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Secure Face Unlock: Spoof Detection on Smartphones

文献类型：期刊论文

作者Patel, Keyurkumar1; Han, Hu1,2; Jain, Anil K.
刊名IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
出版日期2016-10-01
卷号11期号:10页码:2268-2283
关键词Face antispoofing face unlock spoof detection on smartphone unconstraint smartphone spoof attack database image distortion analysis
ISSN号1556-6013
DOI10.1109/TIFS.2016.2578288
英文摘要With the wide deployment of the face recognition systems in applications from deduplication to mobile device unlocking, security against the face spoofing attacks requires increased attention; such attacks can be easily launched via printed photos, video replays, and 3D masks of a face. We address the problem of face spoof detection against the print (photo) and replay (photo or video) attacks based on the analysis of image distortion (e.g., surface reflection, moire pattern, color distortion, and shape deformation) in spoof face images (or video frames). The application domain of interest is smartphone unlock, given that the growing number of smartphones have the face unlock and mobile payment capabilities. We build an unconstrained smartphone spoof attack database (MSU USSA) containing more than 1000 subjects. Both the print and replay attacks are captured using the front and rear cameras of a Nexus 5 smartphone. We analyze the image distortion of the print and replay attacks using different: 1) intensity channels (R, G, B, and grayscale); 2) image regions (entire image, detected face, and facial component between nose and chin); and 3) feature descriptors. We develop an efficient face spoof detection system on an Android smartphone. Experimental results on the public-domain Idiap Replay-Attack, CASIA FASD, and MSU-MFSD databases, and the MSU USSA database show that the proposed approach is effective in face spoof detection for both the cross-database and intra-database testing scenarios. User studies of our Android face spoof detection system involving 20 participants show that the proposed approach works very well in real application scenarios.
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000382167800010
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://119.78.100.204/handle/2XEOYT63/8152]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Han, Hu
作者单位1.Michigan State Univ, Dept Comp Sci & Engn, E Lansing, MI 48824 USA
2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Patel, Keyurkumar,Han, Hu,Jain, Anil K.. Secure Face Unlock: Spoof Detection on Smartphones[J]. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,2016,11(10):2268-2283.
APA Patel, Keyurkumar,Han, Hu,&Jain, Anil K..(2016).Secure Face Unlock: Spoof Detection on Smartphones.IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,11(10),2268-2283.
MLA Patel, Keyurkumar,et al."Secure Face Unlock: Spoof Detection on Smartphones".IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 11.10(2016):2268-2283.

入库方式： OAI收割

来源：计算技术研究所

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