TY - JOUR
T1 - CCTV-based multi-factor authentication system
AU - Kwon, Byoung Wook
AU - Sharma, Pradip Kumar
AU - Park, Jong Hyuk
N1 - Publisher Copyright:
© 2019 KIPS.
PY - 2019
Y1 - 2019
N2 - Many security systems rely solely on solutions based on Artificial Intelligence, which are weak in nature. These security solutions can be easily manipulated by malicious users who can gain unlawful access. Some security systems suggest using fingerprint-based solutions, but they can be easily deceived by copying fingerprints with clay. Image-based security is undoubtedly easy to manipulate, but it is also a solution that does not require any special training on the part of the user. In this paper, we propose a multi-factor security framework that operates in a three-step process to authenticate the user. The motivation of the research lies in utilizing commonly available and inexpensive devices such as onsite CCTV cameras and smartphone camera and providing fully secure user authentication. We have used technologies such as Argon2 for hashing image features and physically unclonable identification for secure device-server communication. We also discuss the methodological workflow of the proposed multi-factor authentication framework. In addition, we present the service scenario of the proposed model. Finally, we analyze qualitatively the proposed model and compare it with state-of-the-art methods to evaluate the usability of the model in real-world applications.
AB - Many security systems rely solely on solutions based on Artificial Intelligence, which are weak in nature. These security solutions can be easily manipulated by malicious users who can gain unlawful access. Some security systems suggest using fingerprint-based solutions, but they can be easily deceived by copying fingerprints with clay. Image-based security is undoubtedly easy to manipulate, but it is also a solution that does not require any special training on the part of the user. In this paper, we propose a multi-factor security framework that operates in a three-step process to authenticate the user. The motivation of the research lies in utilizing commonly available and inexpensive devices such as onsite CCTV cameras and smartphone camera and providing fully secure user authentication. We have used technologies such as Argon2 for hashing image features and physically unclonable identification for secure device-server communication. We also discuss the methodological workflow of the proposed multi-factor authentication framework. In addition, we present the service scenario of the proposed model. Finally, we analyze qualitatively the proposed model and compare it with state-of-the-art methods to evaluate the usability of the model in real-world applications.
KW - Argon2
KW - Convolutional Neural Network
KW - Deep Reinforcement Learning
KW - Physically Unclonable Functions
UR - http://www.scopus.com/inward/record.url?scp=85074905382&partnerID=8YFLogxK
U2 - 10.3745/JIPS.03.0127
DO - 10.3745/JIPS.03.0127
M3 - Article
AN - SCOPUS:85074905382
SN - 1976-913X
VL - 15
SP - 904
EP - 919
JO - Journal of Information Processing Systems
JF - Journal of Information Processing Systems
IS - 4
ER -