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Syst."],"published-print":{"date-parts":[[2021,3,31]]},"abstract":"<jats:p>The fundamental goal of a revocable biometric system is to defend a user\u2019s biometrics from being compromised. This research explores the application of deep learning or Convolutional Neural Networks to multi-instance biometrics. Modality features are transformed into revocable templates through the application of random projection. During the user authentication phase, we employ Support Vector Machines, chosen over three other alternative classifiers after carrying out a comparative study. Comparison of the proposed method over other standard deep learning models and performance evaluation before and after revocability have also been discussed. Results demonstrate ability to improve identification accuracy and provide sound template security. The system was validated on three multi-instance iris and fingervein databases.<\/jats:p>","DOI":"10.1145\/3389683","type":"journal-article","created":{"date-parts":[[2020,8,15]],"date-time":"2020-08-15T13:18:42Z","timestamp":1597497522000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Deep Learning for Multi-instance Biometric Privacy"],"prefix":"10.1145","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0354-7007","authenticated-orcid":false,"given":"Tanuja","family":"Sudhakar","sequence":"first","affiliation":[{"name":"University of Calgary, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marina","family":"Gavrilova","sequence":"additional","affiliation":[{"name":"University of Calgary, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,12,22]]},"reference":[{"volume-title":"Proceedings of the International Conference on Computational Science and Its Applications. 217--226","author":"Anikeenko A.","key":"e_1_2_1_1_1","unstructured":"A. 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Biohashing: Two factor authentication featuring fingerprint data and tokenised random number . Pattern Recog. 37 , 11 (Nov. 2004), 2245--2255. DOI:https:\/\/doi.org\/10.1016\/j.patcog.2004.04.011 10.1016\/j.patcog.2004.04.011 Andrew Teoh Beng Jin, David Ngo Chek Ling, and Alwyn Gohb. 2004. Biohashing: Two factor authentication featuring fingerprint data and tokenised random number. Pattern Recog. 37, 11 (Nov. 2004), 2245--2255. DOI:https:\/\/doi.org\/10.1016\/j.patcog.2004.04.011","journal-title":"Pattern Recog."},{"key":"e_1_2_1_15_1","first-page":"186","article-title":"Extensions of Lipschitz mappings into a Hilbert space","volume":"26","author":"Johnson William","year":"1984","unstructured":"William Johnson and Joram Lindenstrauss . 1984 . Extensions of Lipschitz mappings into a Hilbert space . Contemp. Math. 26 (1984) 186 -- 206 . DOI:https:\/\/doi.org\/10.1090\/conm\/026\/737400 10.1090\/conm William Johnson and Joram Lindenstrauss. 1984. 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Impact of artificial \u201cgummy\u201d fingers on fingerprint systems. Proc. SPIE, Optic. Secur. Counterf. Deterr. Techn. IV, Vol. 4677. 275--289."},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11760-011-0226-8"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/COGINF.2011.6016128"},{"key":"e_1_2_1_23_1","unstructured":"Multimedia-University. 2018. MMU Database. Retrieved from pesona.mmu.edu.my\/ ccteo\/.  Multimedia-University. 2018. MMU Database. Retrieved from pesona.mmu.edu.my\/ ccteo\/."},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2015.2427849"},{"key":"e_1_2_1_26_1","volume-title":"Proceedings of the IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing. 43--49","author":"Paul Padma Polash","year":"2012","unstructured":"Padma Polash Paul and Marina Gavrilova . 2012 . Second order multimodal cancelable biometric system using random projection . 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An overview of gradient descent optimization algorithms. arXiv (1609.04747v2) (2017)."},{"key":"e_1_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2007.4379175"},{"key":"e_1_2_1_35_1","volume-title":"Very deep convolutional networks for large-scale image recognition. arXiv (1409.1556)","author":"Simonyan Karen","year":"2014","unstructured":"Karen Simonyan and Andrew Zisserman . 2014. Very deep convolutional networks for large-scale image recognition. arXiv (1409.1556) ( 2014 ). Karen Simonyan and Andrew Zisserman. 2014. Very deep convolutional networks for large-scale image recognition. arXiv (1409.1556) (2014)."},{"key":"e_1_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.2307\/41409970"},{"key":"e_1_2_1_37_1","volume-title":"Proc. SPIE","volume":"3314","author":"Soutar Colin","year":"1998","unstructured":"Colin Soutar , Danny Roberge , Alex Stoianov , Rene Gilroy , and Bhagavatula Vijaya Kumar . 1998 . Biometric encryption using image processing . Proc. SPIE , Vol. 3314 . 178--188. DOI:https:\/\/doi.org\/10.1117\/12.304705 10.1117\/12.304705 Colin Soutar, Danny Roberge, Alex Stoianov, Rene Gilroy, and Bhagavatula Vijaya Kumar. 1998. Biometric encryption using image processing. Proc. SPIE, Vol. 3314. 178--188. DOI:https:\/\/doi.org\/10.1117\/12.304705"},{"key":"e_1_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/CW.2019.00054"},{"key":"e_1_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1142\/S0218001415560133"},{"key":"e_1_2_1_40_1","volume-title":"Nasrabadi","author":"Talreja Veeru","year":"2017","unstructured":"Veeru Talreja , Matthew C. Valenti , and Nasser M . Nasrabadi . 2017 . Multibiometric secure system based on deep learning. arXiv (1708.02314v1) (2017). Veeru Talreja, Matthew C. Valenti, and Nasser M. Nasrabadi. 2017. Multibiometric secure system based on deep learning. arXiv (1708.02314v1) (2017)."},{"key":"e_1_2_1_41_1","unstructured":"Danny Thakkar. 2018. Unimodal Biometrics vs. Multimodal Biometrics. Retrieved from https:\/\/www.bayometric.com\/unimodal-vs-multimodal\/.  Danny Thakkar. 2018. Unimodal Biometrics vs. Multimodal Biometrics. Retrieved from https:\/\/www.bayometric.com\/unimodal-vs-multimodal\/."},{"key":"e_1_2_1_42_1","unstructured":"Danny Thakkar. 2019. Fingerprint vs. Finger-vein: The Quest for Ideal Biometric Authentication. Retrieved from Bayometric.com.  Danny Thakkar. 2019. Fingerprint vs. Finger-vein: The Quest for Ideal Biometric Authentication. Retrieved from Bayometric.com."},{"key":"e_1_2_1_43_1","unstructured":"Danny Thakkar. 2019. An Overview of Biometric Iris Recognition Technology and Its Application Areas. Retrieved from Bayometric.com.  Danny Thakkar. 2019. An Overview of Biometric Iris Recognition Technology and Its Application Areas. Retrieved from Bayometric.com."},{"volume-title":"Proceedings of the International Workshop on Modeling and Simulation in Biometric Technology. 87--98","author":"Yanushkevich S.","key":"e_1_2_1_44_1","unstructured":"S. Yanushkevich , A. Stoica , S. N. Srihari , V. Shmerko , and M. Gavrilova . 2004. Simulation of biometric information: The new generation of biometric systems . In Proceedings of the International Workshop on Modeling and Simulation in Biometric Technology. 87--98 . S. Yanushkevich, A. Stoica, S. N. Srihari, V. Shmerko, and M. Gavrilova. 2004. Simulation of biometric information: The new generation of biometric systems. In Proceedings of the International Workshop on Modeling and Simulation in Biometric Technology. 87--98."},{"key":"e_1_2_1_45_1","unstructured":"Andy Zeng. 2018. Iris Recognition. Retrieved from cs.princeton.edu.  Andy Zeng. 2018. Iris Recognition. 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