TypeNet: Scaling up Keystroke Biometrics
We study the suitability of keystroke dynamics to authenticate 100K users typing free-text. For this, we first analyze to what extent our method based on a Siamese Recurrent Neural Network (RNN) is able to authenticate users when the amount of data per user is scarce, a common scenario in free-text keystroke authentication. With 1K users for testing the network, a population size comparable to previous works, TypeNet obtains an equal error rate of 4.8% using only 5 enrollment sequences and 1 test sequence per user with 50 keystrokes per sequence. Using the same amount of data per user, as the number of test users is scaled up to 100K, the performance in comparison to 1K decays relatively by less than 5%, demonstrating the potential of TypeNet to scale well at large scale number of users. Our experiments are conducted with the Aalto University keystroke database. To the best of our knowledge, this is the largest free-text keystroke database captured with more than 136M keystrokes from 168K users.
We have developed a novel method for the generation of high-resolution synthetic hand-print images. Specific traits such as fingerprint, palmprint and hand-shape are synthesized to obtain a whole hand-print. Each trait is generated by a methodology that mimics the nature of the corresponding biometric data and their main degrees of freedom. The biometric traits are then integrated into a single high-resolution realistic image. A quantitative validation of the obtained patterns is carried out in the context of minutiae matching by comparing genuine and impostor distributions between synthetic and real hand-prints. The proposed approach also proved to be useful for algorithm training/optimization.
MultiLock: Mobile Active Authentication based on Multiple Biometric and Behavioral Patterns
We have developed a mobile active authentication system based on an ensemble of biometrics and behavior-based profiling signals. We consider seven different data channels and their combination. Touch dynamics (touch gestures and keystroking), accelerometer, gyroscope, WiFi, GPS location and app usage are all collected during humanmobile interaction to authenticate the users. We evaluate two approaches: one-time authentication and active authentication. In one-time authentication, we employ the information of all channels available during one session. For active authentication we take advantage of mobile user behavior across multiple sessions by updating a confidence value of the authentication score. Our experiments are conducted on the semi-uncontrolled UMDAA-02 database. This database comprises smartphone sensor signals acquired during natural human-mobile interaction. Our results show that different traits can be complementary and multimodal systems clearly increase the performance with accuracies ranging from 82.2% to 97.1% depending on the authentication scenario.
Selected publications in this topic:
M. A. Ferrer, M. Diaz-Cabrera, C. Carmona-Duarte, A. Morales, “A Behavioral Handwriting Model for Static and Dynamic Signature Synthesis”. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, no. 6, pp. 1041-1053, June 2017. [pdf]
M. A. Ferrer, M. Diaz-Cabrera, A. Morales, “Static Signature Synthesis: A Neuromotor Inspired Approach for Biometrics,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 37 (3), pp. 667-680, March 2015. [pdf]
J. Galbally, M. Diaz-Cabrera, M. A. Ferrer, M. Gomez-Barrero, A. Morales and J. Fierrez, “On-Line Signature Recognition Through the Combination of Real Dynamic Data and Synthetically Generated Static Data“, Pattern Recognition, vol. 48, pp. 2921–2934, 2015. [pdf]
A. Morales, A. Acien, J. Fierrez, J.V. Monaco, R. Tolosana, R. Vera-Rodriguez, Javier Ortega-Garcia, “Keystroke Biometrics in Response to Fake News Propagation in a Global Pandemic,” Proc. of IEEE International Workshop on Secure Digital Identity Management (SDIM), Madrid, Spain, 2020. [pdf][media]
A. Morales, R. Cappelli, M. A. Ferrer, D. Maltoni, “Synthesis and Evaluation of High Resolution Hand-Prints“, IEEE Transactions on Information Forensics and Security, vol. 9 (11), pp. 1922 – 1932, 2014.
A. Acien, A. Morales, R. Vera-Rodriguez, J. Fierrez, O. Delgado, “Smartphone Sensors For Modeling Human-Computer Interaction: General Outlook And Research Datasets For User Authentication,” Proc. of IEEE Intl. Workshop on Consumer Devices and Systems (CDS), Madrid, Spain, 2020. [pdf]
A. Acien, J.V. Monaco, A. Morales, R. Vera-Rodriguez, J. Fierrez, “TypeNet: Scaling up Keystroke Biometrics,” arXiv:2004.03627, 2020 [pdf]
R Tolosana, R Vera-Rodriguez, J Fierrez, A Morales, J Ortega-Garcia, “DeepFakes and Beyond: A Survey of Face Manipulation and Fake Detection,” arXiv:2001.00179, 2020. [pdf]
D. Valdes-Ramirez, M. A. Medina-Perez, R. Monroy, O. Loyola-Gonzalez, J. Rodríguez, A. Morales and F. Herrera, “A Review of Fingerprint Feature Representations and Their Applications for Latent Fingerprint Identification: Trends and Evaluation“, IEEE Access, vol. 7, n. 1, December 2019. [pdf]
R. Tolosana, R. Vera-Rodriguez, J. Fierrez, A. Morales and J. Ortega-Garcia, “Do You Need More Data? The DeepSignDB On-Line Handwritten Signature Biometric Database“, Proc. 15th International Conference on Document Analysis and Recognition, Sydney, Australia, September 2019. [pdf]
A. Acien, A. Morales, R. Vera-Rodriguez, J. Fierrez, R. Tolosana, “MultiLock: Mobile Active Authentication based on Multiple Biometric and Behavioral Patterns,” Proc. of ACM In. Conf. on Multimedia, Workshop on Multimodal Understanding and Learning for Embodied Applications, pp. 53-59, 2019. [pdf]
A. Acien, A. Morales, R. Vera-Rodriguez, J. Fierrez, “Keystroke Mobile Authentication: Performance of Long-Term Approaches and Fusion with Behavioral Profiling,” Proc. of Iberian Conference on Pattern Recognition and Image Analysis, Madrid, Spain, pp. 12-24, 2019. [pdf]
J. Hernandez-Ortega, J. Fierrez, A. Morales and J. Galbally, “Introduction to Face Presentation Attack Detection“, S. Marcel and M. Nixon and J. Fierrez and N. Evans (Eds.) in Handbook of Biometric Anti-Spoofing, Springer, pp. 187-206, 2019. [pdf]
A. Morales, J. Fierrez and J. Galbally and Marta Gomez-Barrero, “Introduction to Iris Presentation Attack Detection“, S. Marcel and M. Nixon and J. Fierrez and N. Evans (Eds.) in Handbook of Biometric Anti-Spoofing, Springer, pp. 135-150, 2019.
J. Hernandez-Ortega, J. Fierrez, E. Gonzalez-Sosa and A. Morales, “Continuous Presentation Attack Detection in Face Biometrics based on Heart Rate“, X. Bai et al. (Eds.) in Video Analytics. Face and Facial Expression Recognition, LNCS, Springer, vol. 11264, 2019. [pdf]
J. Fierrez, A. Morales, R. Vera-Rodriguez and D. Camacho, “Multiple Classifiers in Biometrics. Part 1: Fundamentals and Review“, Information Fusion, vol. 44, pp. 57-64, November 2018.
J. Fierrez, A. Pozo, M. Martinez-Diaz, J. Galbally and A. Morales, “Benchmarking Touchscreen Biometrics for Mobile Authentication“, IEEE Trans. on Information Forensics and Security, vol. 13, n. 11, pp. 2720-2733, November 2018.
J. Fierrez, A. Morales, R. Vera-Rodriguez and D. Camacho, “Multiple Classifiers in Biometrics. Part 2: Trends and Challenges“, Information Fusion, vol. 44, pp. 103-112, November 2018.
R. Tolosana, M. Gomez-Barrero, J. Kolberg, A. Morales, C. Busch and J. Ortega-Garcia, “Towards Fingerprint Presentation Attack Detection Based on Convolutional Neural Networks and Short Wave Infrared Imaging“, in Proc. 17th International Conference of the Biometrics Special Interest Group (BIOSIG), September 2018.
A. Morales, M. A. Ferrer, R. Cappelli, D. Maltoni, J. Fierrez and J. Ortega-Garcia, “Synthesis of Large Scale Hand-Shape Databases for Biometric Applications“, Pattern Recognition Letters, vol. 68 (1), pp. 183–189, December 2015.
A. Morales, M. A. Medina-Pérez, M. A. Ferrer, M. García-Borroto, L. Altamirano Robles, “LPIDB v1.0 – Latent Palmprint Identification Database“, in Proc. of International Joint Conference on Biometrics (ICB), Clearwater, Florida, USA, pp. 1-6, 2014.
M. Diaz-Cabrera, M. Ferrer and A. Morales, “Cognitive-Based Model to Generate Duplicated Static Signature Images”, in Proc. of 14th International Conference on Frontiers in Handwriting Recognition (ICFHR), pp. 482-487, Creete, Greece, 1-4 September, 2014. Best Student Paper Award.
M. A. Ferrer, A. Morales, A. Diaz. “An Approach to SWIR Hyperspectral Hand Biometrics”, Information Science, vol. 268, pp. 3-19, 2014.
M. A. Ferrer, J. F. Vargas, A. Morales and A. D. Ordóñez, “Robustness of Off-line Signature Verification based on Gray Level Feratures”, IEEE Transactions Information Forensics & Security, vol. 7, No. 3, pp. 966-977, 2012.