A novel security framework for densely populated Internet of Things users in pervasive service access

Abstract

User density in the Internet of Things (IoT) platform changes with different applications and user demands. Security requirements are adaptable based on the services and the authentication servers attached to the resources. However, the lack of unanimous security measures increases the complexity and authentication level in a user-centric scenario. This article introduces an Ascendable Authentication Framework (AAF) for balancing security and services in a dense IoT by considering this drawback. The proposed framework adopts a high level of authentication and user services through unanimous keying and allocations. This process is defined within the framework covering the service provider and end-users. In this authentication, hyper-elliptic curve cryptography is exploited for service authentication, whereas the key distribution follows a discrete allocation process. Here the discreteness and continuity in authentication are determined using regression learning. The change in distribution function determines the authentication level and redeeming security for further service disseminations. Therefore, the regression sequence is modified without augmenting additional keys in a pervasive manner. This reduces the computation complexity, service authentication time, response latency, and failures.