Traditional cybersecurity models operate on binary trust assumptions systems and users are either trusted or untrusted, authenticated or unauthenticated, authorized or unauthorized. This dichotomous approach fails to reflect the continuous, dynamic nature of real-world risk, where trust degrades over time, context influences security posture, and threats evolve continuously. Modern critical infrastructure environments require security frameworks that adapt to changing risk conditions, recognize that trust is temporal and contextual, and implement proportional security controls commensurate with current risk levels.
This paper introduces Adaptive Trust-Decay Cybersecurity Models (ATDCM), a comprehensive framework that implements time-based trust degradation, context-aware risk assessment, and dynamic access control for continuous infrastructure risk management. Unlike zero-trust architectures that require constant verification for every transaction or static trust models that grant persistent access once authenticated, ATDCM implements graduated trust levels that decay exponentially over time unless renewed through verification activities. The decay rate adapts based on contextual risk factors including user behavior patterns, access anomalies, threat intelligence, asset criticality, and environmental conditions.
Our framework comprises five core components: Trust Score Computation Engine employing time-decay functions with adaptive decay coefficients, Context-Aware Risk Assessment integrating behavioral analytics and threat intelligence, Dynamic Policy Engine translating trust scores into granular access controls, Verification Management System orchestrating re-authentication requirements, and Continuous Monitoring Infrastructure providing real-time visibility into trust state transitions. We implement mathematical models for trust decay using exponential decay functions T(t) = T₀ · e^(-λt), where trust score T decays from initial value T₀ over time t at rate λ determined by risk context.
Empirical evaluation across three critical infrastructure deployments (financial services institution with 8,500 users, healthcare network serving 14 facilities, energy utility managing 450,000 customer accounts) demonstrates that ATDCM reduces successful breach attempts by 87% compared to traditional models while decreasing false positive rates from 23% to 8% and reducing user friction (measured by daily re-authentication requests) from 8.7 to 1.8 per user. Mean time to detect anomalous access patterns improved from 4.7 hours to 42 minutes, representing 85% improvement in threat detection speed. System overhead remains minimal at 3.2% CPU utilization and 180ms average latency for access decisions.
Adaptive Trust-Decay Cybersecurity Models represent a significant advancement in access control and risk management for critical infrastructure environments. By implementing graduated trust levels that decay over time at context-aware rates, ATDCM reconciles the competing requirements of strong security and operational continuity. Our empirical evaluation demonstrates 87% breach prevention rates, 85% improvement in threat detection speed, and 79% reduction in user friction compared to traditional zero-trust implementations.
The mathematical framework based on exponential decay functions provides a rigorous foundation for trust degradation while maintaining computational efficiency for real-time access decisions. Context-aware risk assessment enables appropriate security response to dynamic threat conditions without requiring constant user intervention. Dynamic policy enforcement translates trust scores into graduated access controls, maintaining business operations while managing risk proportionally.
Critical infrastructure organizations face unprecedented cybersecurity challenges as digital transformation expands attack surfaces while operational requirements demand high availability and minimal disruption. Traditional security models prove inadequate—static trust fails to respond to evolving threats, while pure zero-trust imposes unacceptable operational burden. Adaptive trust-decay models provide the balanced approach necessary for modern infrastructure protection, combining robust security with practical operational viability.
As cyber threats continue evolving in sophistication and infrastructure systems grow increasingly interconnected, security frameworks must similarly advance beyond binary trust decisions toward continuous, adaptive risk management. ATDCM demonstrates that mathematically grounded, context-aware trust models can significantly improve security posture while supporting operational requirements. Continued research and development in adaptive trust mechanisms will prove essential for protecting the critical infrastructure upon which modern society depends.
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How to Cite This Paper
Amarachi Franca Mgbemele (2025). Adaptive Trust-Decay Cybersecurity Models for Continuous Infrastructure Risk Management. International Journal of Computer Techniques, 12(6). ISSN: 2394-2231.
