Software-defined network-based dynamic access control mechanism for internet of vehicles using Adaboost

Access Control Models (ACM) must secure the communication system of devices in Internet of Vehicles (IoV) under cloud computing architecture. Existing ACM, on the other hand, struggles to determine the right granularity of permissions when dealing with vast numbers of data in the IoV. Furthermore, IoV is vulnerable to attacks, as attackers can readily exploit existing flaws. Due to insufficient or inefficient ACM, some attacks may succeed. As a result, the authentication mechanism must be reinforced as much as possible using cutting-edge ACM. Methods have been applied to Decisions Making System (DMS) about who has access to what in open distributed information systems like big data, the Internet of Things (IoT), and the cloud experience performance issues because of the number and complexity of the rules and regulations governing who has significant exposure to what. The reasonably significant Access Control (AC) time operational costs have a negative impact on the regular functioning of business services as a consequence. This paper presents a framework for an efficient SDN-involved Dynamic Access system based on AdaBoost (SDNDAAB) model. The challenges related to the ACM is changed by this proposed model into a Binary Classification Problem (BCP) that either permit access permission or deny them. So, apart from providing dynamic support for the AC's efficient execution amidst IoV, the AdaBoost algorithm also supports the disseminated application of the decision engine via a Software Defined Network (SDN) controller for predicting the AC. The results show that the proposed model supports better permission decision accuracy than the other models.