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

Abstract

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. INDEX TERMS Access control, hybrid access control, secure vehicle localization, machine learning, neural networks, Internet of Things.

Secure and dynamic access control for the Internet of Things (IoT) based traffic system

“…9C . Moreover, the permission assignment time is compared with other similar models such as permission-based dynamic RBAC (PDRBAC) ( Aftab et al, 2019 ) and hybrid access control model (HAC) ( Aftab et al, 2020 ). The variable permission assignment time of PDRBAC (blue bars) is comparatively better than the HAC model (brown bars).…”

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“…The suggested technique reduces overall response time and lowers the total cost significantly. Cache management strategies are designed and evaluated in few publications [155][156][157][158]. A probability-based scoring method, a hierarchical or tiered, approach, and improvements to previously existing approaches are among the algorithms.…”

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“…e same is true for studies on end-to-end security framework development of the Constrained Application Protocol (CoAP) [93][94][95] and on frameworks in which smart-object users designate privacy preferences to protect personal information generated and consumed by smart objects [96]. Smart objects that have recently attracted attention are vehicles that are equipped with various sensor devices, actuators, GPS (global positioning system) receivers, and micro-embedded computers to collect, process, and transmit vast amounts of data [97,98]. Vehicular sensor networks provide connected sensor devices that collect data and enable safer and more fluid road traffic [99].…”