A Hybrid Access Control Model with Dynamic COI for Secure Localization of Satellite and IoT-Based Vehicles

Secure localization of vehicles is gaining the attention of researchers from both academia and industry especially due to the emergence of internet of things (IoT). The modern vehicles are usually equipped with circuitries that gives connectivity with other vehicles and with cellular networks such as 4G/Fifth generation cellar network (5G). The challenge of secure localization and positioning is magnified further with the invention of technologies such as autonomous or driverless vehicles based on IoT, satellite, and 5G. Some satellite and IoT based localization techniques exploit machine learning, semantic segmentation, and access control mechanism. Access control provides access grant and secure information sharing mechanism to authorized users and restricts unauthorized users, which is necessary regarding security and privacy of government or military vehicles. Previously, static conflict of interest (COI) based access control was used for security proposes. However, static COI based access control creates excesses and administrative overload that creates latency in execution, which is the least tolerable factor in modern IoT or 5G control vehicles. Therefore, in this paper, a hybrid access control (HAC) model is proposed that implements the dynamic COI in the HAC model on the level of roles. The proposed model is enhanced by modifying the role-based access control (RBAC) model by inserting new attributes of the RBAC entities. The HAC model deals with COI on the level of roles in an efficient manner as compared to previously proposed models. Moreover, this model features significant improvement in terms of dynamic behavior, decreased administrative load, and security especially for vehicular localization. Furthermore, the mathematical modeling of the proposed model is implemented with an example scenario to validate the concept.