Exploiting Machine Learning for IOT Attack
2025
The Internet of Things (IoT) has rapidly become integrated into everyday life, offering numerous benefits but also presenting significant security challenges.Nowadays, IoT systems generate huge amounts of sensitive data that have come into the eyes of cybercriminals and have become their primary target.At the same time, machine learning has experienced rapid development in many fields, including cybersecurity.However, when it falls into the hands of malicious individuals, it can cause devastating and damaging cyberattacks.Unlike existing studies that explore the role of machine learning (ML) in enhancing IoT security, this paper focuses on how ML can be used to identify which attacks are more commonly seen on IoT systems.This study uses a Random Forest algorithm to identify various IoT attacks and their occurrences using the RT-IoT2022 dataset, which includes a variety of real-time IoT traffic data.The proposed model productively classifies vulnerable and legitimate traffic with an overall accuracy of 99% for cyber attack identification.