• Journal of information and communication convergence engineering
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• v.7 no.1
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• pp.24-29
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• 2009

Sahai and Waters first introduced the concept of Fuzzy Identity Based Encryption (FIBE) to provide an error-tolerance property for Identity Based Encryption (IBE) in 2005. Yang et al. extended this idea and introduced the concept of Fuzzy Identity Based Signature (FIBS) in 2008, and constructed a FIBS scheme based on Sahai and Waters's FIBE scheme. In this paper, we further formalize the notion and security model of FIBS scheme and propose a new construction of FIBS scheme based on bilinear pairing. The proposed FIBS scheme not only provide shorter public parameters, private key and signature, but also have useful structures which result in more efficient key extraction, signing and verification than that of Yang et al.'s FIBS scheme.

• Journal of the Korea Society of Computer and Information
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• v.21 no.3
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• pp.123-128
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• 2016

This study aims to analyze the causal relation between identity and school adaptation of multicultural family children, starting from necessity of empirical research considering insufficient preceding research. To achieve the purpose of the research, this study implemented empirical analysis regarding the causal relation between factors of self-identity and school adaptation. As a result, factors of self-identity implies significant effect on school regulations, while factors of school adaptation partially have an effect on school class and relations with a teacher and friend. Based on the result of verification, this study emphasizes teachers' effort as well as comprehensive and practical development of an educational program to help children from multicultural family establish the right self-identity for settling into school life. Moreover, the limitation of this study and future research direction is presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3C
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• pp.257-267
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• 2009

This paper presents a training method for neural networks and the employment of MSE (mean scare error) values as the basis of a decision regarding the identity claim of a speaker in a recurrent neural networks based speaker verification system. Recurrent neural networks (RNNs) are employed to capture temporally dynamic characteristics of speech signal. In the process of supervised learning for RNNs, target outputs are automatically generated and the generated target outputs are made to represent the temporal variation of input speech sounds. To increase the capability of discriminating between the true speaker and an impostor, a discriminative training method for RNNs is presented. This paper shows the use and the effectiveness of the MSE value, which is obtained from the Euclidean distance between the target outputs and the outputs of networks for test speech sounds of a speaker, as the basis of speaker verification. In terms of equal error rates, results of experiments, which have been performed using the Korean speech database, show that the proposed speaker verification system exhibits better performance than a conventional hidden Markov model based speaker verification system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.5
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• pp.858-865
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• 2006

A certificate that is issued by the certification authority can be revoked within the period of validity by various reasons such as the loss of private key, disqualification or the change in key. Therefore, the certificate status verification must precede prior to use Currently, the CRL or the OCSP methods are used in most cases. But the CRL system can't guarantee the present status of the certificate, and the OCSP generates heavy network traffic by checking or requesting certificate status in real-time using high-capacity messages. In this paper, we propose a system that requests the certificate verification by creating VDN for user identity information. Through this system, the certification authority will be able to guarantee the certificate's status in real-time, and solve the problem of the sewer and network overload by verifying and finding user identity information from VDN, Based on the results, we propose a real-time certificate status verification system which can improve the speed of the verification. We confirmed the improvement in speed by testing and comparing it with the existing methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.1
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• pp.49-66
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• 2022

The COVID-19 pandemic has led many countries around the world to introduce and employ a digital certificate system to prevent infectious diseases, however, there are difficulties in using the compatible digital certificate between countries in that the international standards of the system have not been developed. Accordingly, we propose an improved system, comparing two methods of presenting a certificate, existing QR code-based and a short-range wireless communication-based certificates. The proposed system is a digital certificate system against the spread of infectious disease by storing verification information of the certificate using decentralized identity-based technology on the blockchain. Blockchain-based trust anchor improves security by solving the problem of forgery and alteration of certificates and guaranteeing the identity of certificate issuers and presenters. This system is also expected to enhance usability providing concurrent verification of a number of certificates(vaccination certificates, recovery certificates, test results, identity certificates, etc.) in a single certificate presentation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.639-644
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• 2002

Password typing is the most wifely ued identity verification method in computer security domain. However, due to its simplicity, it is vulnerable to imposter attacks Keystroke dynamics adds a shield to password. Discriminating imposters from owners is a novelty detection problem. Auto-Associative Multilayer Perceptron (AaMLP) has teen proved to be a good novelty detector. However, the wifely used 2-layer AaMLP cannot identify nonlinear boundaries, which can result in serious problems in computer security. In this paper, a nonlinear model, i.e. 4-layer AaMLP, is proposed to serve as the novelty detector, which can remedy the limitations of 2-layer AaMLP.

• Phonetics and Speech Sciences
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• v.9 no.2
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• pp.85-94
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• 2017

Conventional speaker verification systems using time delay neural network, identity vector and probabilistic linear discriminant analysis (TDNN-Ivector-PLDA) are known to be very effective for verifying long-duration speech utterances. However, when test utterances are of short duration, duration mismatch between enrollment and test utterances significantly degrades the performance of TDNN-Ivector-PLDA systems. To compensate for the I-vector mismatch between long and short utterances, this paper proposes to use probabilistic linear discriminant analysis (PLDA) model adaptation with augmented data. A PLDA model is trained on vast amount of speech data, most of which have long duration. Then, the PLDA model is adapted with the I-vectors obtained from short-utterance data which are augmented by using vocal tract length perturbation (VTLP). In computer experiments using the NIST SRE 2008 database, the proposed method is shown to achieve significantly better performance than the conventional TDNN-Ivector-PLDA systems when there exists duration mismatch between enrollment and test utterances.

• The KIPS Transactions:PartC
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• v.19C no.4
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• pp.225-230
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• 2012

Since one of weak points of public crypto-systems is to require the verification of public key, identity based crypto-systems were proposed as an alternative. However, such techniques need a private key generator which can be a single point of failure. To improve such weakness, threshold identity-based crypto-systems were proposed. In this paper, we propose a new threshold identity-based encryption scheme which is constructed to extend an identity-based encryption scheme by Cocks. Since the proposed scheme is based on quadratic residues, it has smaller complexity of encryption. And we prove that the proposed scheme is secure against a chosen identity attack.

• 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.

• Journal of Broadcast Engineering
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• v.23 no.3
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• pp.395-402
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• 2018

Human palms contain discriminative features for proving the identity of each person. In this paper, we present a novel method for user verification based on palmprints and palm veins. Specifically, the region of interest (ROI) is first determined to be forced to include the maximum amount of information with respect to underlying structures of a given palm image. The extracted ROI is subsequently enhanced by directional patterns and statistical characteristics of intensities. For multispectral palm images, each of convolutional neural networks (CNNs) is independently trained. In a spirit of ensemble, we finally combine network outputs to compute the probability of a given ROI image for determining the identity. Based on various experiments, we confirm that the proposed ensemble method is effective for user verification with palmprints and palm veins.