Browse > Article
http://dx.doi.org/10.13089/JKIISC.2020.30.3.379

Identity Verification in Financial Transactions Using a Stylus Pen  

Kim, Hyun-Ji (Hansung University)
Jang, Kyung-Bae (Hansung University)
Kwon, Hyeok-Dong (Hansung University)
Kim, Hyun-Jun (Hansung University)
Seo, Hwa-Jeong (Hansung University)
Publication Information
Journal of the Korea Institute of Information Security & Cryptology / v.30, no.3, 2020 , pp. 379-388 More about this Journal
Abstract
As the use of credit cards increases, security threats increase. In particular, despite being vulnerable to related crimes, such as fraudulent use of credit cards and theft of names, there are virtually no security procedures to authenticate the validity of user while paying with the credit card. In order to overcome these limitations of current credit card payments, we add a process of signing payment using a stylus pen with built-in acceleration sensor in the existing transaction method, and classifying and comparing the image of the signature and signature information measured by the sensor through the convolutional neural network. we propose a method to improve security in financial transactions by performing the user authentication process through the possession of the stylus pen and the characteristic values of the signature.
Keywords
styluspen; acceleration sensor; signature; 2 Factor Authentication; Convolution Neural Network;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
1 Incheon Paik, "Framework architecture for electronic commerce software system based on SET protocol," The Korean Institute of Information Scientists and Engineers, 25(1A), pp. 732-734, Apr. 1998.
2 Woosuk Chang, Kwangwoo Lee, Donghyun Choi, Hak Chong, Byunghee Lee, Younsung Choi, Seungjoo Kim and Dongho Won. "A study on SET and its transformation techniques," Journal of The Korea Institute of Information Security and Cryptology, 15(4), pp. 16-27, Aug. 2005.
3 Gonie Ahn, Jae Hyeong Yoo, Jae Hyeong Yoo and Seoung Bum Kim, "Explainable convolutional neural networks for multi-Sensor data," Journal of Korean institute of industrial engineers, 45(2), pp. 146-153, Apr. 2019.   DOI
4 Hyunsoo Ha and Byung-Yeon Hwang, "Machine learning model of gyro sensor data for drone flight control," Journal of Korea Multimedia Society, 20(6), pp. 927-934, Jun. 2017.   DOI
5 HyeonTae Ju and SungSoo Kim, "Voltage state diagnosis using the metric defined via kalman filter," Journal of the Research Institute for Computer and Information Communication, pp. 75-79, May. 2013.
6 Yunyoung Nam, Yoo-Joo Choi and We-Duke Cho, "Human activity recognition using an image sensor and a 3-axis accelerometer sensor," Journal of Korean Society for Internet Information, 11(1), pp. 129-141, Feb. 2010.
7 Seng-soo Nam, Chang-ho Seo and Dae-seon Choi. "Mobile Finger Signature Verification Robust to Skilled Forgery," Journal of the Korea Institute of Information Security & Cryptology, 26(5), pp. 1161-1170, Oct. 2016.   DOI
8 Ja-Woong Yoon, "Improvement of dynamic respiration monitoring through sensor fusion of accelerometer and gyro-sensor," Journal of Electrical Engineering & Technology, 9(1), pp.334-343, Jan. 2014.   DOI
9 Sang-Ha Nam, Joo-Hee Kim, Se-Kyeong Heo and In-Cheol Kim, "Smartphone Accelerometer-Based Gesture Recognition and its Robotic Application," KIPS Transactions on Software and Data Engineering, 2(6), pp. 395-402, 2013.   DOI
10 Soo-Yeun Shin and Joo-Heon Cha, "Human activity recognition system using multimodal sensor and deep learning based on LSTM," Journal of Mechanical Science and Technology A, 42(2), pp. 111-121, Feb. 2018.
11 Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., and Wojna, Z. "Rethinking the inception architecture for computer vision," Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 2818-2826, Jun. 2016.
12 Young-Cheol Lim, Chi-Ho Park and Sang-Dong Kim, WooYoung Chung, "Development of motion-detective algorithm using accelerometer," Journal of Electrical Engineering&Technology, pp. 594-596, Oct. 2006.   DOI