Evaluation of a lightweight zero trust architecture enhances security for IoT devices, suggesting improved protection.
The rapid proliferation of Internet of Things (IoT) devices has introduced critical security challenges stemming from device heterogeneity, limited native safeguards, and expanded attack surfaces. Traditional perimeter-based security models are increasingly ineffective against modern threats, particularly lateral movement and insider attacks. This paper presents the design, implementation, and evaluation of a light-weight Zero Trust Architecture for IoT (ZT-IoT) that enforces continuous authentication, context-aware access control, and behavioral anomaly detection. Unlike prior ZTA frameworks that incur high computational costs or depend on blockchain consensus mechanisms, ZT-IoT is optimized for resource-constrained environments through mutual TLS, adaptive micro-segmentation, and telemetry-driven enforcement. A hybrid evaluation—combining simulated cyberattack scenarios with real-world IoT testbeds—demonstrates that ZT-IoT reduces unauthorized access attempts by 95%, completely prevents insider privilege escalation, detects lateral threats in under three minutes, and blocks all data tampering and replay attacks. Moreover, large-scale simulations with 1,000 heterogeneous nodes confirmed its scalability, maintaining detection times under three minutes with less than 12% RAM overhead. These findings validate ZT-IoT as a practical, scalable, and energy-efficient security paradigm, positioning it for deployment in critical domains such as smart cities, industrial IoT, and remote healthcare systems.
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Hani Al‐Balasmeh (2025) studied this question.
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