Cybersecurity for AI-Enhanced Supervisory Control and Data Acquisition (SCADA) Systems: Safeguarding Critical Infrastructure From Evolving Cyber Threats

This study aims to enhance the cybersecurity of AI-driven Supervisory Control and Data Acquisition (SCADA) systems by identifying vulnerabilities and proposing robust defense mechanisms. Utilizing a mixed-methods approach, including qualitative research, case study analysis, and conceptual modeling, the research investigates the unique threats faced by SCADA systems and evaluates the effectiveness of AI-enhanced security measures. Key findings reveal that traditional security frameworks are inadequate against evolving cyber threats, necessitating the integration of advanced AI techniques for anomaly detection and incident response. The study concludes that implementing AI-driven solutions significantly improves the resilience of SCADA systems against cyberattacks, highlighting the need for ongoing adaptation to emerging threats. These findings underscore the importance of proactive cybersecurity strategies in safeguarding critical infrastructure.