Research Overview

Traditional Internet of Things (IoT) security relies heavily on static cryptographic keys and perimeter authentication. While these defenses manage initial network access, they introduce a critical post-authentication blind spot: once a low-power edge node is compromised, it remains fully "trusted" by the network, allowing malicious actors to manipulate data or launch protocol-level attacks from within the perimeter without triggering traditional firewalls. To eliminate this vulnerability, this research introduces a real-time, lightweight monitoring framework driven by a Behavioral Trust Index (BTI). Instead of relying on static credentials, the gateway continuously evaluates device trustworthiness by analyzing live communication patterns—including transmission frequency, inter-arrival timing consistency, sensor data stability, and payload size consistency over an active sliding window. This enables the system to instantly detect internal anomalies, calculate dynamic trust degradation, and isolate compromised nodes before they threaten network integrity.