• 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.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.65-72
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• 2022

In this paper, a zero trust-based complex biometric authentication was proposed in a passwordless environment. The linkage of FIDO 2.0 (Fast IDENTITY Online) transaction authentication platforms was designed in conjunction with metaverse. In particular, it was applied with the location information of a smart terminal according to a geomagnetic sensor, an accelerator sensor, and biometric information for multi-factor authentication(MFA). At this time, a FIDO transaction authentication platform was presented for adaptive complex authentication with user's environment through complex authentication with secondary authentication based on situational awareness such as illuminance and temperature/humidity. As a result, it is possible to authenticate secondary users based on zero trust with behavior patterns such as fingerprint recognition, iris recognition, face recognition, and voice according to the environment. In addition, it is intended to check the linkage result of the FIDO platform for complex integrated authentication and improve the authentication accuracy of the linkage platform for transaction authentication using FIDO2.0.

• Korean Journal of Construction Engineering and Management
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• v.16 no.4
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• pp.60-69
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• 2015

Labor attendance management has traditionally been carried out by writing a table for checking an attendance of labor, which requires a lot of time and effort. As electronic devices with additions such as barcodes, Quick Response codes, and Radio Frequency Identification(RFID) have been developed, however, automated labor attendance management systems have appeared. Recently, various types of labor recognition devices converged with biometrics (fingerprint, vein, face recognition, etc.) have been released. However, although these devices can be used to check attendance automatically, there is insufficient guidance when it comes to selecting the appropriate labor attendance management system for construction sites. Therefore, this study proposed a decision framework to determine which labor attendance management system would be suitable for a construction site and to select the labor recognition device. This study investigated different labor recognition devices, focusing on how they worked, and tested the performance of devices and their usability for construction labor attendance management. The test results showed that RFID is most suitable when verifying the attendance of many laborers over a short period of time. The devices for hand vein and fingerprint recognition did not function when there was a foreign material such as cement or paint on the laborer's hand, except for a deformed finger. Reflecting these test results, this study suggested a framework for selecting a labor attendance system and recognition device; this is expected to contribute to the development of more efficient labor management systems.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.2
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• pp.69-80
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• 1999

Recently, social requirements of personal identification techniques are rapidly expanding in a number of new application ares. Especially fingerprint recognition is the most important technology. Fingerprint recognition technologies are well established, proven, cost and legally accepted. Therefore, it has more spot lighted among the any other biometrics technologies. In this paper we propose a new on-line fingerprint recognition algorithm for non-inked type live scanner to fit their increasing of security level under the computing environment. Fingerprint recognition system consists of two distinct structural blocks: feature extraction and feature matching. The main topic in this paper focuses on the feature matching using the fingerprint minutiae (ridge ending and bifurcation). Minutiae matching is composed in the alignment stage and matching stage. Success of optimizing the alignment stage is the key of real-time (on-line) fingerprint recognition. Proposed alignment algorithm using clique shows the strength in the search space optimization and partially incomplete image. We make our own database to get the generality. Using the traditional statistical discriminant analysis, 0.05% false acceptance rate (FAR) at 8.83% false rejection rate (FRR) in 1.55 second average matching speed on a Pentium system have been achieved. This makes it possible to construct high performance fingerprint recognition system.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.275-284
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• 2008

With increases in recent security requirements, biometric technology such as fingerprints, faces and iris recognitions have been widely used in many applications including door access control, personal authentication for computers, internet banking, automatic teller machines and border-crossing controls. Finger vein recognition uses the unique patterns of finger veins in order to identify individuals at a high level of accuracy. This paper proposes new device and methods for touchless finger vein recognition. This research presents the following five advantages compared to previous works. First, by using a minimal guiding structure for the finger tip, side and the back of finger, we were able to obtain touchless finger vein images without causing much inconvenience to user. Second, by using a hot mirror, which was slanted at the angle of 45 degrees in front of the camera, we were able to reduce the depth of the capturing device. Consequently, it would be possible to use the device in many applications having size limitations such as mobile phones. Third, we used the holistic texture information of the finger veins based on a LBP (Local Binary Pattern) without needing to extract accurate finger vein regions. By using this method, we were able to reduce the effect of non-uniform illumination including shaded and highly saturated areas. Fourth, we enhanced recognition performance by excluding non-finger vein regions. Fifth, when matching the extracted finger vein code with the enrolled one, by using the bit-shift in both the horizontal and vertical directions, we could reduce the authentic variations caused by the translation and rotation of finger. Experimental results showed that the EER (Equal Error Rate) was 0.07423% and the total processing time was 91.4ms.

• Journal of Korea Technology Innovation Society
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• v.15 no.3
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• pp.604-626
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• 2012

As a society of knowledge and information has been developed rapidly, because of changing from web environment to ubiquitous environment, a lot of countries across the world as well as S. Korea for e-Government have come to use the internet electronic voting for a variety of elections. So this research focused on the strategy consulting of the internet electronic voting of S. Korea with spatial information system analysed by the application of 'scenario planning' as a foresight method. And as a consequence, the strategy formulation of the electronic voting for the future S. Korea is to use the biometrics technology system as vein recognition and face recognition, using a part of the human body like a password, with spatial information system.

• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.132-144
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• 2017

The fingerprint classification of categorizing fingerprints by classes should be used in order to improve the processing speed and accuracy in a fingerprint recognition system using a large database. The fingerprint classification methods extract features from the fingerprint ridges of a fingerprint and classify the fingerprint using learning and reasoning techniques based on the classes defined according to the flow and shape of the fingerprint ridges. In earlier days, many researches have been conducted using NIST database acquired by pressing or rolling finger against a paper. However, as automated systems using live-scan scanners for fingerprint recognition have become popular, researches using fingerprint images obtained by live-scan scanners, such as fingerprint data provided by FVC, are increasing. And these days the methods of fingerprint classification using Deep Learning have proposed. In this paper, we investigate the trends of fingerprint classification technology and compare the classification performance of the technology. We desire to assist fingerprint classification research with increasing large fingerprint database in improving the performance by mentioning the necessity of fingerprint classification research with consideration for fingerprint images based on live-scan scanners and analyzing fingerprint classification using deep learning.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.4
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• pp.115-124
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• 2011

There has been significant research in security technology such as e-passport standards, as e-passports have been introduced internationally. E-passports combine the latest security technologies such as smart card, public key infrastructure, and biometric recognition, so that these technologies can prevent unauthorized copies and counterfeits. Biometric information stored in e-passports is the most sensitive personal information, and it is expected to bring the highest risk of damages in case of its forgery or duplication. The present e-passport standards cannot handle security features that verify whether its biometric information is copied or not. In this paper, we propose an e-passport security technology in which biometric watermarking is used to prevent the copy of biometric information in the e-passport. The proposed method, biometric watermarking, embeds the invisible date of acquisition into the original data during the e-passport issuing process so that the human visual system cannot perceive its invisibly watermarked information. Then the biometric sample, having its unauthorized copy, is retrieved at the moment of reading the e-passport from the issuing database. The previous e-passport security technology placed an emphasis on both access control readers and anti-cloning chip features, and it is expected that the proposed feature, copy protection of biometric information, will be demanded as the cases of biometric recognition to verify personal identity information has increased.

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.173-179
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• 2010

Over recent years, much research attention has been devoted to a two-factor authentication mechanism which integrates both tokenized pseudorandom numbers with user specific biometric features for biometric verification, known as Biohash. The main advantage of Biohash over sole biometrics is that Biohash is able to achieve a zero equal error rate and provide a clean separation of the genuine and imposter populations, thereby allowing elimination of false accept rates without imperiling the false reject rates. Nonetheless, when the token of a user is compromised, the recognition performance of a biometric system drops drastically. As such, a few solutions have been proposed to improve the degraded performance but such improvements appear to be insignificant. In this paper, we investigate and pinpoint the basis of such deterioration. Subsequently, we propose a two-level approach by utilizing strong inner products and fuzzy logic weighting strategies accordingly to increase the original performance of Biohash under this scenario.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.521-526
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• 2015

Research on how to use the biological characteristics of human to confirm the identity of the individual is being actively conducted. Electrocardiogram(: ECG) based biometric system is difficult to counterfeit and does not cause skin irritation on the subject. It can be easily combined with conventional biometrics such as fingerprint and face recognition to give multimodal biometric systems. In this thesis, biometric identification method analysing ECG waveform characteristics from Discrete Wavelet Transform(DWT) coefficients is suggested. Feature selection is performed on the 9 coefficients of DWT using the correlation analysis. The verification is achieved by using the error back propagation neural networks. Using the proposed approach on 24 subjects of MIT-BIH QT Database, 98.88% verification rate has been obtained.