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http://dx.doi.org/10.3837/tiis.2017.12.025

Energy-Efficient Biometrics-Based Remote User Authentication for Mobile Multimedia IoT Application  

Lee, Sungju (Dept. of Computer Convergence Software, Korea University)
Sa, Jaewon (Dept. of Computer Convergence Software, Korea University)
Cho, Hyeonjoong (Dept. of Computer Convergence Software, Korea University)
Park, Daihee (Dept. of Computer Convergence Software, Korea University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.11, no.12, 2017 , pp. 6152-6168 More about this Journal
Abstract
Recently, the biometric-based authentication systems such as FIDO (Fast Identity Online) are increased in mobile computing environments. The biometric-based authentication systems are performed on the mobile devices with the battery, the improving energy efficiency is important issue. In the case, the size of images (i.e., face, fingerprint, iris, and etc.) affects both recognition accuracy and energy consumption, and hence the tradeoff analysis between the both recognition accuracy and energy consumption is necessary. In this paper, we propose an energy-efficient way to authenticate based on biometric information with tradeoff analysis between the both recognition accuracy and energy consumption in multimedia IoT (Internet of Things) transmission environments. We select the facial information among biometric information, and especially consider the multicore-based mobile devices. Based on our experimental results, we prove that the proposed approach can enhance the energy efficiency of GABOR+LBP+GRAY VALUE, GABOR+LBP, GABOR, and LBP by factors of 6.8, 3.6, 3.6, and 2.4 over the baseline, respectively, while satisfying user's face recognition accuracy.
Keywords
Multicore-based handheld device; energy consumption; biometric recognition; image compression; image transmission; tradeoff analysis;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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1 Y. Chen, J. Mair, Z. Huang, D. Eyers, and H. Zhang, "A State-Based Energy/Performance Model for Parallel Applications on Multicore Computers," in Proc. of Parallel Processing Workshops (ICPPW), 2015 44th International Conference on, pp. 230-239, September, 2015.
2 S. Lee, H. Kim, Y. Chung, and D. Park, "Energy Efficient Image/Video Data Transmission on Commercial Multi-Core Processors," Sensors, vol. 12, no. 11, pp. 14647-14670, November, 2012.   DOI
3 S. Lee, H. Kim, and Y. Chung, "Power-Time Tradeoff of Parallel Execution on Multi-core Platforms," Mobile, Ubiquitous, and Intelligent Computing, vol. 274, pp.157-163, 2014.
4 N. Hirofumi, N. Naoya, and T. Katsuya, "WT210/WT230 Digital Power Meters," Yokogawa TR 35, pp. 17-20, 2003. http://tmi.yokogawa.com/technical-library/white-papers/wt210wt230-digital-power-meters/
5 http://cvc.yale.edu/projects/yalefaces/yalefaces.html (accessed on 2016).
6 Z. He, Y. Liang, L. Chen, A. Hmad, and D. Wu, "Power-rate-distortion analysis for wireless video communication under energy constraints," IEEE Transactions on Circuits and Systems for Video Technology, vol. 15, no. 5, pp. 645-658, May, 2005.   DOI
7 Z. He, W. Cheng, and X. Chen, "Energy minimization of portable video communication devices based on power-rate-distortion optimization," IEEE Transactions on Circuits and Systems for Video Technology, vol. 18, no. 5, pp. 596-608, April, 2008.   DOI
8 D. Lee, H. Kim,M. Rahimi, D. Estrin, and J. Villasenor, "Energy-Efficient Image Compression for Resource-Constrained Platforms," IEEE Transactions on Image Processing, vol. 18, no. 9, pp. 2100-2113, May, 2009.   DOI
9 S. Beak, B. Hieu, H. Lee, S. Choi, I. Kim, K. Lee, Y. Lee, and T. Jeong, "Novel binary tree Huffman decoding algorithm and field programmable gate array implementation for terrestrial-digital multimedia broadcasting mobile handheld," IET Science, Measurement and Technology, vol. 6, no. 6, pp. 527-532, November, 2012.   DOI
10 B. Barney, "POSIX Threads Programming," Available online(accessed on 2016). http://www.llnl.gov/computing/tutorials/pthreads
11 X. Tan and B. Triggs, "Fusing Gabor and LBP Feature Sets for Kernel-Based Face Recognition," International Workshop on Analysis and Modeling of Faces and Gestures, pp. 235-249, 2007.
12 L. A. Cament, F. J. Galdames, K. W. Bowyer, and C. A. Perez, "Face recognition under pose variation with local Gabor features enhanced by Active Shape and Statistical Models," Pattern Recognition, vol. 48, no. 11, pp. 3371-3384, November 2015.
13 D. Huang, C. Shan, M. Ardabilian, Y. Wang, and L. Chen, "Local Binary Patterns and Its Application to Facial Image Analysis: A Survey," IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 41, no. 6, pp. 765-781, March, 2011.   DOI
14 G. P. Nam, B. J. Kang, and K. R. Park, "Robustness of Face Recognition to Variations of Illumination on Mobile Devices Based on SVM," TIIS, vol. 4, no.1, pp. 25-44, February, 2010.
15 X. Xiang, F. Liu, Y. Bi, Y. Wang, and J. Tang, "Local Similarity based Discriminant Analysis for Face Recognition," TIIS, vol. 9, no.11, pp. 4502-4518, November, 2015.
16 W. Li and L. Wang, "Near-infrared Face Recognition by Fusion of E-GV-LBP and FKNN," TIIS, vol. 9, no.1, pp. 208-223, January, 2015.
17 Q. Lin, J. Yang, N. Ye, R. Wang, and B. Zhang, "Face Recognition in Mobile Wireless Sensor Networks," International Journal of Distributed Sensor Networks, vol. 9, no. 9, August, 2013.
18 Y. Y. Park, Y. Choi, and K. Lee, "A Study on the Design and Implementation of Facial Recognition Application System," International Journal of Bio-Science and Bio-Technology, vol. 6, no. 2, pp.1-10, April, 2014.   DOI
19 https://fidoalliance.org/ (accessed on 2016).
20 M. Sahani, S. Subudhi, and M. Mohanty, "Design of Face Recognition based Embedded Home Security System," TIIS, vol. 10, no. 4, pp. 1751-1767, April, 2016.
21 A. T. Tran, J. Y. Kim, A. Chaudhry, B. Pham, and H-. G. Kim, "Visual Observation Confidence based GMM Face Recognition robust to Illumination Impact in a Real-world Database," TIIS, vol. 10, no.4, April, 2016.
22 A. Gorea and S. Guptab, "Full reference image quality metrics for JPEG compressed images," AEU-International Journal of Electronics and Communications, vol. 69, no. 2, pp. 604-608, February, 2015.   DOI
23 A. M. Kishk, N. W. Messiha, N. A. El-Fishawy, A. A. Alkafs, and A. H. Madian, "Low Energy Lossless Image Compression Algorithm for Wireless Sensor Network (LE-LICA)," Sensors & Transducers Journal, vol. 188, no. 5, pp. 102-106, May, 2015.
24 G. Weinhandel, H. Stogner, and A. Uhl, "Experimental study on lossless compression of biometric sample data," Proc. of Image and Signal Processing and Analysis, pp. 517-522, September, 2009.
25 A. Sepas-Moghaddam and M. Moin, "Face recognition in colour JPEG compressed domain," International Journal of Biometrics, vol. 6, no. 3, pp. 304-320, August, 2014.   DOI
26 M. Gerards, J. Hurink, and J. Kuper, "On the interplay between global DVFS and scheduling tasks with precedence constraints," IEEE Transactions on Computers, vol. 64, no. 6, pp. 1742-1754, June, 2015.   DOI
27 S. K. Saurav, G. Prasad, and M. Chauhan, "Adaptive Power Management for HPC applications," Green High Performance Computing (ICGHPC), 2016 2nd International Conference on, pp. 26-27, February, 2016.