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http://dx.doi.org/10.13089/JKIISC.2016.26.5.1161

Mobile Finger Signature Verification Robust to Skilled Forgery  

Nam, Seng-soo (Kongju National University)
Seo, Chang-ho (Kongju National University)
Choi, Dae-seon (Kongju National University)
Publication Information
Journal of the Korea Institute of Information Security & Cryptology / v.26, no.5, 2016 , pp. 1161-1170 More about this Journal
Abstract
In this paper, we provide an authentication technology for verifying dynamic signature made by finger on smart phone. In the proposed method, we are using the Auto-Encoder-based 1 class model in order to effectively distinguish skilled forgery signature. In addition to the basic dynamic signature characteristic information such as appearance and velocity of a signature, we use accelerometer value supported by most of the smartphone. Signed data is re-sampled to give the same length and is normalized to a constant size. We built a test set for evaluation and conducted experiment in three ways. As results of the experiment, the proposed acceleration sensor value and 1 class model shows 6.9% less EER than previous method.
Keywords
Deep learning; AE; Mobile Signature; One Class; Biometric Recognition;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 S.S. Arora, et al, "3D fingerprint phantoms," Proc. of 22nd Int. Conf. on Pattern Recognition, pp. 684-689, Sweden, Aug. 2014.
2 H. Malik and H. Farid, "Audio Forensics from Acoustic Reverberation," Proc. IEEE Int'l Conf. Acoustics, Speech, Signal Processing. pp. 1710-1713, USA, March 2010.
3 T. Fladsrud, "Face recognition in a border control environment: Non-zero effort attacks effect on false acceptance rate," Master thesis, Gjovik Univ. College, Norway, 2005.
4 D. Kim and J. Paik, "Gait recognition using active shape model and motion prediction," Computer Vision IET, vol. 4, no. 1, pp. 25-36, March 2010.   DOI
5 M. C. Thomas and A. P. M. S. Pradeepa, "A comprehensive review on vision based hand gesture recognition technology," International Journal of Research in Advent Technology, Vol. 2, no. 1, pp.303-310, January, 2014.
6 R. P. Krish, J. Fierrez, J. Galbally and M. Martinez-Diaz, "Dynamic Signature Verification on Smart Phones," In Communications in Computer and Information Science, vol 365, pp.213-222. 2013.   DOI
7 M. A. Ferrer, J. B. Alonso, and C.M. Travieso, "Offline geometric parameters for automatic signature verification using fixed-point arithmetic," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 6, pp.993-997, Jun. 2005.   DOI
8 M. Martinez-Diaz, J. Fierrez, J. Galbally and J. Ortega-Garcia, "Towards mobile authentication using dynamic signature verification: useful features and performance evaluation," In Proceedings of the International Conference on Pattern Recognition, ICPR, pp.1-5, Dec. 2008.
9 N. Sae-Bae and N. Memon, "Online signature verification on mobile devices," IEEE Trans. Inf. Forensics Security, vol. 9, no. 6, pp.933-947, Jun. 2014.   DOI
10 N. Paudel, M. Querini and G. F. Italiano, "Handwritten Signature Verification for Mobile Phones," International Conference on Information Systems Security and Privacy(ICISSP), pp46-52, 2016.
11 R. Kumar, J.D. Sharma and B. Chanda, " Writer-independent off-line signature verification using surroundedness feature," Pattern Recognition Letters, vol. 33, no. 3, pp.301-308, Feb. 2012.   DOI
12 G. Dimauro, S. Impedovo, M.G.Lucchese, R.Modugno and G. Pirlo, "Recent Advancements in Automatic Signature Verification," Int'l Workshop on Frontiers in Handwriting Recognition(IWFHR), pp. 179-184, Oct, 2004.
13 N. Li, J. Liu, Q. Li and X. Luo, "Online Signature Verification Based on Biometric Features," International Conference on System Sciences, pp. 5527-5534, Jan. 2016.
14 A. Fischer, M. Diaz, R. Plamondon and M.A. Ferrer, "Robust score normalization for DTW-based on-line signature verification," International Conference on document analysis and recognition, pp.241-245, Aug. 2015.
15 M. Fayyza, et al. "Online Signature Verification Based on Feature Representation," IEEE Artificial Intelligence and signal Processing, pp.211-216, Mar. 2015.
16 W.S. Wijesoma, M. Mingming and K. W. Yue, "On-line signature verification using a computational intelligence approach," Lecture Notes in Computer Science Springer-Verlag, vol. 2206, pp.699-711, Oct. 2001.
17 S.Y. Ryu, D.J. Lee, M.G. Chun, "A Robust On-line Signature Verification System," International Journal of Fuzzy Logic and Intelligent Systems, vol. 3, no. 1, pp.27-31, 2003.   DOI
18 C. Gruber, et al, "Online Signature Verification With Support Vector Machines Based on LCSS Kernel Functions," IEEE Transactions on Systems Browse Journals & Magazines, Vol. 40, No 4, pp.1088-1100, Aug. 2010.
19 V. Irnmanesh, et al. "Online Signature Verification Using Neural Network and Pearson Correlation Features", IEEE Conference on Open Systems (ICOS), pp.18-21, Dec. 2014.
20 A. Makhzani and B.J. Frey, "Winner-take-all autoencoders," Neural Information Processing Systems(NIPS), pp.2773-2781, CANADA, Dec. 2015.
21 D.I. Chae, et al, " Hidden Singer Contest: Auto-encoder based singer Identification," Joint Conference on communications and Information (JCCI), pp.629-632, Apr. 2016.
22 P.O. Kristensson, T. Nicholson, and A. Quigley, "Continuous recognition of one-handed and two-handed gestures using 3D full-body motion tracking sensors," Proc. of ACM Int'l. Conf. on Intelligent User Interfaces, pp.89-92, 2012.
23 P.O. Kristensson and L.C. Denby, "Continuous recognition and visualization of pen strokes and touch-screen gestures," Proc. of Euro graphics Symposium on Sketch-Based Interfaces and Modeling, pp.95-102, 2011.
24 R. Reed and R. Marks, "Neural smithing supervised learning in feedforward artificial neural networks," Cambridge MA: MIT press, 1999.
25 Y. N. Dauphi, H. D. Vries and Y. Beigio, "Equilibrated adaptive learning rates for non-convex optimization", arXiv preprint arXiv:2502.04390, 2015.
26 A. Krizhevsky and G.E. Hinton, "Using very deep autoencoders for content-based image retrieval", In Proceedings of the European Symposium of Artifical Neural Networks, pp.489-494, Belgium. 2011.
27 https://en.wikipedia.org/wiki/Autoencoder
28 A. Krizhevsky, I. Sutskever and G. Hinton, "ImageNet Classification with Deep Convolutional Neural Networks", In Neural Information Processiong Systems. 2012.
29 https://en.wikipedia.org/wiki/Biometrics