Analysis of Spoofing and Phishing Attacks on IoT Device

Abstract

Internet of Things (IoT) device security remains a concern due to their limited computational resources and increasing exposure to network-based cyberattacks. While recent IoT security research has focused on machine-learning and blockchain-based defense mechanisms, many of these approaches introduce computational overhead that may not be suitable for resource-constrained devices. This study investigates lightweight host-based countermeasures against network-level spoofing and phishing attacks targeting IoT environments. Specifically, the research examines attack entry points, classifies associated vulnerabilities, and evaluates three practical defense mechanisms: packet analysis using Wireshark, port monitoring using iptables, and host file reconfiguration. Detection is performed through the identification of abnormal TCP communication patterns, unauthorized port activity, and malicious-domain access attempts. A controlled experimental environment based on a Raspberry Pi IoT platform was used to assess the effectiveness and resource consumption of each approach. The results indicate that host file reconfiguration achieved the highest detection accuracy (96%) with the lowest CPU overhead (7%), while the combined deployment of all mechanisms achieved a 99% blocking success rate. The findings demonstrate that lightweight host-based defenses can provide protection against phishing and spoofing attacks while maintaining operational suitability for resource-constrained IoT devices.