Enhancing Security and Energy Efficiency in Smart Energy Management Systems through IoT Device Detection and Machine Learning Techniques
Mohammed Algarni, Naoufel Kraïem, Houneida Sakly · 2024
This research endeavors to fortify the security aspects of smart energy management systems (SEMSs) while optimizing energy efficiency by amalgamating Internet of Things (IoT) technologies. By integrating the IoT into the SEMS framework, this study aims to explore and enhance cybersecurity measures by implementing cutting-edge strategies to protect against potential vulnerabilities and threats. This comprehensive approach involves leveraging IoT devices to create a secure and efficient ecosystem within an SEMS, encompassing encryption techniques, authentication protocols, anomaly detection, and other innovative security strategies to ensure the resilience and optimal performance of these interconnected energy management systems.