Evaluating Adaptive Access Policies for Zero Trust Architectures in Modern Cybersecurity Environments

This study develops a mathematically rigorous framework for adaptive access control within Zero Trust Architectures, integrating dynamic risk scoring and threshold optimization. Utilizing publicly available datasets such as CICIDS2017 and CERT Insider Threat, the framework is validated through extensive Monte Carlo simulations and adversarial testing. The optimized policies achieve a True Positive Rate (TPR) exceeding 0.88 and maintain a False Positive Rate (FPR) below 0.12 across varying operational loads. Access latency remains bounded under 180 milliseconds in high-load scenarios, with computational overhead scaling linearly, as average decision processing times range between 5 ms and 10 ms. Policy robustness is quantified by a variance metric below 0.05 under parameter perturbations, indicating consistent performance. The iterative update of policy parameters <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\theta$</tex> employs a gradient descent-based rule <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\theta^{(t+1)}=\theta^{(t)}-\eta \nabla_{\theta} \mathscr{L}\left(\theta^{(t)}\right)$</tex>, where <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathscr{L}(\theta)$</tex> balances security and usability trade-offs. Access decisions are made via a threshold function on the risk score <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$R=\mathbf{w}^{\top} \mathbf{f}$</tex>, with adaptive thresholds <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\theta_{\text {low}}$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\theta_{\text {high}}$</tex> guiding permit, challenge, or deny outcomes. These quantitative results substantiate the efficacy of adaptive access control in dynamically balancing security and operational requirements, demonstrating scalability and robustness suitable for deployment in complex, evolving cybersecurity environments.