IOT ENABLED MULTI FACTOR AUTHENTICATION LOCK SYSTEM

Conventional door locks are easily bypassed, posing security threats. Recent IoT advancements have led to smart door locks, but many rely on single authentication methods. This work presents an IoT-enabled multi-factor authentication door lock system, enhancing security with RFID, numeric keypad, and access control via an ESP32 microcontroller and Arduino Uno board. It requires two out of three methods: PIN, facial recognition, and RFID tag verification, unlocking within 10 seconds and re-locking in 5-6 seconds. The average success rate in face recognition with and without disturbances such as spectacles, facial hair etc., are 97% and 92% respectively. Features include robust encryption, secure communication, and fail-safe mechanisms, with a modular design for smart home integration. Thoroughly tested, the system outperforms existing solutions in accuracy and flexibility, providing enhanced security through multi-factor authentication

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Publication Details

Journal
Journal of Information System and Technology Management
Published
2025-06-20
DOI
https://doi.org/10.35631/jistm.1039013
Primary Topic
Wireless Sensor Networks and IoT
Type
article
Field-Weighted Citation Impact
0.00

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article

IOT ENABLED MULTI FACTOR AUTHENTICATION LOCK SYSTEM

Sandeep Krishna, J. Florence Gnana Poovathy, A. Karthik, I. Divya et al.
Journal of Information System and Technology Management
Wireless Sensor Networks and IoT
article

IOT ENABLED MULTI FACTOR AUTHENTICATION LOCK SYSTEM

Sandeep Krishna, J. Florence Gnana Poovathy, A. Karthik, I. Divya, SP Akshith, Rashmitha Mukka
article en

Abstract

Conventional door locks are easily bypassed, posing security threats. Recent IoT advancements have led to smart door locks, but many rely on single authentication methods. This work presents an IoT-enabled multi-factor authentication door lock system, enhancing security with RFID, numeric keypad, and access control via an ESP32 microcontroller and Arduino Uno board. It requires two out of three methods: PIN, facial recognition, and RFID tag verification, unlocking within 10 seconds and re-locking in 5-6 seconds. The average success rate in face recognition with and without disturbances such as spectacles, facial hair etc., are 97% and 92% respectively. Features include robust encryption, secure communication, and fail-safe mechanisms, with a modular design for smart home integration. Thoroughly tested, the system outperforms existing solutions in accuracy and flexibility, providing enhanced security through multi-factor authentication

Journal of Information System and Technology ManagementVol. 10(39)
Centre for Artificial Intelligence and Robotics (IN), Vellore Institute of Technology University (IN)
Strong
Openalex Percentile: Top 79%
Wireless Sensor Networks and IoT
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IOT ENABLED MULTI FACTOR AUTHENTICATION LOCK SYSTEM — Sandeep Krishna, J. Florence Gnana Poovathy, et al. · Journal of Information System and Technology Management (2025) | TGRS Research Map | TGRS