Quantifying AI Vulnerabilities: A Synthesis of Complexity, Dynamical Systems, and Game Theory

arXiv:2404.10782v1 Announce Type: new
Abstract: The rapid integration of Artificial Intelligence (AI) systems across critical domains necessitates robust security evaluation frameworks. We propose a novel approach that introduces three metrics: System Complexity Index (SCI), Lyapunov Exponent for AI Stability (LEAIS), and Nash Equilibrium Robustness (NER). SCI quantifies the inherent complexity of an AI system, LEAIS captures its stability and sensitivity to perturbations, and NER evaluates its strategic robustness against adversarial manipulation. Through comparative analysis, we demonstrate the advantages of our …

artificial artificial intelligence arxiv complexity critical cs.ai cs.cr domains evaluation frameworks game game theory index integration intelligence metrics nash novel rapid robustness robust security security stability system systems theory vulnerabilities