Enhancing Security and Energy Efficiency in Smart Energy Management Systems through IoT Device Detection and Machine Learning Techniques

Enhancing Security and Energy Efficiency in Smart Energy Management Systems through IoT Device Detection and Machine Learning Techniques

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 b...

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Bibliographic Details
Published in:2024 IEEE 7th International Conference on Advanced Technologies, Signal and Image Processing (ATSIP) Vol. 1; pp. 506 - 511
Main Authors: Algarni, Mohammed Ali, Kraiem, Naoufel, Sakly, Houneida
Format: Conference Proceeding
Language:English
Published: IEEE 11-07-2024
Subjects:
Cybersecurity
Device detection
Ecosystems
Encryption
Energy efficiency
Image processing
Internet of Things (IoT)
Machine learning
Performance evaluation
Protocols
Security
Smart energy management systems (SEMSs)
Vulnerabilities
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Summary: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.
ISSN:2687-878X
DOI:10.1109/ATSIP62566.2024.10638911