SECURE INTELLIGENT NETWORK TECHNOLOGIES FOR INDUSTRIAL COMPLEXES

Abstract

This paper proposes a formalized risk-adaptive authorization model for Zero Trust
architectures based on dynamic trust evaluation and adaptive access token management. Unlike traditional
authorization mechanisms relying on static policies and fixed token lifetimes, the proposed approach
continuously updates trust and operational risk during an active session. The model integrates asset
sensitivity, contextual factors, and behavioral signals into a unified decision-making loop implemented at
the PDP/PEP levels. Authorization decisions (permit, step-up, deny) directly influence token lifetime,
which is dynamically reduced in response to detected risk events such as anomalous behavior, context
changes, or device integrity violations. A formal mechanism for adaptive token lifetime control is
introduced to minimize the potential attack window in case of token compromise. Scenario-based
evaluation demonstrates that the proposed method significantly reduces attack exposure while maintaining
acceptable decision latency and usability. The results confirm the effectiveness of risk-driven session
management for enhancing the resilience of identity-centric security systems within Zero Trust
environments.
Keywords: Hybrid industrial network, Industry 4.0, Industrial Internet of Things, Time-Sensitive
Networking, deterministic data transmission, network monitoring, anomaly detection, cyber resilience

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