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Research Paper | Computer Science and Information Technology | Nigeria | Volume 12 Issue 6, June 2023 | Popularity: 5 / 10
Enhancing Role - Based Access Control with Embedded Facial Recognition RBAC - EFR System
Joe Essien
Abstract: Over time, a range of control mechanisms have been devised to deter unauthorised individuals from gaining entry to restricted facilities. The principal objective of implementing an automated access control system is to guarantee the protection of individuals and assets. The proliferation of electronic devices that offer security measures has gained significant traction in recent times. The automated door access control system is a highly sophisticated method of identification that utilises both biometric and non-biometric techniques. Non-biometric methods of identification rely on the use of passwords and access cards, while biometric methods utilise techniques such as fingerprint, iris, or facial recognition to establish a person's identity. Nevertheless, the majority of these techniques do not incorporate algorithms that are based on roles, which assess access requests in relation to a predetermined set of roles. The study introduces a novel design and simulation of a role-based access control system that has been augmented with a facial recognition system, utilising the ESP32-CAM. The RBAC-EFR system has been developed with the aim of facilitating domain-specific expert systems. It leverages roles and facial recognition technologies to enable deductions or choices pertaining to user access that it actively monitors. The Arduino Integrated Development Environment (IDE) serves as a design tool for interacting with and uploading programmes to the Arduino hardware. On the other hand, Proteus is utilised as a circuit simulation and virtual system modelling application. This technology is utilised for simulating the interaction between microcontroller scripts and digital electronics components.
Keywords: Door Control System, Expert Systems, Microcontrollers, Role-Based Access Control, Embedded Facial Recognition System
Edition: Volume 12 Issue 6, June 2023
Pages: 2767 - 2774
DOI: https://www.doi.org/10.21275/SR23625003927
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