Zero-Trust in Zero-Time: Designing Self-Healing IoT Networks for Mass Casualty Events

Abstract

Omid Panahi and Uras Panahi

Mass casualty events—earthquakes, terrorist attacks, industrial accidents, and natural disasters—present the ultimate challenge for communication networks. Thousands of victims require immediate triage, continuous monitoring, and coordinated evacuation, yet the very infrastructure that enables these capabilities is often destroyed or degraded during the event. This paper presents ZT-SelfHeal, a novel framework for designing self-healing Internet of Things (IoT) networks that embed zero-trust security principles into zero-time recovery operations for mass casualty scenarios. The framework integrates three core innovations: (1) a hierarchical edge-cloud architecture with microservice orchestration that achieves sub-second recovery from node failures through automated replication and load balancing, (2) a distributed zero-trust authentication model where every device, sensor, and gateway is continuously verified without reliance on centralized infrastructure that may be unavailable during disasters, and (3) a self-organizing mesh topology that dynamically reconfigures around damaged nodes using LoRaWAN and other low-power wide-area technologies to maintain communication links when infrastructure is compromised. We validate the framework through simulation of a 5,000-victim earthquake scenario, demonstrating 94.2% network resilience (maintaining connectivity despite 40% node failure), 92.3% detection rate for compromised terminals, and average network recovery time of 187ms after infrastructure disruption. The zero-trust component prevents unauthorized access to medical data streams with 99.1% effectiveness, while the self-healing capability maintains communication for critical triage and evacuation operations. This work establishes that zero-trust and self-healing are not competing priorities but complementary requirements for disaster-resilient IoT networks.

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