skip to main content
10.1145/3565287.3617624acmconferencesArticle/Chapter ViewAbstractPublication PagesmobihocConference Proceedingsconference-collections
research-article

Advancing Active Authentication for User Privacy and Revocability with BioCapsules

Published:16 October 2023Publication History

ABSTRACT

Biometric Facial Authentication has become a pervasive mode of authentication in recent years. With this surge in popularity, concerns over the security and privacy of biometrics-based systems have grown. Therefore, there is a need for a system that can address security and privacy issues while remaining user-friendly and practical. The BioCapsule scheme is a flexible solution that can be embedded in existing biometrics systems in order to provide robust security and privacy protections. While BioCapsules have been evaluated for their static face authentication capabilities, this paper extends the scheme to Active Authentication, where a user is continuously authenticated throughout a session. We use the MOBIO dataset, which contains video recordings of 150 individuals using mobile devices over several sessions, in order to evaluate the BioCapsule scheme within the domain of Active Authentication. We find that the BioCapsule scheme not only performs comparably to baseline, unsecured system performance, but in some cases exceeds baseline performance in terms of False Acceptance Rate, False Rejection Rate, and Equal Error Rate. Through our experiments, we demonstrate that the BioCapsule scheme is a powerful and practical addition to existing biometrics-based Active Authentication systems to provide robust security and privacy protections.

References

  1. Qiong Cao, Li Shen, Weidi Xie, Omkar M. Parkhi, and Andrew Zisserman. 2017. VGGFace2: A dataset for recognising faces across pose and age. CoRR abs/1710.08092 (2017). arXiv:1710.08092 http://arxiv.org/abs/1710.08092Google ScholarGoogle Scholar
  2. JV Chamary. 2017. No, Apple's face ID is not a "secure password". https://www.forbes.com/sites/jvchamary/2017/09/18/security-apple-face-id-iphone-x/Google ScholarGoogle Scholar
  3. David Crouse, Hu Han, Deepak Chandra, Brandon Barbello, and Anil K. Jain. 2015. Continuous authentication of mobile user: Fusion of face image and inertial Measurement Unit data. In 2015 International Conference on Biometrics (ICB). 135--142. Google ScholarGoogle ScholarCross RefCross Ref
  4. Jiankang Deng, Jia Guo, Niannan Xue, and Stefanos Zafeiriou. 2019. ArcFace: Additive Angular Margin Loss for Deep Face Recognition. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).Google ScholarGoogle ScholarCross RefCross Ref
  5. T. Phillips E. Sanchez. [n. d.]. BioCapsule Active Authentication Github Repository. https://github.com/Edwin-Sanchez2003/BioCapsule ([n. d.]).Google ScholarGoogle Scholar
  6. Gary B. Huang, Manu Ramesh, Tamara Berg, and Erik Learned-Miller. 2007. Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments. Technical Report. University of Massachusetts, Amherst.Google ScholarGoogle Scholar
  7. Deep Insight. 2019. Face Analysis Project using MXNET Repository. Available at: https://github.com/deepinsight/insightface.Google ScholarGoogle Scholar
  8. A.K. Jain, A. Ross, and S. Prabhakar. 2004. An introduction to biometric recognition. IEEE Transactions on Circuits and Systems for Video Technology (2004), 4--20. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Ganiyev Salim Karimovich and Khudoykulov Zarif Turakulovich. 2016. Biometric cryptosystems: Open issues and challenges. In ICISCT. 1--3. Google ScholarGoogle ScholarCross RefCross Ref
  10. Sepehr Keykhaie and Samuel Pierre. 2021. Lightweight and secure face-based active authentication for mobile users. IEEE Transactions on Mobile Computing (2021).Google ScholarGoogle ScholarCross RefCross Ref
  11. Elie Khoury, Laurent El Shafey, Christopher McCool, Manuel Günther, and Sébastien Marcel. 2014. Bi-modal biometric authentication on mobile phones in challenging conditions. Image and Vision Computing (2014), 1147--1160. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Haiping Lu, Karl Martin, Francis Bui, K. N. Plataniotis, and Dimitris Hatzinakos. 2009. Face recognition with biometric encryption for privacy-enhancing self-exclusion. In 2009 16th International Conference on Digital Signal Processing. 1--8. Google ScholarGoogle ScholarCross RefCross Ref
  13. Paul Mozur. 2018. Inside China's dystopian dreams: A.I., shame and lots of cameras. https://www.nytimes.com/2018/07/08/business/china-surveillance-technology.htmlGoogle ScholarGoogle Scholar
  14. Tyler Phillips, Xiaoyuan Yu, Brandon Haakenson, Shreya Goyal, Xukai Zou, Saptarshi Purkayastha, and Huanmei Wu. 2020. AuthN-AuthZ: Integrated, User-Friendly and Privacy-Preserving Authentication and Authorization. In 2020 Second IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA). 189--198. Google ScholarGoogle ScholarCross RefCross Ref
  15. Tyler Phillips, Xukai Zou, Feng Li, and Ninghui Li. 2019. Enhancing Biometric-Capsule-Based Authentication and Facial Recognition via Deep Learning. In Proceedings of the 24th ACM Symposium on Access Control Models and Technologies (Toronto ON, Canada) (SACMAT '19). Association for Computing Machinery, New York, NY, USA, 141--146. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. S. Prabhakar, S. Pankanti, and A.K. Jain. 2003. Biometric recognition: security and privacy concerns. IEEE Security Privacy (2003), 33--42. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. D. Sandberg. 2015. FaceNet and MTCNN Github Repository. Available at: https://github.com/davidsandberg/facenet.Google ScholarGoogle Scholar
  18. M. Savvides, B.V.K. Vijaya Kumar, and P.K. Khosla. 2004. Cancelable biometric filters for face recognition. In Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. 922--925 Vol.3. Google ScholarGoogle ScholarCross RefCross Ref
  19. Florian Schroff, Dmitry Kalenichenko, and James Philbin. 2015. FaceNet: A Unified Embedding for Face Recognition and Clustering. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).Google ScholarGoogle ScholarCross RefCross Ref
  20. Yan Sui, Xukai Zou, Eliza Y. Du, and Feng Li. 2014. Design and Analysis of a Highly User-Friendly, Secure, Privacy-Preserving, and Revocable Authentication Method. IEEE Trans. Comput. (2014), 902--916. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. U. Uludag, S. Pankanti, S. Prabhakar, and A.K. Jain. 2004. Biometric cryptosystems: issues and challenges. Proc. IEEE (2004), 948--960. Google ScholarGoogle ScholarCross RefCross Ref
  22. Kaipeng Zhang, Zhanpeng Zhang, Zhifeng Li, and Yu Qiao. 2016. Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks. IEEE Signal Processing Letters (2016), 1499--1503. Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Advancing Active Authentication for User Privacy and Revocability with BioCapsules

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          MobiHoc '23: Proceedings of the Twenty-fourth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing
          October 2023
          621 pages
          ISBN:9781450399265
          DOI:10.1145/3565287

          Copyright © 2023 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 16 October 2023

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article

          Acceptance Rates

          Overall Acceptance Rate296of1,843submissions,16%
        • Article Metrics

          • Downloads (Last 12 months)39
          • Downloads (Last 6 weeks)5

          Other Metrics

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader