Reconnaissance attacks, particularly Host Discovery, are often precursors to more severe cyber threats. In this study, we examine a labeled network traffic flow dataset to analyze patterns and identify key indicators of Recon Host Discovery attacks. Leveraging exploratory data analysis and feature correlation techniques, we uncover critical traffic behaviors, such as short flow durations and anomalous packet statistics, that distinguish benign from malicious activities. The findings lay the groundwork for developing robust detection mechanisms for IoT networks, emphasizing the importance of targeted feature selection and real-time analytics.