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A Framework for Secure Selfie-Based Biometric Authentication in the Cloud

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Selfie Biometrics

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

Cloud-based selfie authentication has multiple advantages over on-device selfie authentication: Cloud-based authentication can support nomadic access from multiple devices including those not owned by the user, can leverage cheap and scalable utility computing, and can enable rapid innovation by allowing new matching algorithms to be continually deployed with no need to update the local device. This chapter presents a framework for a cloud-based selfie biometric authentication, which is termed Selfie-Biometrics-as-a-Service (SBaaS). By leveraging Platform-as-a-Service (PaaS) concepts, the framework is designed to enable independent software vendors to develop extensions and add-ons to a provider’s core application. In particular, the framework creates an innovative marketplace for biometric algorithms by providing a standard pre-built interface for the development and submission of new matching algorithms. When an authentication request is submitted, a criteria is used to select an appropriate matching algorithm. Every time a particular algorithm is selected, the corresponding developer is rendered a micropayment. Also presented in this chapter are solutions for preserving the confidentiality of biometrics stored in the cloud. This can be achieved through the use of biocryptosystems, which are secure biometric architectures involving the conversion of biometric features into secure signals that can be stored in the biometric database but are still useable for authentication. To provide a concrete example, a case study of a selfie-based ocular recognition system is disclosed, and detailed descriptions are provided of the user and developer interfaces.

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Notes

  1. 1.

    http://www.m-gwt.com/.

  2. 2.

    http://www.gwtproject.org/.

  3. 3.

    http://biosecure.wp.tem-tsp.eu/.

  4. 4.

    http://svnext.it-sudparis.eu/svnview2-eph/ref_syst//Iris_Osiris_v4.1.

References

  1. Alonso-Fernandez F, Bigun J (2015) Near-infrared and visible-light periocular recognition with gabor features using frequency-adaptive automatic eye detection. IET Biom 4(2):74–89

    Article  Google Scholar 

  2. Barra S et al (2015) Ubiquitous iris recognition by means of mobile devices. Pattern Recognit Lett 57:66–73

    Article  Google Scholar 

  3. Beimborn D, Miletzki T, Wenzel S (2011) Platform as a service (PaaS). Bus & Inf Syst Eng 3(6)

    Google Scholar 

  4. Bharadi VA, D’silva GM (2015) Online signature recognition using software as a service (SAAS) model on public cloud. In: International conference on computer, communication and automated, pp 65–72

    Google Scholar 

  5. Bommagani AS, Valenti MC, Ross A (2014) A framework for secure cloud-empowered mobile biometrics. In: Proceeding of IEEE military communications conference, pp 255–261

    Google Scholar 

  6. Bowyer KW, Flynn PJ (2010) The ND-IRIS-0405 iris image dataset. University of Notre Dame, CVRL

    Google Scholar 

  7. Bradski G (2000) The opencv library. Dr. Dobb’s J Softw Tools Prof Program 25(11):120–123 (2000)

    Google Scholar 

  8. Canuto AM, Pintro F, Xavier-Junior JC (2013) Investigating fusion approaches in multi-biometric cancellable recognition. Expert Syst Appl 40(6):1971–1980

    Article  Google Scholar 

  9. Chow R, Jakobsson M, Masuoka R, Molina J, Niu Y, Shi E, Song Z (2010) Authentication in the clouds: a framework and its application to mobile users. In: Proceedings of the 2010 ACM workshop on cloud computing security workshop, CCSW ’10. ACM, New York, NY, USA, pp 1–6. https://doi.org/10.1145/1866835.1866837

  10. Das R (2013) Biometrics in the cloud. Keesing J Doc Identity, 21–23

    Google Scholar 

  11. de Freitas Pereira T, Marcel S (2015) Periocular biometrics in mobile environment. In: Proceeding of biometrics: theory, applications and systems (BTAS), pp 1–7

    Google Scholar 

  12. Jeong DS, et al (2006) Iris recognition in mobile phone based on adaptive gabor filter. In: Proceeding of international conference on biometrics (ICB), pp 457–463

    Chapter  Google Scholar 

  13. Jillela RR, Ross A (2015) Segmenting iris images in the visible spectrum with applications in mobile biometrics. Pattern Recognit Lett 57(C):4–16

    Article  Google Scholar 

  14. Juels A, Sudan M (2002) A fuzzy vault scheme. In: Proceeding IEEE international symposium on information theory, p 408. https://doi.org/10.1109/ISIT.2002.1023680

  15. Juels A, Wattenberg M (1999) A fuzzy commitment scheme. In: Proceeding 6th ACM conference on computer and communications security, pp 28–36 (1999)

    Google Scholar 

  16. Kang JS (2010) Mobile iris recognition systems: an emerging biometric technology. Procedia Comput Sci 1(1):475–484

    Article  Google Scholar 

  17. Kong A, Cheung KH, Zhang D, Kamel M, You J (2006) An analysis of biohashing and its variants. Pattern Recognit 39(7):1359–1368

    Article  Google Scholar 

  18. Lawton G (2008) Developing software online with platform-as-a-service technology. Computer 41(6):13–15

    Article  Google Scholar 

  19. Mell P, Grance T (2011) The NIST definition of cloud computing. In: Recommendations of the national institute of standards and technology, special publication pp 800–145

    Google Scholar 

  20. Nagar A, Nandakumar K, Jain AK (2008) Securing fingerprint template: fuzzy vault with minutiae descriptors. In: Proceeding 19th international conference on pattern recognition. https://doi.org/10.1109/ICPR.2008.4761459

  21. Nagar A, Nandakumar K, Jain AK (2012) Multibiometric cryptosystems based on feature-level fusion. IEEE Trans Inf Forensics Secur 7(1):255–268. https://doi.org/10.1109/TIFS.2011.2166545

    Article  Google Scholar 

  22. Nandakumar K, Jain AK (2008) Multibiometric template security using fuzzy vault. In: Proceeding IEEE international conference on biometrics: theory, applications and systems

    Google Scholar 

  23. Nandakumar K, Jain AK, Pankanti S (2007) Fingerprint-based fuzzy vault: implementation and performance. IEEE Trans Inf Forensics Secur 2(4):744–757. https://doi.org/10.1109/TIFS.2007.908165

    Article  Google Scholar 

  24. Patel VM, Ratha NK, Chellappa R (2015) Cancelable biometrics: a review. IEEE Signal Process Mag 32(5):54–65. https://doi.org/10.1109/MSP.2015.2434151

    Article  Google Scholar 

  25. Raghavendra R, Busch C (2016) Learning deeply coupled autoencoders for smartphone based robust periocular verification. In: 23rd international conference on image processing (ICIP). IEEE

    Google Scholar 

  26. Rane S, Wang Y, Draper SC, Ishwar P (2013) Secure biometrics: concepts, authentication architectures, and challenges. IEEE Signal Process Mag 30(5):51–64. https://doi.org/10.1109/MSP.2013.2261691

    Article  Google Scholar 

  27. Ratha NK, Chikkerur S, Connell JH, Bolle RM (2007) Generating cancelable fingerprint templates. IEEE Trans Pattern Anal Mach Intell 29(4):561–572. https://doi.org/10.1109/TPAMI.2007.1004

    Article  Google Scholar 

  28. Rose J (2016) Biometrics as a service: the next giant leap? Biom Technol Today 2016(3):7–9

    Article  Google Scholar 

  29. Stojmenovic M (2012) Mobile cloud computing for biometric applications. In: 15th international conference on network-based information system, pp 654–659

    Google Scholar 

  30. Sutcu Y, Li Q, Memon N (2007) Protecting biometric templates with sketch: theory and practice. IEEE Trans Inf Forensics Secur 2(3):503–512

    Article  Google Scholar 

  31. Sutcu Y, Li Q, Memon N (2007) Secure biometric templates from fingerprint-face features. In: Proceeding IEEE conference on computer vision and pattern recognition

    Google Scholar 

  32. Talreja V, Ferrett T, Valenti MC, Ross A (2018) Biometrics-as-a-service: a framework to promote innovative biometric recognition in the cloud. In: Proceeding IEEE international conference on consumer electronics (ICCE)

    Google Scholar 

  33. Talreja V, Valenti MC, Nasrabadi NM (2017) Multibiometric secure system based on deep learning. In: Proceeding IEEE global conference on signal and information processing, pp 298–302. https://doi.org/10.1109/GlobalSIP.2017.8308652

  34. Teoh AB, Kuan YW, Lee S (2008) Cancellable biometrics and annotations on biohash. Pattern Recognit 41(6):2034–2044

    Article  Google Scholar 

  35. Thönes J (2015) Microservices. IEEE Softw 32(1), 116, 113–115

    Google Scholar 

  36. Woodard DL, Pundlik S, Miller P, Jillela R, Ross A (2010) On the fusion of periocular and iris biometrics in non-ideal imagery. In: 20th international conference on pattern recognition (ICPR). IEEE, pp 201–204

    Google Scholar 

  37. Zuo J, Ratha NK, Connell JH (2008) Cancelable iris biometric. In: Proceeding IEEE international conference on pattern recognition, pp 1–4

    Google Scholar 

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Acknowledgements

This research was funded by the Center for Identification Technology Research (CITeR), a National Science Foundation (NSF) Industry/University Cooperative Research Center (I/UCRC).

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Authors and Affiliations

  1. West Virginia University, Morgantown, WV, USA

    Veeru Talreja, Terry Ferrett & Matthew C. Valenti

  2. Michigan State University, East Lansing, MI, USA

    Arun Ross

Authors
  1. Veeru Talreja
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  2. Terry Ferrett
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  3. Matthew C. Valenti
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  4. Arun Ross
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Corresponding author

Correspondence to Arun Ross .

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Editors and Affiliations

  1. Department of Electrical Engineering and Computer Science, Wichita State University, Wichita, KS, USA

    Ajita Rattani

  2. Department of Computer Science and Electrical Engineering, University of Missouri-Kansas City, Kansas City, MO, USA

    Reza Derakhshani

  3. Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA

    Arun Ross

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Talreja, V., Ferrett, T., Valenti, M.C., Ross, A. (2019). A Framework for Secure Selfie-Based Biometric Authentication in the Cloud. In: Rattani, A., Derakhshani, R., Ross, A. (eds) Selfie Biometrics. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-030-26972-2_14

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  • DOI: https://doi.org/10.1007/978-3-030-26972-2_14

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-26972-2

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