ENHANCING SECURITY AND TRUST IN DISTRIBUTED INTELLIGENT SYSTEMS

Abstract

The rapid adoption of distributed intelligent technologies such as cloud computing, Internet of Things (IoT), artificial intelligence, and edge computing has significantly transformed modern digital infrastructures. While these technologies enable scalability, automation, and real‑time data processing, they also introduce complex cybersecurity challenges. Traditional perimeter‑based security models are no longer sufficient to protect dynamic and distributed environments where users, devices, and services interact continuously across heterogeneous networks. This paper proposes a Dynamic Trust‑based Zero Trust Architecture (DTZTA), an adaptive cybersecurity framework designed to enhance security and trust in distributed intelligent systems. The proposed framework integrates zero‑trust access control, dynamic trust evaluation, artificial intelligence driven anomaly detection, and automated response mechanisms. A multi‑layered architecture ensures continuous authentication, real‑time risk assessment, and intelligent threat mitigation. Experimental evaluation using intrusion detection datasets demonstrates that the proposed framework improves threat detection accuracy, reduces false positives, and enhances system scalability compared with traditional security models such as perimeter security, role‑based access control, and conventional intrusion detection systems. The DTZTA framework therefore provides an effective security solution for next‑generation distributed computing environments.