GTM approach towards engineering a features-oriented evaluation framework for secure authentication in IIoT environment

Abstract

Industry Internet of Things (IIoT) has become the most evolving area over the last few years. The number of IoT devices connected in industry has sharply elevated but this surge has led to the vulnerability and data breach such as if a malicious entry is made to the secure network, it will forfeit all the network resources. For this purpose a full pledged secure authentication method is essential to safeguard IIoT network. There is a bulky list of number of authentications protocols available to keep network safe with a variety of features so but it becomes herculean task for network administrator to pick the strong and secure authentication method due to huge number of criteria, conflicting objectives and availability of authentication protocols in industry environment. It has become imperative to get the most rational authentication method in devices operating in IIoT. To address this issue, a feature-oriented assessment framework is put forward to provide a ground for ranking and selection of best authentication mechanism. This framework uses a mathematic approach known as Graph Theory Matrix Approach (GTMA) and selects the best authentication method based on the number of features. These features are related to authentication and covers almost every aspect of authentication method and are used as benchmark for selection purposes. This framework takes into account the most important features and helps in selecting the best and most ideal features-oriented authentication method that can be employed in IIoT to keep the integrity and security of connected devices and overall network infrastructure.