Utilizing The DLBAC Approach Toward a ZT Score-based Authorization for IoT Systems

Abstract

The internet of Things (IoT) refers to a network of physical objects that are equipped with sensors, software, and other technologies in order to communicate with other devices and systems over the internet. IoT has emerged as one of the most important technologies of this century over the past few years. To ensure IoT systems' sustainability and security over the long term, several researchers lately motivated the need to incorporate the recently proposed zero trust (ZT) cybersecurity paradigm when designing and implementing access control models for IoT systems. This poster proposes a hybrid access control approach incorporating traditional and deep learning-based authorization techniques toward score-based ZT authorization for IoT systems.