An Intelligent Defensive and Countermeasure Mechanism for IoT Botnet Threats
Ramesh Singh Rawat, Manoj Diwakar, Umang Garg, Prakash Srivastava · 2024
The rapid expansion of Internet of Things devices has created a fertile ground for botnet threats, posing significant risks to cybersecurity. Traditional defensive mechanisms are often inadequate in addressing the dynamic and sophisticated nature of these threats. This paper proposes an intelligent defensive and countermeasure mechanism specifically designed to combat IoT botnet threats. By leveraging advanced machine learning algorithms, real-time data analytics, and automated response strategies, the proposed system can detect, analyze, and neutralize botnet activities with high accuracy and speed. The mechanism integrates a multi-layered defense approach, including anomaly detection, behavior analysis, and threat intelligence sharing, to provide a comprehensive security solution. Extensive simulations and real-world implementations demonstrate the system's effectiveness in mitigating botnet attacks, reducing response time, and minimizing the impact on IoT networks. The present paper highlights the importance of adaptive and intelligent cybersecurity solutions in protecting the ever-expanding IoT ecosystem.