A Novel Approach Based on Machine Learning, Blockchain, and Decision Process for Securing Smart Grid

Autor: Nabil Tazi Chibi, Omar Ait Oualhaj, Wassim Fassi Fihri, Hassan El Ghazi
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: IEEE Access, Vol 12, Pp 33190-33199 (2024)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2024.3370239
Popis: Smart Grids (SGs) rely on advanced technologies, generating significant data traffic across the network, which plays a crucial role in various tasks such as electricity consumption billing, actuator activation, resource optimization, and network monitoring. This paper presents a new approach that integrates Machine Learning (ML), Blockchain Technology (BT), and Markov Decision Process (MDP) to improve the security of SG networks while ensuring accurate storage of events reported by various network devices through BT. The enhanced version of the Proof of Work (PoW) consensus mechanism ensures data integrity by preventing tampering and establishing the reliability of known and unknown attack detection. The proposed versions of PoW, namely GPoW 1.0 and GPoW 2.0, aim to make the consensus process more environmentally friendly.
Databáze: Directory of Open Access Journals