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Please use this identifier to cite or link to this item: http://lrcdrs.bennett.edu.in:80/handle/123456789/1813
Title: AI-enabled IoT based multimodal authentication system for securing the hardware and software clients
Authors: Shelke, Nitin Arvind
Banarjee, Avishek
Singh, Navneet Pratap
Kukreja, Sonal
Keywords: Face Recognition
Fingerprint Recognition
Keypad
LBPH
Multimodal Authentication System
RFID
Issue Date: 2022
Publisher: Institute of Electrical and Electronics Engineers Inc.
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. © 2022 IEEE.
URI: https://doi.org/10.1109/COM-IT-CON54601.2022.9850797
http://lrcdrs.bennett.edu.in:80/handle/123456789/1813
ISSN: 9781665496025
Appears in Collections:Conference/Seminar Papers_ SCSET

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