. Iso/iec, Information technology-Biometric performance testing and reporting-Part 1: Principles and framework, 2006.

A. F. Abate, S. Barra, L. Gallo, and F. Narducci, Kurtosis and skewness at pixel level as input for som networks to iris recognition on mobile devices, Pattern Recognition Letters, vol.91, pp.37-43, 2017.

N. U. Ahmed, S. Cvetkovic, E. H. Siddiqi, A. Nikiforov, and I. Nikiforov, Combining iris and periocular biometric for matching visible spectrum eye images, Pattern Recognition Letters, vol.91, pp.11-16, 2017.

K. Ahuja, R. Islam, F. A. Barbhuiya, and K. Dey, Convolutional neural networks for ocular smartphone-based biometrics, Pattern Recognition Letters, vol.91, pp.17-26, 2017.

F. Alonso-fernandez, K. B. Raja, C. Busch, and J. Bigun, Log-likelihood score level fusion for improved cross-sensor smartphone periocular recognition, 25th European Signal Processing Conference (EUSIPCO), pp.271-275, 2017.

N. Amjed, F. Khalid, R. W. Rahmat, and H. B. Madzin, Noncircular iris segmentation based on weighted adaptive hough transform using smartphone database, Journal of Computational and Theoretical Nanoscience, vol.15, issue.3, pp.739-743, 2018.

G. Baldini and G. Steri, A survey of techniques for the identification of mobile phones using the physical fingerprints of the built-in components, IEEE Communications Surveys Tutorials, vol.19, issue.3, pp.1761-1789, 2017.

S. Barra, M. De-marsico, M. Nappi, F. Narducci, and D. Riccio, A hand-based biometric system in visible light for mobile environments, Information Sciences, 2018.

Z. Boulkenafet, J. Komulainen, Z. Akhtar, A. Benlamoudi, D. Samai et al., A competition on generalized software-based face presentation attack detection in mobile scenarios, 2017 IEEE International Joint Conference on, pp.688-696, 2017.
DOI : 10.1109/btas.2017.8272758

Z. Boulkenafet, J. Komulainen, L. Li, X. Feng, and A. Hadid, Oulu-npu: A mobile face presentation attack database with real-world variations, 12th IEEE International Conference on Automatic Face Gesture Recognition (FG 2017), pp.612-618, 2017.
DOI : 10.1109/fg.2017.77

C. Burt, Smartphone growth to slow in 2018 as mobile biometrics mostly stay the course, 2018.

M. Castrillón-santana, M. De-marsico, M. Nappi, F. Narducci, and H. Proença, Mobile iris challenge evaluation ii: results from the icpr competition, Pattern Recognition (ICPR), 2016 23rd International Conference on, pp.149-154, 2016.

D. Crouse, H. Han, D. Chandra, B. Barbello, and A. K. Jain, Continuous authentication of mobile user: Fusion of face image and inertial measurement unit data, 2015 International Conference on Biometrics (ICB), pp.135-142, 2015.

P. Fernandez-lopez, J. Sanchez-casanova, P. Tirado-martín, and J. Liu-jimenez, Optimizing resources on smartphone gait recognition, 2017 IEEE International Joint Conference on Biometrics (IJCB), pp.31-36, 2017.
DOI : 10.1109/btas.2017.8272679

J. Fierrez, A. Pozo, M. Martinez-diaz, J. Galbally, and A. Morales, Benchmarking touchscreen biometrics for mobile authentication, IEEE Transactions on Information Forensics and Security, vol.13, issue.11, pp.2720-2733, 2018.
DOI : 10.1109/tifs.2018.2833042

R. D. Findling, M. Holzl, and R. Mayrhofer, Mobile matchon-card authentication using offline-simplified models with gait and face biometrics, IEEE Transactions on Mobile Computing, pp.1-1, 2018.
DOI : 10.1109/tmc.2018.2812883

R. D. Findling and R. Mayrhofer, Towards secure personal device unlock using stereo camera pan shots, International Conference on Computer Aided Systems Theory, pp.417-425, 2013.
DOI : 10.1007/978-3-642-53862-9_53

M. Frucci, C. Galdi, M. Nappi, D. Riccio, and G. Sanniti-di-baja, Idem: Iris detection on mobile devices, Pattern Recognition (ICPR), 2014 22nd International Conference on, pp.1752-1757, 2014.
DOI : 10.1109/icpr.2014.308

M. Gadaleta and M. Rossi, Idnet: Smartphone-based gait recognition with convolutional neural networks, Pattern Recognition, vol.74, pp.25-37, 2018.

C. Galdi and J. Dugelay, Fire: Fast iris recognition on mobile phones by combining colour and texture features, Pattern Recognition Letters, vol.91, pp.44-51, 2017.
DOI : 10.1016/j.patrec.2017.01.023

C. Galdi, M. Nappi, J. Dugelay, and Y. Yu, Exploring new authentication protocols for sensitive data protection on smartphones, IEEE Communications Magazine, vol.56, issue.1, pp.136-142, 2018.
DOI : 10.1109/mcom.2017.1700342

M. I. Gofman, S. Mitra, and N. Smith, Hidden markov models for feature-level fusion of biometrics on mobile devices, 2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA), pp.1-2, 2016.

A. Goode, Bring your own finger how mobile is bringing biometrics to consumers, Biometric Technology Today, issue.5, pp.5-9, 2014.
DOI : 10.1016/s0969-4765(14)70088-8

M. Günther, A. Costa-pazo, C. Ding, E. Boutellaa, G. Chiachia et al., The 2013 face recognition evaluation in mobile environment, Biometrics (ICB), 2013 International Conference on, pp.1-7, 2013.

A. G. Howard, M. Zhu, B. Chen, D. Kalenichenko, W. Wang et al., Mobilenets: Efficient convolutional neural networks for mobile vision applications, 2017.

. Iso/iec, Information technology-Biometric presentation attack detection-Part 3: Testing and reporting. Standard, International Organization for Standardization, 2017.

E. Khoury, B. Vesnicer, J. Franco-pedroso, R. Violato, Z. Boulkcnafet et al., The 2013 speaker recognition evaluation in mobile environment, Biometrics (ICB), 2013 International Conference on, pp.1-8, 2013.
DOI : 10.1109/icb.2013.6613025
URL : https://hal.archives-ouvertes.fr/hal-01262087

G. Li and P. Bours, A novel mobilephone application authentication approach based on accelerometer and gyroscope data, 2018 International Conference of the Biometrics Special Interest Group (BIOSIG), 2018.

U. Mahbub and R. Chellappa, Path: person authentication using trace histories, Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), pp.1-8, 2016.

S. Marcel, C. Mccool, P. Mat?jka, T. Ahonen, J. Cernock`cernock et al.,

S. Chakraborty, V. Balasubramanian, S. Panchanathan, and C. H. ,

J. Chan and . Kittler, On the results of the first mobile biometry (mobio) face and speaker verification evaluation, Recognizing Patterns in Signals, Speech, Images and Videos, pp.210-225, 2010.

M. De-marsico, M. Nappi, F. Narducci, and H. Proença, Insights into the results of miche i-mobile iris challenge evaluation, Pattern Recognition, vol.74, pp.286-304, 2018.

M. De-marsico, M. Nappi, and H. Proença, Results from miche ii mobile iris challenge evaluation ii, Pattern Recognition Letters, vol.91, pp.3-10, 2017.

W. Meng, D. S. Wong, S. Furnell, and J. Zhou, Surveying the development of biometric user authentication on mobile phones, IEEE Communications Surveys & Tutorials, vol.17, issue.3, pp.1268-1293

J. Moar,

M. Muaaz and R. Mayrhofer, Smartphone-based gait recognition: From authentication to imitation, IEEE Transactions on Mobile Computing, vol.16, issue.11, pp.3209-3221, 2017.

M. Muaaz and R. Mayrhofer, Smartphone-based gait recognition: from authentication to imitation, IEEE Transactions on Mobile Computing, vol.16, issue.11, pp.3209-3221, 2017.

A. Munalih and W. Ardianto, Finger vein biometrics: The future for a mobile authentication system, 2017.

T. J. Neal and D. L. Woodard, Surveying biometric authentication for mobile device security, Journal of Pattern Recognition Research, vol.1, pp.74-110, 2016.

X. Niu, H. Han, S. Shan, and X. Chen, Continuous heart rate measurement from face: A robust rppg approach with distribution learning, IEEE IJCB, pp.642-650, 2017.

X. Niu, H. Han, S. Shan, and X. Chen, Synrhythm: Learning a deep heart rate estimator from general to specific, ICPR, 2018.

J. Olivares-mercado, K. Toscano-medina, G. Sanchez-perez, H. Perez-meana, and M. Nakano-miyatake, Face recognition system for smartphone based on lbp, 5th International Workshop on Biometrics and Forensics (IWBF), pp.1-6, 2017.

K. Patel, H. Han, and A. K. Jain, Secure face unlock: Spoof detection on smartphones, IEEE Transactions on Information Forensics and Security, vol.11, issue.10, pp.2268-2283, 2016.

P. Perera and V. M. Patel, Efficient and low latency detection of intruders in mobile active authentication, IEEE Transactions on Information Forensics and Security, vol.13, issue.6, pp.1392-1405, 2018.

E. Rahmawati, M. Listyasari, A. S. Aziz, S. Sukaridhoto, F. A. Damastuti et al., Digital signature on file using biometric fingerprint with fingerprint sensor on smartphone, 2017 International Electronics Symposium on Engineering Technology and Applications (IES-ETA), pp.234-238, 2017.

K. B. Raja, R. Raghavendra, V. K. Vemuri, and C. Busch, Smartphone based visible iris recognition using deep sparse filtering, Pattern Recognition Letters, vol.57, pp.33-42, 2015.

K. B. Raja, P. Wasnik, R. Raghavendra, and C. Busch, Robust face presentation attack detection on smartphones : An approach based on variable focus, 2017 IEEE International Joint Conference on Biometrics (IJCB), pp.651-658, 2017.
DOI : 10.1109/btas.2017.8272753

A. Rattani and R. Derakhshani, Online co-training in mobile ocular biometric recognition, 2017 IEEE International Symposium on Technologies for Homeland Security (HST), pp.1-5, 2017.
DOI : 10.1109/ths.2017.7943490

A. Rattani, R. Derakhshani, S. K. Saripalle, and V. Gottemukkula, Icip 2016 competition on mobile ocular biometric recognition. In Image Processing (ICIP), 2016 IEEE International Conference on, pp.320-324, 2016.
DOI : 10.1109/icip.2016.7532371

N. Reddy, A. Rattani, and R. Derakhshani, A robust scheme for iris segmentation in mobile environment, 2016.
DOI : 10.1109/ths.2016.7568948

U. Scherhag, A. Nautsch, C. Rathgeb, M. Gomez-barrero, R. N. Veldhuis et al., Biometric systems under morphing attacks: Assessment of morphing techniques and vulnerability reporting, 2017 International Conference of the Biometrics Special Interest Group (BIOSIG), pp.1-7, 2017.
DOI : 10.23919/biosig.2017.8053499

M. Stokkenes, R. Ramachandra, K. B. Raja, M. Sigaard, M. Gomez-barrero et al., Multi-biometric template protection on smartphones: An approach based on binarized statistical features and bloom filters, Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, pp.385-392, 2017.
DOI : 10.1007/978-3-319-52277-7_47

L. Sun, Y. Wang, B. Cao, P. S. Yu, W. Srisa et al., Sequential keystroke behavioral biometrics for mobile user identification via multi-view deep learning, Machine Learning and Knowledge Discovery in Databases, pp.228-240, 2017.
DOI : 10.1007/978-3-319-71273-4_19
URL : http://arxiv.org/pdf/1711.02703

R. Tan and M. Perkowski, Toward improving electrocardiogram (ecg) biometric verification using mobile sensors: A two-stage classifier approach, Sensors, vol.17, issue.2, p.410, 2017.
DOI : 10.3390/s17020410
URL : http://www.mdpi.com/1424-8220/17/2/410/pdf

R. Tolosana, R. Vera-rodriguez, J. Fierrez, A. Morales, and J. Ortega-garcia, Benchmarking desktop and mobile handwriting across cots devices: The e-biosign biometric database, PLOS ONE, vol.12, issue.5, pp.1-17, 2017.
DOI : 10.1371/journal.pone.0176792
URL : https://doi.org/10.1371/journal.pone.0176792

A. Ungureanu, S. Thavalengal, T. E. Cognard, C. Costache, and P. Corcoran, Unconstrained palmprint as a smartphone biometric, IEEE Transactions on Consumer Electronics, vol.63, issue.3, pp.334-342, 2017.
DOI : 10.1109/tce.2017.014994

R. Vera-rodriguez, R. Tolosana, J. Ortega-garcia, and J. Fierrez, E-biosign: stylus-and finger-input multi-device database for dynamic signature recognition, IWBF, pp.1-6, 2015.
DOI : 10.1109/iwbf.2015.7110242

P. Wasnik, K. B. Raja, R. Ramachandra, and C. Busch, Assessing face image quality for smartphone based face recognition system, 5th International Workshop on Biometrics and Forensics (IWBF), pp.1-6, 2017.
DOI : 10.1109/iwbf.2017.7935089

P. Wasnik, K. Schafer, R. Ramachandra, C. Busch, and K. Raja, Fusing biometric scores using subjective logic for gait recognition on smartphone, 2017 International Conference of the Biometrics Special Interest Group (BIOSIG), pp.1-5, 2017.
DOI : 10.23919/biosig.2017.8053508

D. Wen, H. Han, and A. K. Jain, Face spoof detection with image distortion analysis, IEEE Transactions on Information Forensics and Security, vol.10, issue.4, pp.746-761, 2015.

A. Wojciechowska, M. Chora´schora´s, and R. Kozik, The overview of trends and challenges in mobile biometrics, Journal of Applied Mathematics and Computational Mechanics, vol.16, 2017.

M. Zhang, Q. Zhang, Z. Sun, S. Zhou, and N. U. Ahmed, The btas competition on mobile iris recognition, Biometrics Theory, Applications and Systems (BTAS), pp.1-7, 2016.
DOI : 10.1109/btas.2016.7791191

Q. Zhang, H. Li, Z. Sun, Z. He, and T. Tan, Exploring complementary features for iris recognition on mobile devices, Biometrics (ICB), 2016 International Conference on, pp.1-8, 2016.
DOI : 10.1109/icb.2016.7550079

Q. Zhang, H. Li, Z. Sun, and T. Tan, Deep feature fusion for iris and periocular biometrics on mobile devices, IEEE Transactions on Information Forensics and Security, vol.13, issue.11, pp.2897-2912, 2018.
DOI : 10.1109/tifs.2018.2833033