參考文獻 |
[1] M. Tolentino, “iPhone Users Prefer Convenience Over Security?: Here’s Three Ways to Get Smart on Safety - SiliconANGLE,” 2013. [Online]. Available: https://siliconangle.com/blog/2013/04/18/iphone-users-prefer-convenience-over-security-heres-3-ways-to-get-smart-on-safety/. [Accessed: 25-Jun-2018].
[2] O. Mazhelis, J. Markkula, and J. Veijalainen, “An integrated identity verification system for mobile terminals,” Inf. Manag. Comput. Secur., vol. 13, pp. 367–378, 2005.
[3] McAfee, “More Than 30% of People Don’t Password Protect Their Mobile Devices | McAfee Blogs,” 2013. [Online]. Available: https://securingtomorrow.mcafee.com/consumer/identity-protection/unprotected-mobile-devices/. [Accessed: 04-Jul-2018].
[4] C. C. Lin, C. C. Chang, D. Liang, and C. H. Yang, “A new non-intrusive authentication method based on the orientation sensor for smartphone users,” Proc. 2012 IEEE 6th Int. Conf. Softw. Secur. Reliab. SERE 2012, pp. 245–252, 2012.
[5] C. C. Lin, C. C. Chang, and D. Liang, “A new non-intrusive authentication approach for data protection based on mouse dynamics,” Proc. - 2012 Int. Symp. Biometrics Secur. Technol. ISBAST 2012, pp. 9–14, 2012.
[6] C. C. Lin, C. C. Chang, and D. Liang, “A novel non-intrusive user authentication method based on touchscreen of smartphones,” Proc. - 2013 Int. Symp. Biometrics Secur. Technol. ISBAST 2013, pp. 212–216, 2013.
[7] C. Lin, C. Chang, and D. Liang, “Nonintrusive Authentication of Smartphone Users by Using Behavioral Biometrics Based on the Orientation Sensor and Touchscreen.”
[8] S. Ben-David and J. Blitzer, “Analysis of representations for domain adaptation,” Adv. Neural Inf. Process. Syst., vol. 19, pp. 137–144, 2007.
[9] S. J. Pan, I. W. Tsang, J. T. Kwok, and Q. Yang, “Domain adaptation via transfer component analysis,” IEEE Trans. Neural Networks, vol. 22, no. 2, pp. 199–210, 2011.
[10] L. Lamport, “Password authentication with insecure communication,” Commun. ACM, vol. 24, no. 11, pp. 770–772, 1981.
[11] N. Harini and T. R. Padmanabhan, “2CAuth: A new two factor authentication scheme using QR-code,” Int. J. Eng. Technol., vol. 5, no. 2, pp. 1087–1094, 2013.
[12] D. Dasgupta, A. Roy, and A. Nag, “Toward the design of adaptive selection strategies for multi-factor authentication,” Comput. Secur., vol. 63, no. September 2017, pp. 85–116, 2016.
[13] J. Bonneau, C. Herley, P. C. van Oorschot, and F. Stajano, “Passwords and the evolution of imperfect authentication,” Commun. ACM, vol. 58, no. 7, pp. 78–87, 2015.
[14] R. Amin, T. Gaber, G. Eltaweel, and A. E. Hassanien, “Bio-inspiring Cyber Security and Cloud Services: Trends and Innovations,” vol. 70, no. February, 2014.
[15] M. Pusara and C. E. Brodley, “User re-authentication via mouse movements,” Proc. 2004 ACM Work. Vis. data Min. Comput. Secur. - VizSEC/DMSEC ’04, p. 1, 2004.
[16] C. Cortes and V. Vapnik, “Support-Vector Networks,” Mach. Learn., vol. 20, no. 3, pp. 273–297, 1995.
[17] T. Joachims et al., “Introduction to Support Vector Machines,” Svm, pp. 1–15, 2002.
[18] X. Zhou, X. Zhang, and B. Wang, Online Support Vector Machine: A Survey. 2016.
[19] T. Kudo and Y. Matsumoto, “Chunking with Support Vector Machines,” Second Meet. North Am. Chapter Assoc. Comput. Linguist. Lang. Technol. 2001 - NAACL ’01, vol. 816, pp. 1–8, 2001.
[20] F. Cai and V. Cherkassky, “Generalized SMO Algorithm for SVM-Based which is the subject of this brief, falls into the last cate- Multitask Learning,” IEEE Trans. Neural Networks, vol. 23, no. 5, pp. 821–827, 2012.
[21] P.-H. Chen, R.-E. Fan, and C.-J. Lin, “A study on SMO-type decomposition methods for support vector machines.,” IEEE Trans. Neural Netw., vol. 17, no. 4, pp. 893–908, 2006.
[22] S. K. Shevade, S. S. Keerthi, C. Bhattacharyya, and K. R. K. Murthy, “Improvements to the SMO algorithm for SVM regression,” IEEE Trans. Neural Networks, vol. 11, no. 5, pp. 1188–1193, 2000.
[23] A. Bordes, L. Bottou, and P. Gallinari, “SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent,” J. Mach. Learn. Res., vol. 10, pp. 1737–1754, 2009.
[24] R. Singh, M. Vatsa, A. Ross, and A. Noore, “Biometric Classifier Update using Online Learning?: A Case Study in Near Infrared Face Verification,” Science (80-. )., no. January 2010, pp. 1–21, 2010.
[25] S. A. Putri, D. Liang, and C. Chang, “Nonintrusive Behavioral Biometric Authentication on Smartphones: An Online Learning Approach,” 2017.
[26] J. Blitzer, R. McDonald, and F. Pereira, “Domain adaptation with structural correspondence learning,” Proc. 2006 Conf. Empir. Methods Nat. Lang. Process. - EMNLP ’06, p. 120, 2006.
[27] F. Zhuang, X. Cheng, P. Luo, S. J. Pan, and Q. He, “Supervised Representation Learning?: Transfer Learning with Deep Autoencoders,” Ijcai, no. Ijcai, pp. 4119–4125, 2015.
[28] M. Mahmud, “Universal Transfer Learning,” pp. 135–149, 2008.
[29] Qiang Yang, “a Survey on Transfer Learning,” vol. 1, no. 10, pp. 1–15, 2010.
[30] I. K. Putri, S. H. Pramono, Rahmadwati, C. Chang, and D. Liang, “Optimized Active Learning to Collect User’s Behavior for Training Model Based on Non-intrusive Smartphone Authentication,” 2016. |