Zero Trust 6G: Survivability Optimization with Stochastic Attack Modeling

Future sixth-generation (6G) wireless networks are envisioned as a backbone for mission-critical applications, including autonomous transportation, smart grids, space communications, and tactical defense systems. Ensuring continuous service delivery under adversarial conditions is a fundamental goal of Zero Trust Architectures (ZTA) for Future G. This paper presents an integrated framework that combines stochastic cyberattack modeling with cost-constrained survivability optimization to enhance resilience in 6G mission-critical networks. We extend the methodology to 6G radio access networks (RAN) and core infrastructures by building upon validated survivability models for cyber-physical systems (CPSs) and stochastic attack rate prediction. We also incorporate redundancy allocation strategies and series-parallel reliability modeling. Cyber-attacks are characterized by using stochastic processes such as Poisson and negative binomial distributions to predict attack rates and dynamically update trust scores within ZTA policy engines. The proposed approach is supported by comparative analysis, including numerical insights from prior validated studies and literature benchmarks. The framework aligns with 3GPP security enhancements for 6G and offers a pathway toward unbreakable resilience in Zero Trust-enabled mission-critical networks.