Show simple item record

dc.contributor.authorAsaduzzaman, Abu
dc.contributor.authorMummidi, Abhishek
dc.contributor.authorSibai, Fadi N.
dc.date.accessioned2019-09-10T20:32:46Z
dc.date.available2019-09-10T20:32:46Z
dc.date.issued2015-10
dc.identifier.citationAsaduzzaman, A., Mummidi, A., Sibai, F. N., "An eye blinking password based liveness monitoring system to improve the detection of video spoofing," Journal of Mechatronics, Electrical, and Computer Technology (IJMEC), 5(17), pp. 2398-2407, Oct. 2015
dc.identifier.issn2411-6173
dc.identifier.issn2305-0543 (online)
dc.identifier.urihttp://www.aeuso.org/includes/files/articles/Vol5_Iss17_2398-2407_An_Eye_Blinking_Password_Based_Live.pdf
dc.identifier.urihttp://hdl.handle.net/10057/16580
dc.descriptionPublishing paper in IJMEC is free of charge and all the content is freely available electronically immediately upon publication and can be distributed under the Creative Commons Attribution-NonCommercial License (CC BY-NC). This license allows anyone to reuse, remix, and build upon the content, as long as it is for legal noncommercial purposes.
dc.description.abstractContemporary protocols in the TCP/IP suite may be very vulnerable to spoofing attacks when extra precautions are not taken to verify the identity. There are several ways to spoof the facial recognition such as using photograph, three-dimensional (3D) model, and video clip of a valid user. Studies show that there have been significant improvements in detecting photograph and 3D model spoofing. However, there is no such improvement in detecting video spoofing. Recent studies also show that liveliness monitoring using the facial features has potential to improve security, especially in biometric systems. In this paper, an efficient method to detect video spoofing using liveliness monitoring is introduced. An eye blinking password system using ultrasonic range sensing module is developed for liveliness detection of the users. In the proposed system, local facial features like eye blinking and chin movement pattern are used via a real-time generic web-camera. The system is tested by conducting experiments using 20 valid users and 100 different users' appearances. According to the experimental results, the proposed system achieves 100% face recognition accuracy and 100% liveliness detection performance.
dc.language.isoen_US
dc.publisherIJMEC
dc.relation.ispartofseriesInternational Journal of Mechatronic, Electrical and Computer Technology
dc.relation.ispartofseriesv.5 no.17
dc.subjectEye blinking password
dc.subjectLiveliness monitoring
dc.subjectNetwork security
dc.subjectUltrasonic method
dc.subjectVideo spoofing
dc.titleAn eye blinking password based liveness monitoring system to improve the detection of video spoofing
dc.typeArticle
dc.rights.holderCopyright IJMEC


Files in this item

Thumbnail

This item appears in the following Collection(s)

  • Articles [10]
    Selected research articles by Dr. Abu Asaduzzaman

Show simple item record