• Journal of KIISE:Software and Applications
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• v.34 no.4
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• pp.377-388
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• 2007

In this paper, we propose a multi-modal biometric system based on face, iris and fingerprint recognition system. To effectively aggregate two systems, we use statistical distribution models based on matching values for genuine and impostor, respectively. And then, We performed reveal fusion algorithms including weighted summation, Support Vector Machine(SVM), Fisher discriminant analysis, Bayesian classifier. From the various experiments, we found that the performance of multi-modal biometric system was influenced with the normalization methods and classifiers.

• Journal of Satellite, Information and Communications
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• v.11 no.1
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• pp.16-20
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• 2016

In this paper, we analyze the characteristics and ATM applications for fingerprint, iris, vein recognition technology that can be applied to the ATM to reinforce security. Describe the important requirements to be considered when introducing a biometric authentication in the ATM, and were compared to each biometric authentication scheme based on these requirements. Fingerprint authentication has limitations in accuracy, iris recognition is a big weakness in user convenience, whereas vein recognition has the advantage of being hygienic, yet excellent accuracy and secrecy. Vein authentication approach is expected to be expanded to apply to ATM due to the many advantages.

• The Journal of Society for e-Business Studies
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• v.21 no.4
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• pp.41-53
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• 2016

Today, leading smartphone manufacturers offer biometric technologies such as fingerprints, voice recognition, and iris patterns in their flagship models. These biometric technologies are used for authentication. Biometric authentications are widely used in device security and even in financial transaction. This paper examines cases where a user uses biometric authentication during financial transaction (both online and smartphone banking), and explains biometric for non-repudiation by digital signature. Finally, the paper also explains technical and legal requirements for biometric authentication in the area of financial services.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.167-168
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• 2019

Lately, variety of algorithms using encryption technology has been adopted as methods of unlocking smartphone. It is advancing toward the direction to solve through human biometrics technology which has already succeeded in commercialization. These include finger print recognition, face recognition, and iris recognition. In this study, we selected biometrics recognition technology and pattern recognition and password input methods which are already commercialized as evaluation items. The evaluation items are five algorithms including finger print recognition, face recognition iris recognition, pattern recognition and password input method. Based on these algorithms, analytic hierarchy process is used to analyze the preference of smartphone users. Also, the theoretical implications are presented based on the analysis results.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2002.11a
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• pp.440-445
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• 2002

최근 생체인식제품 시장이 활성화됨에 따라 생체인식제품에 대한 객관적인 성능평가가 절실히 요구되고 있는 상황이다. 이미 국외에서는 이러한 추세에 따라 지문, 얼굴, 홍채, 음성 등 각 생체인식제품에 대한 성능평가 기술을 개발하고 있으며, 자국의 생체인식제품에 대한 성능을 개선하는데 도움을 주고 있다. 현재 국내의 경우는 생체인식제품에 대한 객관적인 성능평가 연구기반이 취약한 상태이며, 개발자 자신에 의한 주관적인 평가방법에 따라 자체 시험을 하는데 머물고 있는 실정이다. 이에 따라 본 고에서는 우선적으로 지문인식제품에 대한 국내 적용 가능한 성능평가 항목과 평가방법을 제시하기 위하여 광학식, 반도체식, 열감지식 입력센서별 온도, 습도, 압력, 기만성 측정방법과 인식알고리즘에 대한 성능측정방법을 분석하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1228-1233
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• 2019

Recently, a variety of algorithms using encryption technology have been adopted as methods of unlocking smartphone. It is advancing toward the direction to solve the unlocking problem through human biometrics technology, which has already succeeded in commercializing. These include finger print recognition, face recognition, and iris recognition. In this study, the evaluation items are five algorithms, including finger print recognition, face recognition, iris recognition, pattern recognition, and password input method. Based on the algorithms adopted, the AHP (analytic hierarchy process) technique was used to calculate the preferred priorities for smartphone users. Finger print recognition ( .400) was the top priority for smartphone users. Next, pattern recognition ( .237) was placed in the second priority for smartphone users. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• The KIPS Transactions:PartB
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• v.8B no.2
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• pp.189-194
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• 2001

본 논문에서는 개인 식별을 위하여 복수 해상도 구조를 제시하였고 이 방법으로 구순문 인식을 구현하였다. 구순문 인식은 지문, 음성 패턴, 홍채 패턴과 얼굴 인식과 같은 신체적 특징에 비하여 상대적으로 연구가 많이 이루어지지 않은 신체적 특징이다. 구순문은 CCD 카메라를 이용할 경우 홍채나 얼굴 패턴 같은 다른 특징 요소와 연결하여 인식 시스템을 구축할 수 있는 장점을 가지고 있다. 구순문 인식을 위해 pattern kernels를 이용한 새로운 방법을 제시하였다. Pattern kernels는 여러 개의 local lip print mask들로 구성된 함수이며, lip print의 정보를 디지털 데이터로 전환시켜 준다. 복수 해상도를 가지는 인식 시스템은 단일 해상도의 시스템보다 더욱 신뢰적이며 인식률도 높다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.2
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• pp.305-314
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• 2017

Recently, user authentication through biometric traits such as fingerprint and iris raise more and more attention especially in mobile commerce and fin-tech fields. In particular, commercialized authentication methods using fingerprint recognition are widely utilized mainly because customers are more adopted and used to fingerprint recognition applications. In the meantime, the security issues caused by fingerprint falsification bring lots of attention. In this paper, we propose a new method to improve the performance of fake fingerprint detection using CNN(Convolutional Neural Network). It is common practice to increase the amount of learning data by using affine transformation or horizontal reflection to improve the detection rate in CNN characteristics that are influenced by learning data. However, in this paper we propose an effective data augmentation method based on the database difficulty level. The experimental results confirm the validity of proposed method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.2
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• pp.1-9
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• 2008

As the security requirements of mobile phones have been increasing, there have been extensive researches using one biometric feature (e.g., an iris, a fingerprint, or a face image) for authentication. Due to the limitation of uni-modal biometrics, we propose a method that combines face and iris images in order to improve accuracy in mobile environments. This paper presents four advantages and contributions over previous research. First, in order to capture both face and iris image at fast speed and simultaneously, we use a built-in conventional mega pixel camera in mobile phone, which is revised to capture the NIR (Near-InfraRed) face and iris image. Second, in order to increase the authentication accuracy of face and iris, we propose a score level fusion method based on SVM (Support Vector Machine). Third, to reduce the classification complexities of SVM and intra-variation of face and iris data, we normalize the input face and iris data, respectively. For face, a NIR illuminator and NIR passing filter on camera are used to reduce the illumination variance caused by environmental visible lighting and the consequent saturated region in face by the NIR illuminator is normalized by low processing logarithmic algorithm considering mobile phone. For iris, image transform into polar coordinate and iris code shifting are used for obtaining robust identification accuracy irrespective of image capturing condition. Fourth, to increase the processing speed on mobile phone, we use integer based face and iris authentication algorithms. Experimental results were tested with face and iris images by mega-pixel camera of mobile phone. It showed that the authentication accuracy using SVM was better than those of uni-modal (face or iris), SUM, MAX, NIN and weighted SUM rules.

• Review of KIISC
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• v.28 no.4
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• pp.18-24
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• 2018

전통적으로 바이오인식기술은 출입국심사, 출입통제 행정, 사회복지, 의료, 금융 등 다방면에서 폭넓게 보급되어 실생활에서 널리 활용되고 있다. 최근 들어, 모바일 지급결제서비스 ATM 인출기 인터넷전문은행 등과 같은 핀테크 분야에서 비대면 인증기술로 바이오인식기술이 각광을 받기 시작했다. 그러나 지문 얼굴 홍채 정맥 등 기존의 신체적 특징을 이용한 바이오인식기술은 가짜지문 등 신체적 특징을 이용한 바이오인식기술의 위변조 위협에 대한 우려가 존재하여 심전도 등 생체신호, 걸음걸이와 같이 살아있는 사람의 행동학적 특징을 이용한 차세대 바이오인식기술에 박차를 가하고 있는 추세이다. 이에 본 논문에서는 바이오인식 표준화를 위한 ITU-T SG17 Q9 국제표준화기구를 소개하고, X.tab 국제표준화 현황에 대하여 집중적으로 살펴보고자 한다.