OPEN COMPETITION-BASED EVALUATION OF EMERGING ARTIFICIAL INTELLIGENCE CYBER THREATS

Abstract

The rapid advancement of artificial intelligence has introduced new cybersecurity challenges that require rigorous and transparent evaluation methodologies to assess emerging AI-related threats before deployment in critical environments. Open competition-based evaluation enables researchers, security professionals, and industry experts to collaboratively identify vulnerabilities, evaluate AI robustness, validate defensive strategies, and improve governance practices under controlled conditions. This paper proposes an open competition-based framework integrating ethical AI evaluation, machine learning, cloud-native DevSecOps, behavioral analytics, human-in-theloop validation, continuous monitoring, and enterprise governance. The proposed methodology supports standardized benchmarking of AI security, automated risk assessment, collaborative defensive testing, and continuous model improvement while ensuring responsible disclosure and regulatory compliance. Experimental evaluation demonstrates improvements in AI robustness assessment, governance efficiency, defensive validation accuracy, operational reliability, and enterprise cyber resilience. The proposed framework provides a scalable and productionready solution for evaluating emerging AI cybersecurity risks within modern enterprise environments. Keywords— Artificial Intelligence Security, Cyber Threat Evaluation, AI Benchmarking, DevSecOps, Behavioral Analytics, Enterprise Governance, Responsible AI, Threat Assessment.