Cloud-Based Face and Speech Recognition for Access Control Applications
Abstract
This paper describes the implementation of a system to recognize employees and visitors wanting to gain access to a physical office through face images and speech-to-text recognition. The system helps employees to unlock the entrance door via face recognition without the need of tag-keys or cards. To prevent spoofing attacks and increase security, a randomly generated code is sent to the employee, who then has to type it into the screen. On the other hand, visitors and delivery persons are provided with a speech-to-text service where they utter the name of the employee that they want to meet, and the system then sends a notification to the right employee automatically. The hardware of the system is constituted by two Raspberry Pi, a 7-inch LCD-touch display, a camera, and a sound card with a microphone and speaker. To carry out face recognition and speech-to-text conversion, the cloud-based platforms Amazon Web Services and the Google Speech-to-Text API service are used respectively. The two-step face authentication mechanism for employees provides an increased level of security and protection against spoofing attacks without the need of carrying key-tags or access cards, while disturbances by visitors or couriers are minimized by notifying their arrival to the right employee, without disturbing other co-workers by means of ring-bells.
Cite
@article{arxiv.2004.11168,
title = {Cloud-Based Face and Speech Recognition for Access Control Applications},
author = {Nathalie Tkauc and Thao Tran and Kevin Hernandez-Diaz and Fernando Alonso-Fernandez},
journal= {arXiv preprint arXiv:2004.11168},
year = {2020}
}
Comments
Published at Proc. 6th International Workshop on Security and Privacy in the Cloud, SPC, in conjunction with IEEE Conference on Communications and Network Security, CNS, Avignon, France, 29 June - 1 July 2020