Abstract—The transition to renewable energy sources, facilitated by Smart Grid (SG) communication networks, has introduced cybersecurity vulnerabilities that threaten power generation reliability. Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks disrupt blockchain-based energy networks stability, raising legal and regulatory concerns. This study investigates the legal obligations and communication challenges associated with securing smart grid networks against cyber threats. Specifically, we analyze how existing data protection laws ((General Data Protection Regulation (GDPR), Network Information Service (NIS) Directive)) and cybersecurity policies ((National Institute of Standards and Technology (NIST) Cybersecurity Framework, EU Energy Policy)) apply to energy communication infrastructures and assess the legal accountability of energy providers to ensure grid resilience. The study employs Machine Learning (ML) models, namely K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Random Forest (RF), to classify operational states: normal, single attack, and multiple attacks. Big data obtained from blockchainpowered renewable energy networks was used. The RF model achieved the highest classification accuracy of 98%. The findings underscore regulatory measures’ needs and legal frameworks that address AI-driven security risks in communication networks. We recommend policy updates for automated cybersecurity solutions and to enforce data protection compliance, and establish liability protocols for smart grid operators.