Engineering a resilient smart grid: Practical defense mechanisms and deployable framework against evolving cyber-threats

• Proposes a novel, dual-criteria taxonomy for cyber-attacks and a new classification for defense mechanisms, providing a more profound and systematic understanding of the threat and solution landscape. • Presents an integrated, multi-layered defense framework that synergizes technical solutions, operational policies, and regulatory considerations for comprehensive smart grid protection. • Provides the first comprehensive performance evaluation of defense mechanisms based on key engineering metrics: effectiveness, response speed, cost, scalability, and ease of use/deployment. • Introduces a new taxonomy of mathematical models for analyzing and predicting cybersecurity threats in smart grids. • Analyzes the complete threat intelligence lifecycle (identification, collection, processing, analysis, dissemination) for proactive security management. • Leverages cutting-edge enablers (AI, Blockchain) to propose practical and deployable countermeasures for enhancing grid resilience. The integration of smart grids as - is fundamental to developing sustainable urban energy infrastructure. However, this convergence of information and operational technologies (IT/OT) introduces critical cybersecurity challenges that threaten grid reliability and urban resilience. This comprehensive study provides an innovative analysis of cybersecurity in smart grid CPS through: (1) a novel dual-categorization framework for cyber-attacks targeting critical infrastructure; (2) evaluation of AI-driven defense mechanisms for sustainable grid operations; (3) vulnerability assessment of CPS components across urban energy networks; (4) implementation of threat intelligence lifecycles for proactive defense; and (5) analysis of regulatory frameworks governing smart grid security. Our findings demonstrate that False Data Injection (FDI) and Distributed Denial-of-Service (DDoS) attacks pose severe threats to grid stability, while the IT/OT convergence represents the most critical vulnerability. The study proposes deployable AI-powered countermeasures and mathematical models for enhancing CPS security in smart grids. These insights provide policymakers and engineers with actionable strategies for protecting critical urban infrastructure, establishing a foundation for developing resilient and sustainable cities through secure cyber-physical systems.