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the Korean Institute of Electrical Engineers
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2020-12
(Vol.69P No.04)
10.5370/KIEEP.2020.69.4.267
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REF
References
1
Wang Xinran, Kohno Tadayoshi, Blakley Bob, 2014, Poly- morphism as a Defense for Automated Attack of Websites, in Int. Conf. on Appl. Cryptography and Netw. Secur., pp. 513-530
2
Goedde Amanda, Jul 2020, Credential Stuffing in the Media Industry, Akamai, [Online]. Available: https://www.akamai.com/us/en/multimedia/documents/state-of-the-internet/soti-security-credential-stuffing-in-the-media-industry-report-2020.pdf
3
J.-H. Ki, Sep 2017, The Past and Present of Authentication Technology, ITFIND, pp. 13-22
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Ometov Aleksandr, Jan 2018, Multi-Factor Authentication: A Survey, Cryptography, Vol. 2, No. 1, pp. 1-31
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Wiefling Stephan, Lo Iacono Luigi, 2019, Is This Really You? An Empirical Study on Risk-Based Authentication Applied in the Wild, IFIP Adv. in Inf. and Commun. Technol., Vol. 562, pp. 134-148
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Wiefling Stephan, Dürmuth Markus, Lo Iacono Luigi, 2020, More Than Just Good Passwords? A Study on Usability and Security Perceptions of Risk-based Authentication, arXiv:2010.00339
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Jonghyun Lee, 2020, Exploring the prediction model for middle school low-performing students ratio in mathematics using machine learning, Ph.D. dissertation, Youngnam University, Daegu, Korea
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Yunhye Oh, 2019, Comparative experiment of Logistic Regression and Machine Learning Performance of Support Vector Machines, M.S. thesis, Kookmin University, Seoul, Korea
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Jiacang Ho, Dae-Ki Kang, 2015, Sequence Alignment with Dynamic Divisor Generation for Keystroke Dynamics Based User Authentication, J. of Sensors, Vol. 2015, pp. 1-14
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Raul Nataasha, D’mello Royston, Bhalerao Mander, 2019, Keystroke Dynamics Authentication Using Small Datasets, Commun. in Comput. and Inf. Sci., Vol. 939, pp. 89-96
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Pilseong Kang, Seongjun Cho, 2012, A Study on User Authentication based on Keystroke Dynamics of Long and Free Texts, IE interface, Vol. 25, No. 3, pp. 290-299
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Sepczuk Mariusz, Kotulski Zbigniew, 2018, A new risk- based authentication management model oriented on user’s experience, Comput. & Secur., Vol. 73, pp. 17-33
13
2019, Network intrusion detection system using machine learning algorithm, M.S. thesis, Sungkyunkwan University, Seoul, Korea