A Comprehensive Approach Enhancing Home Automation Security With Artificial Intelligence Firewalls: Design and Evaluation

This study introduced an innovative AI-driven solution to enhance the security of home automation systems, addressing the growing vulnerabilities associated with IoT devices. The proposed system combines sophisticated machine-learning techniques with a blockchain-based data-management platform to analyze network-traffic patterns and device behaviors, ensuring data integrity while proactively identifying and combating various cyber threats. Experimental findings demonstrate the system's ability to recognize and mitigate attacks such as denial-of-service and unauthorized access attempts. During a 24-hour evaluation, the AI-powered firewall processed 10,000 requests, successfully blocking 8% of the malicious traffic and identifying suspicious activities for further examination. Notably, it outperformed traditional systems that lacked anomaly-based algorithms by effectively detecting a wide range of significant threats. Future research will focus on enhancing anomaly detection algorithms through user feedback, highlighting the potential of AI-enhanced firewalls to provide robust protection against cyber threats while preserving data confidentiality in emerging 6G networks and smart home ecosystems.