Malware and botnet prevention in smart building IoT devices using blockchain-enabled federated learning
Christopher Taylor, Biju Issac, Nauman Aslam, Kay Rogage, Graham Kelly · IET conference proceedings. · 2024
The project proposes an AI-driven framework to enhance malware and botnet detection in smart buildings, employing blockchain and federated learning. It aims to overcome the limitations of conventional security methods by introducing a more dynamic and intelligent detection system. The initiative seeks to improve IoT security, establishing new standards for protecting smart building infrastructures against evolving cyber threats. Through the integration of blockchain and federated learning, the project addresses data security and privacy challenges, ensuring robust detection capabilities across various IoT environments.