• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2919-2937
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• 2020

Post-Quantum Cryptography (PQC) is rapidly developing as a stable and reliable quantum-resistant form of cryptography, throughout the industry. Similarly to existing cryptography, however, it does not prevent a third-party from using the secret key when third party obtains the secret key by deception, unauthorized sharing, or unauthorized proxying. The most effective alternative to preventing such illegal use is the utilization of biometrics during the generation of the secret key. In this paper, we propose a biometric-based secret key generation scheme for multivariate quadratic signature schemes, such as Rainbow. This prevents the secret key from being used by an unauthorized third party through biometric recognition. It also generates a shorter secret key by applying Principal Component Analysis (PCA)-based Confidence Interval Analysis (CIA) as a feature extraction method. This scheme's optimized implementation performed well at high speeds.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.8
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• pp.1456-1462
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• 2008

In general, it is known a single biometric-based personal authentication has limitation to improve recognition rate due to weakness of individual recognition scheme. The recognition rate of face recognition system can be reduced by environmental factor such as illumination, while speaker verification system does not perform well with added surrounding noise. In this paper, a multi-modal biometric system composed of face and voice recognition system is proposed in order to improve the performance of the individual authentication system. The proposed empirical weight sum rule based on the reliability of the individual authentication system is applied to improve the performance of multi-modal biometrics. Since the proposed system is implemented using JAVA applet with security function, it can be utilized in the field of user authentication on the generic Web.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.107-113
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• 2016

In this paper, by managing the biometric data is changed with the passage of time, a systematic and scientifically propose a framework to increase the bio-vector generation efficiency of the smart health care. Increasing the development of human life as a medicine and has emerged smart health care according to this. Organic and efficient health management becomes possible to generate a vector when the biological domain to the wireless communication infrastructure based on the measurement of the health status and to take action in accordance with the change of the physical condition. In this paper, we propose a framework to create a bio-vector that contains information about the current state of health of the person. In the proposed framework, Bio vectors may be generated by collecting the biometric data such as blood pressure, pulse, body weight. Biometric data is the raw data from the bio-vector. The scope of the primary data can be set to active. As the collecting biometric data from multiple items of the bio-recognition vectors may increase. The resulting bio-vector is used as a measure to determine the current health of the person. Bio-vector generating the proposed framework, it can aid in the efficiency and systemic health of healthcare for the individual.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.639-642
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• 2007

오늘날 네트워크의 급속한 발전에 더불어 정보화의 가속화는 보안 문제가 크게 부각하고 있다. 이에 마그네틱 카드, IC 카드 등을 이용하여 개인을 식별하는 다양한 보안 시스템들이 개발되고 있으나 분실, 복사, 고의적 양도에 의한 부정사용 등의 문제로 인해 그 해결책이 되지 않고 있으며 이에 대한 해결책으로 생체인식(Biometrics)을 이용한 개인식별 시스템[1]이 제안되어 연구가 진행되고 있다. 본 논문은 기존의 생체인식 시스템 중 가장 활발하게 활용되고 있는 지문인식 시스템이 가지고 있는 환경적인 요소나 물리적 요소에 의한 인식률 저하를 보안할 수 있는 시스템을 새롭게 제안한다. 지문인식은 사용의 편리함과 저가의 초기 투자비용, 그리고 소형화의 가능으로 생체인식 중에서 실생활에 사용되기 가장 적합한 기법으로 여겨져 다양한 응용 범위에 널려 사용되고 있다. 따라서, 제안 시스템은 기존의 지문인식 시스템을 기반으로 하여 손가락에서 추가적인 생체정보를 이용함으로써 지문인식 시스템이 갖은 단점을 보안하면서 인식률 향상과 효율적인 활용이 가능한 시스템을 제안한다.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1147-1155
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• 2005

This paper deals with Iris recognition as one of biometric techniques which is applied to identify a person using his/her behavior or congenital characteristics. The Iris of a human eye has a texture that is unique and time invariant for each individual. First, we obtain the feature vector from the 2D Iris pattern having a property of size invariant and using the fuzzy LDA which is further through four types of 2D Gabor wavelet. At the recognition process, we compute the similarity measure based on the correlation values. Here, since we use four different matching values obtained from four different directional Gabor wavelet and select the maximum value, it is possible to minimize the recognition error rate. To show the usefulness of the proposed algorithm, we applied it to a biometric database consisting of 300 Iris Patterns extracted from 50 subjects and finally got more higher than $90\%$ recognition rate.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.48 no.4
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• pp.201-206
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• 2022

Objectives: Contemporary biometric technologies have been gaining traction in both public and private security sectors. Facial recognition is the most commonly used biometric technology for this purpose. We aimed to evaluate the ability of a publicly available facial recognition application program interface to calculate similarity scores of presurgical and postsurgical photographs of patients who had orthognathic surgery. Materials and Methods: Presurgical and postsurgical photographs of 75 patients who had orthognathic surgery between January 2018 and November 2020 in our department were used. Frontal photographs of patients in relaxed and smiling states were taken. The patients were classified into three groups: Group 2 had one-jaw surgery, Group 3 had two-jaw surgery to correct mandibular prognathism, and Group 4 had two-jaw surgery to correct facial asymmetry. For comparison, photographs of 10 participants were used as controls (Group 1). Two facial recognition application programs (Face X and Azure) were used to assess similarity scores. Results: The similarity scores in the two programs showed significant results. The similarity score of the control group, which did not undergo orthognathic surgery, was the highest. The results for Group 2, Group 3, and Group 4 were higher in the order of Group 2, Group 3, and Group 4. Conclusion: In this study, all orthodontic patients were recognized as the same person using the face recognition program before and after surgery. A significant difference in similarity results was obtained between the groups with both Face X and Azure and in both relaxed and smiling states.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.280-286
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• 2022

Facial recognition system is a biometric manipulation. Its applicability is simpler, and its work range is broader than fingerprints, iris scans, signatures, etc. The system utilizes two technologies, such as face detection and recognition. This study aims to develop a facial recognition system to recognize person's faces. Facial recognition system can map facial characteristics from photos or videos and compare the information with a given facial database to find a match, which helps identify a face. The proposed system can assist in face recognition. The developed system records several images, processes recorded images, checks for any match in the database, and returns the result. The developed technology can recognize multiple faces in live recordings.

• Journal of information and communication convergence engineering
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• v.2 no.3
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• pp.177-181
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• 2004

In this paper, we suggest an Iris recognition system with an excellent recognition rate and confidence as an alternative biometric recognition technique that solves the limit in an existing individual discrimination. For its implementation, we extracted coefficients feature values with the wavelet transformation mainly used in the signal processing, and we used neural network to see a recognition rate. However, Scale Conjugate Gradient of nonlinear optimum method mainly used in neural network is not suitable to solve the optimum problem for its slow velocity of convergence. So we intended to enhance the recognition rate by using Levenberg-Marquardt Back-propagation which supplements existing Scale Conjugate Gradient for an implementation of the iris recognition system. We improved convergence velocity, efficiency, and stability by changing properly the size according to both convergence rate of solution and variation rate of variable vector with the implementation of an applied algorithm.