• Journal of Venture Innovation
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• v.2 no.2
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• pp.21-29
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• 2019

In the public certificate technology commonly used in Korea, users have a cumbersome problem of always resetting when they forget their password. In this paper, as a solution to this problem, we propose a secure authentication certificate password recovery protocol using blockchain, PKI, and DID for distributed storage. DID is a schema for protecting block ID in blockchain system. The private key used in the PKI is configured as a user's biometric, for example, a fingerprint, so that it can completely replace the memory of the complex private key. To this end, based on the FIDO authentication technology that most users currently use on their smartphones, the process of authenticating a user to access data inside the block minimizes the risk of an attacker taking over the data.

• Smart Media Journal
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• v.5 no.2
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• pp.77-83
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• 2016

Today, the great revolution in all financial industrial such as bank have been progressing through the utilization of IT technology actively, it is called the fintech. In this paper, we draw the draft design of NFC-based electronic payment and coupon system using FIDO framework to apply the 2 factor authentication technique for strength security. In detailed, we will study that the terminal device in front-end will be applied the 2 factor authentication and electric signature, and cloud-based payment gateway in back-end will be applied malicious code detection technique of distributed avoidance type.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.25-37
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• 2019

Inspired by the rapid development of deep learning and online biometrics-based authentication, we propose a handwritten one-time password authentication system which employs deep learning-based handwriting recognition and writer verification techniques. We design a convolutional neural network to recognize handwritten digits and a Siamese network to compute the similarity between the input handwriting and the genuine user's handwriting. We propose the first application of the second edition of NIST Special Database 19 for a writer verification task. Our system achieves 98.58% accuracy in the handwriting recognition task, and about 93% accuracy in the writer verification task based on four input images. We believe the proposed handwriting-based biometric technique has potential for use in a variety of online authentication services under the FIDO framework.

• Nuclear Engineering and Technology
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• v.52 no.2
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• pp.448-455
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• 2020

The H.B. Robinson Unit 2 (HBR-2) pressure vessel dosimetry benchmark is an in- and ex-Reactor Pressure Vessel (RPV) neutron dosimetry benchmark based on experimental data from the HBR-2 reactor, a 2300-MW PWR designed by Westinghouse and put in operation in March 1971, openly available through the SINBAD Database at OECD/NEA data Bank. The goals of the present work were to carry out three-dimensional (3D) fixed source transport calculations in both Cartesian (X,Y,Z) and cylindrical (R,θ,Z) geometries by using the TORT-3.2 discrete ordinates code on very detailed 3D HBR-2 geometrical models and to test the latest broad-group coupled (47 neutron groups + 20 photon groups) working cross section libraries in FIDO-ANISN format with same structure as BUGLE-96, such as BUGJEFF311.BOLIB, BUGENDF70.BOLIB and BUGLE-B7. The results obtained with all the cited libraries were satisfactory and are here reported and compared.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.6152-6168
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• 2017

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.