10, June 2026

Multi-Dimensional Trust Evaluation Using Behavioral Profiling and Contextual Risk Assessment for Industrial IoT Security

VOLUME-12; ISSUE-6; JUNE-2026

Author(s): 1.Balasubramanian R, 2.Dr. Thenmozhi D S, 3.Dr. Marikkannan M

Authors Affiliations:

Balasubramanian R¹, Dr. Thenmozhi D S², Dr. Marikkannan M³
¹PG Scholar, Department of Computer Science and Engineering, Government College of Engineering, Erode, Tamil Nadu, India
²Assistant Professor, Department of Computer Science and Engineering, Government College of Engineering, Erode, Tamil Nadu, India
³Assistant Professor, Department of Computer Science and Engineering, Government College of Engineering, Erode, Tamil Nadu, India

DOIs:10.2015/IJIRMF/202606007     |     Paper ID: IJIRMF202606007


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Industrial automation systems increasingly rely on Internet of Things (IoT) technologies for real-time monitoring, predictive maintenance, and intelligent process control. However, conventional security mechanisms in Industrial IoT (IIoT) environments use static trust models that authenticate devices only once during connection, making systems vulnerable to insider threats, compromised devices, and lateral attacks. To address these limitations, a Security-Aware Adaptive Zero Trust Security Framework (AZTSF) is proposed, which eliminates implicit trust and continuously verifies devices throughout their lifecycle. The framework evaluates device identity, behavioral patterns, and contextual risk factors to support dynamic and fine-grained access control decisions, ensuring that only trusted devices can access critical industrial resources. It also integrates anomaly detection techniques to identify abnormal activities such as unauthorized access attempts, data irregularities, and unusual communication behavior. The proposed model is implemented and tested in a simulation-based IIoT environment using OMNeT++ and Python. Experimental results show improved access control accuracy, enhanced malicious device detection, and better adaptability compared to traditional static trust models. By enforcing continuous authentication and least-privilege access, the framework reduces attack surfaces, limits the impact of compromised devices, and improves overall system resilience, making it a scalable and effective security solution for modern industrial applications.

Adaptive Zero Trust, Behavior-Based Trust Evaluation,Dynamic Trust Score, Zero Trust Architecture.

Balasubramanian R, Dr. Thenmozhi D S, Dr. Marikkannan M (2026); Multi-Dimensional Trust Evaluation Using Behavioral Profiling and Contextual Risk Assessment for Industrial IoT Security, International Journal for Innovative Research in Multidisciplinary Field, ISSN(O): 2455-0620, Vol-12, Issue-6, Available on –   https://www.ijirmf.com/

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