학술논문

AI-enabled IoT based multimodal authentication system for securing the hardware and software clients
Document Type
Conference
Source
2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COM-IT-CON) Machine Learning, Big Data, Cloud and Parallel Computing (COM-IT-CON), 2022 International Conference on. 1:545-550 May, 2022
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
Robotics and Control Systems
Face recognition
Authentication
Manuals
Fingerprint recognition
Streaming media
Real-time systems
Software reliability
Multimodal Authentication System
LBPH
Face Recognition
RFID
Fingerprint Recognition
Keypad
Language
Abstract
Security is one of most essential needs in today’s era. With the advent of today’s technology, the threats have also increased, and it is now challenging to safeguard one’s belongings. It is desired to reduce human involvement and effort as much as possible, and here comes the need for a multimodal authentication system. In order to standardize the development of authentication agents without compromising the response time, security, and robustness, an AI-enabled IOT based authentication system is presented in this paper. Different authentication modules such as real-time face recognition using Artificial Intelligence (AI) based algorithms, fingerprint recognition, RFID authentication, and manual keypad entry are used in this authentication system. All these modules are then interconnected to take a global decision about the person authentications. Experimental outcomes reveal that the presented multimodal authentication system works well and provides good results.