• Journal of Information Processing Systems
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• v.14 no.2
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• pp.435-447
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• 2018

Fingerprint-based biometric identification is one of the most interesting automatic systems for identifying individuals. Owing to the poor sensing environment and poor quality of skin, biometrics remains a challenging problem. The main contribution of this paper is to propose a new approach to recognizing a person's fingerprint using the fingerprint's local characteristics. The proposed approach introduces the barycenter notion applied to triangles formed by the Delaunay triangulation once the extraction of minutiae is achieved. This ensures the exact location of similar triangles generated by the Delaunay triangulation in the recognition process. The results of an experiment conducted on a challenging public database (i.e., FVC2004) show significant improvement with regard to fingerprint identification compared to simple Delaunay triangulation, and the obtained results are very encouraging.

• 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.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.2
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• pp.149-154
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• 2015

Biometric techniques for authentication using body parts such as a fingerprint, face, iris, voice, finger-vein and also photoplethysmography have become increasingly important in the personal security field, including door access control, finance security, electronic passport, and mobile device. Finger-vein images are now used to human identification, however, difficulties in recognizing finger-vein images are caused by capturing under various conditions, such as different temperatures and illumination, and noise in the acquisition camera. The human photoplethysmography is also important signal for human identification. In this paper To increase the recognition rate, we develop camera based identification method by combining finger vein image and photoplethysmography signal. We use a compact CMOS camera with a penetrating infrared LED light source to acquire images of finger vein and photoplethysmography signal. In addition, we suggest a simple pattern matching method to reduce the calculation time for embedded environments. The experimental results show that our simple system has good results in terms of speed and accuracy for personal identification compared to the result of only finger vein images.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.3
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• pp.129-141
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• 2006

The purpose of this paper is to design Conformance Test Suite for BSP(Biometric Service Provider) based on BioAPI(Biometric Application Programming Interface) v2.0. The proposed BioAPI Conformance Test Suite enables users to test BSP with framework independently. A test scheduling tool has been embodied to use Test Assertion in the form of XML. In order to demonstrate the performance of the Conformance Test Suite, the experiment was performed by using both verification and identification BSPs. As the results of this experiment, we were able to determinate whether BSPs based on BioAPI v2.0 satisfied standard requirements or not.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.659-664
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• 2010

This paper provides an integrated framework for biometric data and private information protection in TeleHealth. Biometric technology is indispensable in providing identification and convenience in the TeleHealth environment. Once biometric information is exposed to mallicious attacker, he will suffer great loss from the illegferuse of his biometric data by someone else because of difficulty of change not like ID and password. We have to buil by someone esystem data bon the integrated framework for biometric data and private information protection in TeleHealth. First, we consider the structure of the biometric system and the security requirements of y someone esystem data bon the biometrics. And then, we define the TeleHealth system model and provide the vulnerabilities and countermeasures of the biometric-data by someone eintegrated model.byhe TeleHealth sse bec requires two-phata authentication for countermeasure. Finally, we made some functionferrequirements for main componenets of biometric-data bintegrated TeleHealth system framework to protect biometric data.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.437-444
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• 2008

This paper deals with the biometric template protection in the biometric system which has been widely used for personal authentication. First, we consider the structure of the biometric system and the function of its sub-systems and define the biometric template and identification(ID) information. And then, we describe the biometric template attack points of a biometric system and attack examples and provide their countermeasures. From this, we classify the vulnerability which can be protected by encryption and hashing techniques. For more detail investigation of these at real operating situations, we analyze them and suggest several protection methods for the typical application scheme of biometric systems such as local model, download model, attached model, and center model. Finally, we also handle the privacy problem which is most controversy issue related to the biometric systems and suggest some guidances of safeguarding procedures on establishing privacy sympathy biometric systems.

• Animal Bioscience
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• v.36 no.6
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• pp.980-989
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• 2023

Objective: Iris pattern recognition system is well developed and practiced in human, however, there is a scarcity of information on application of iris recognition system in animals at the field conditions where the major challenge is to capture a high-quality iris image from a constantly moving non-cooperative animal even when restrained properly. The aim of the study was to validate and identify Black Bengal goat biometrically to improve animal management in its traceability system. Methods: Forty-nine healthy, disease free, 3 months±6 days old female Black Bengal goats were randomly selected at the farmer's field. Eye images were captured from the left eye of an individual goat at 3, 6, 9, and 12 months of age using a specialized camera made for human iris scanning. iGoat software was used for matching the same individual goats at 3, 6, 9, and 12 months of ages. Resnet152V2 deep learning algorithm was further applied on same image sets to predict matching percentages using only captured eye images without extracting their iris features. Results: The matching threshold computed within and between goats was 55%. The accuracies of template matching of goats at 3, 6, 9, and 12 months of ages were recorded as 81.63%, 90.24%, 44.44%, and 16.66%, respectively. As the accuracies of matching the goats at 9 and 12 months of ages were low and below the minimum threshold matching percentage, this process of iris pattern matching was not acceptable. The validation accuracies of resnet152V2 deep learning model were found 82.49%, 92.68%, 77.17%, and 87.76% for identification of goat at 3, 6, 9, and 12 months of ages, respectively after training the model. Conclusion: This study strongly supported that deep learning method using eye images could be used as a signature for biometric identification of an individual goat.

• Journal of the Microelectronics and Packaging Society
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• v.23 no.2
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• pp.29-35
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• 2016

With the pace of rapid innovation in technology of IoT (Internet of Things) and smart devices, biometric technology becomes one of the most progressive industries. Recent trends in biometrics show most are focused on embedding biometric sensors in mobile devices for user authentication. Multifactor biometrics such as fingerprint, retina, voice, etc. are considering as identification system to provide users with services more secured and convenient. Here we, therefore, demonstrate some major technologies and market trends of mobile biometric technology with its concerns and issues.

• The KIPS Transactions:PartC
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• v.10C no.6
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• pp.747-754
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• 2003

Thia paper suggests a milti user-authentication system comprises that DNA biometric informatiom, owner's RFID(Radio Frequency Identification) smartcard of hardware token, and PKI digital signqture of software. This system improved items proposed in [1] as follows : this mechanism provides one RFID smartcard instead of two user-authentication smartcard(the biometric registered seal card and the DNA personal ID card), and solbers user information exposure as RFID of low proce when the card is lost. In addition, this can be perfect multi user-autentication system to enable identification even in cases such as identical twins, the DNA collected from the blood of patient who has undergone a medical procedure involving blood replacement and the DNA of the blood donor, mutation in the DNA base of cancer cells and other cells. Therefore, the proposed system is applied to terminal log-on with RFID smart card that stores accurate digital DNA biometric information instead of present biometric user-authentication system with the card is lost, which doesn't expose any personal DNA information. The security of PKI digital signature private key can be improved because secure pseudo random number generator can generate infinite one-time pseudo randon number corresponding to a user ID to keep private key of PKI digital signature securely whenever authenticated users access a system. Un addition, this user-authentication system can be used in credit card, resident card, passport, etc. acceletating the use of biometric RFID smart' card. The security of proposed system is shown by statistical anaysis.

• Information Systems Review
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• v.23 no.4
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• pp.1-22
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• 2021

In the newly encountered economy caused by the Corona virus Disease-19, remote transaction becomes a new normal that disrupt traditional economic order. In the middle of the disruption, mobile tech is placed and remote finance on mobile is highly noticed and considered as an infra-tech to support the new ecology, In mobile finance. remote payment is becoming the most common service and personal identification on it is critical to operate the new service. There are various means of remotely identifying a person. Recently the use of biometric information is increasing. In this study, a correlation analysis was conducted on factors that effects to biometrics usage and the intention to use in remote personal identification. Variables for critical factor in the remote identification were classified into 4 groups such as Performance expectancy, Effort expectancy, Social influence, and Security. The empirical analysis based on the Unified Theory of Acceptance and Use of Technology (UTAUT) was conducted. The relationship between variables and the intention to use is also analyzed. In the study, stepwise regression analysis was conducted four times in which variables were adjusted in individual stage. As a result, the analysis suggests that performance expectancy, effort expectancy, social influence, security have positive effects for intention to use. Additionally, effort expectancy and security have moderating effects to intention to use depends on biometric authentication experience. The analysis has shown positive effect of variables grouped on the intention to use them. It also suggests that the intention to use biometric authentication will quickly grow. This study is expected to make a contribution to utilize and improve the use of biometric information in mobile payment.