• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.160-167
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• 2009

This paper describes how to protect the personal information of a biometric reference provider wherein biometric reference and personally identifiable information are bounded in a biometric system. To overcome the shortcomings of the simple personal authentication method using a password, such as identify theft, a biometric system that utilizes physical and behavioral characteristics of each person is usually adopted. In the biometric system, the biometric information itself is personal information, and it can be used as an unique identifier that can identify a particular individual when combining with the other information. As a result, secure protection methods are required for generating, storing, and transmitting biometric information. Considering these issues, this paper proposes a method for ensuring confidentiality and integrity in storing and transferring personally identifiable information that is used in conjunction with biometric information, by extending the related X9.84 standard. This paper also outlines the usefulness of the proposition by defining a standard format represented by ASN.1, and implementing it.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.16 no.3
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• pp.115-127
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• 2006

The purpose of this paper is evaluation of various normalization methods and fusion algorithms in addition to pattern classification algorithms for multi-biometric systems. Experiments are performed using various normalization functions, fusion algorithms and pattern classification algorithms based on Biometric Scores Set-Releasel(BSSR1) provided by NIST. The performance results are presented by Half Total Error Rate (WTER). This study gives base data for the study on performance enhancement of multiple-biometric system by showing performance results using single database and metrics.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.319-326
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• 2014

According to the increasing mobile security users who have experienced authentication failure by forgetting passwords, user names, or a response to a knowledge-based question have preference for biological information such as hand geometry, fingerprints, voice in personal identification and authentication. Therefore biometric verification of personal identification and authentication for mobile security provides assurance to both the customer and the seller in the internet. Our study focuses on human hand biometric information recognition system for personal identification and personal Authentication, including its shape, palm features and the lengths and widths of the fingers taken from mobile phone photographs such as iPhone4 and galaxy s2. Our hand biometric information recognition system consists of six steps processing: image acquisition, preprocessing, removing noises, extracting standard hand feature extraction, individual feature pattern extraction, hand biometric information recognition for personal identification and authentication from input images. The validity of the proposed system from mobile phone image is demonstrated through 93.5% of the sucessful recognition rate for 250 experimental data of hand shape images and palm information images from 50 subjects.

• Journal of Korea Multimedia Society
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• v.17 no.8
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• pp.937-945
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• 2014

Multi-modal biometric system can use another biometric trait in the case of having deficiency at a biometric trait. It also has an advantage of improving the performance of personal identification by using multiple biometric traits, so studies on new biometric traits have continuously been performed. The inner face of finger is a relatively new biometric trait. It has two major features of knuckle lines and wrinkles, which can be used as discriminative features. This paper proposes a finger identification method based on displacement vector to effectively process some variation appeared in contactless hand image. At first, the proposed method produces displacement vectors, which are made by connecting corresponding points acquired by matching each pair of local block. It then recognize finger by measuring the similarity among all the detected displacement vectors. The experimental results using pubic CASIA hand image database show that the proposed method may be effectively applied to personal identification.

• Journal of Information Technology Applications and Management
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• v.27 no.2
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• pp.1-21
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• 2020

The purpose of this study is to investigate the behavioral factors affecting the security attitude and intention to use biometrics password based on the protection motivation theory. This study also investigates security awareness training to understand trust, privacy, and security vulnerability regarding biometric authentication password. This empirical analysis reveals security awareness training boosts the protection motivational factors that affect on the behavior and intention of using biometric authentication passwords. This study also indicates that biometric authentication passwords can be used when the overall belief in a biometric system is present. After all, security awareness training enhances the belief of biometric passwords and increase the motivation to protect security threats. The study will provide insights into protecting security vulnerability with security awareness training.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.2
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• pp.41-46
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• 2016

Fast growth of smartphone technology and advent of Fintech enabled smartphones to deal with more sensitive information. Although many devices applying biometric technology are released as a step for protecting sensitive information securely, there can be potential vulnerabilities if security is not considered at the design stage of a biometric system. By analyzing the potential vulnerabilities, we classify threats in biometric system design process on smartphones and we propose the design requirements for solving these problems. In addition, we propose a framework for secure biometric system design on smartphone by synthesizing the design requirements.

• Journal of Digital Convergence
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• v.16 no.1
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• pp.159-164
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• 2018

Biometric information does not need to be stored separately, and there is no risk of loss and no theft. For this reason, it has been attracting attention as an alternative authentication means for existing authentication means such as passwords and authorized certificates. However, there may be a privacy problem due to leakage of personal information stored in the server. To overcome these weaknesses, FIDO solved the problem of leakage of personal information on the server by using biometric information stored on the user device and authenticating. In this paper, we propose a multiple biometric authentication method that can be used in FIDO environment. In order to utilize multiple biometric information, fingerprints and EEG signals can be generated and used in FIDO system. The proposed method can solve the problem due to limitations of existing 2-factor authentication system by authentication using multiple biometric information.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.251-256
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• 2010

In times past, simple numeric password was the commonly used method in security system. For complement this method, the security system using biometric information is appeared. But it usually uses the scheme to utilize portion of biometric information, and has limited application fields. This biometric security system has low reliability because of some problems such as steal, robbery, and so on. Furthermore, it is associated secondary crime as leaking personal information. For this reason new security system using the unique individual biometric is required. In this paper, we propose the security scheme which used face image and iris analysis. While face image processing for specific person identification, it calculate some feature points of face image and iris's features in our proposed scheme. After person identification applying RFID tags in doorway, several feature information is extracted from camera image, and these compare with registered information of our system for final identification.

• ETRI Journal
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• v.25 no.5
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• pp.401-406
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• 2003

A biometric system determines the identity of a person by measuring physical features that can distinguish that person from others. Since biometric features have many variations and can be easily corrupted by noises and deformations, it is necessary to apply machine learning techniques to treat the data. When applying the conventional machine learning methods in designing a specific biometric system, however, one first runs into the difficulty of collecting sufficient data for each person to be registered to the system. In addition, there can be an almost infinite number of variations of non-registered data. Therefore, it is difficult to analyze and predict the distributional properties of real data that are essential for the system to deal with in practical applications. These difficulties require a new framework of identification and verification that is appropriate and efficient for the specific situations of biometric systems. As a preliminary solution, this paper proposes a simple but theoretically well-defined method based on a statistical test theory. Our computational experiments on real-world data show that the proposed method has potential for coping with the actual difficulties in biometrics.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.310-316
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• 2013

Biometric techniques have been widely used for various areas including criminal identification due to their reliability. However, they have some drawbacks when the biometric information is divulged to illegal users. This paper proposed multimodal biometric system using a real fuzzy vault by RN-ECC for protecting fingerprint and face template. This proposed method has some advantages to regenerate a key value compared with face or fingerprint based verification system having non-regenerative nature and to implement advanced biometric verification system by fusion of both fingerprint and face recognition. From the various experiments, we found that the proposed method shows high recognition rates comparing with the conventional methods.