Publication Type
Journal Article
Version
acceptedVersion
Publication Date
4-2018
Abstract
Face authentication has been widely available on smartphones, tablets, and laptops. As numerous personal images are published in online social networks (OSNs), OSN-based facial disclosure (OSNFD) creates significant threat against face authentication. We make the first attempt to quantitatively measure OSNFD threat to real-world face authentication systems on smartphones, tablets, and laptops. Our results show that the percentage of vulnerable users that are subject to spoofing attacks is high, which is about 64% for laptop users, and 93% smartphone/tablet users. We investigate liveness detection methods in the real-world face authentication systems against OSNFD threat. We discover that under protection of liveness detection, the percentage of vulnerable images is 18.8%, but the percentage of vulnerable users is as high as 73.3%. This evidence suggests that the current face authentication systems are not strong enough under OSNFD attacks. Finally, we develop a risk estimation tool based on logistic regression, and analyze the impacts of key attributes of facial images on the OSNFD risk. Our statistical analysis reveals that the most influential attributes of facial images are image resolution, facial makeup, occluded eyes, and illumination. This tool can be used to evaluate OSNFD risk for OSN images to increase users’ awareness of OSNFD.
Keywords
liveness detection, Face authentication, online social networks, OSN-based facial disclosure
Discipline
Computer Sciences | Information Security
Research Areas
Cybersecurity
Publication
IEEE Transactions on Dependable and Secure Computing
Volume
15
Issue
2
First Page
231
Last Page
245
ISSN
1545-5971
Identifier
10.1109/TDSC.2016.2550459
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
LI, Yan; Yingjiu LI; XU, KE; YAN, Qiang; and DENG, Robert H..
Empirical study of face authentication systems under OSNFD attacks. (2018). IEEE Transactions on Dependable and Secure Computing. 15, (2), 231-245.
Available at: https://ink.library.smu.edu.sg/sis_research/3339
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/TDSC.2016.2550459