• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.892-911
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• 2019

Biometric recognition systems have been widely used for information security. Among the most popular biometric traits, there are fingerprint and face due to their high recognition accuracies. However, the security system that uses face recognition as the login method are vulnerable to face-spoofing attacks, from using printed photo or video of the valid user. In this study, we propose a fast and robust method to detect face-spoofing attacks based on the analysis of spatial frequency differences between the real and fake videos. We found that the effect of a spoofing attack stands out more prominently in certain regions of the 2D Fourier spectra and, therefore, it is adequate to use the information about those regions to classify the input video or image as real or fake. We adopt a divide-conquer-aggregate approach, where we first divide the frequency domain image into local blocks, classify each local block independently, and then aggregate all the classification results by the weighted-sum approach. The effectiveness of the methodology is demonstrated using two different publicly available databases, namely: 1) Replay Attack Database and 2) CASIA-Face Anti-Spoofing Database. Experimental results show that the proposed method provides state-of-the-art performance by processing fewer frames of each video.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.32-39
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• 2017

Recently, usage of mobile cloud services has been increasing. In particular, beyond the constraints of a single cloud computing service, studies on the multi-cloud have been actively pursued. A user must authenticate multiple cloud service providers to use additional cloud services in a multi-cloud. In previous studies, an authentication method using single sign-on (SSO) was not available in all cloud services. Cloud services will not be available when the SSO server is not available due to malicious attacks, because all authentication is done via the SSO server. Additionally, using a broker, there is a vulnerability that can expose authentication information for the service provider to a user who did not sign up. In this paper, we propose a secure user authentication protocol using biometric authentication that does not expose user information when using additional cloud services. The proposed protocol can use a single biometric authentication for multi-cloud services without storing authentication information in each cloud service. In terms of key stability (to ensure stability through the key agreement process and the key area), by disabling various attack methods, such as man-in-the-middle attacks and replay attacks, we provide secure mobile cloud services.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.6
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• pp.18-26
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• 2009

In this paper, we proposed multipurpose signal detection methods for ECG (electrocardiogram) based u-healthcare systems. For ECG based u-healthcare system, QRS signal extraction for cardiovascular disease diagnosis is essential. Also, for security and convenience reasons, it is desirable if u-healthcare system support biometric identification directly from user's bio-signal such as ECG for this case. For this, from Lead II signal, we developed QRS signal detection method and also, we developed signal extraction method for biometric identification using Lead II signal which is relatively robust from signal alteration by aging and diseases. For QRS signal detection capability from Lead II signal, ECG signals from MIT-BIH database are used and it showed 99.36% of accuracy and 99.68% of sensitivity. Also, to show the performance of signal extraction capability for biometric diagnosis purpose, Lead III signals are measured after drinking, smoking, or exercise to consider various monitoring conditions and it showed 99.92% of accuracy and 99.97% of sensitivity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.3
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• pp.549-555
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• 2007

A digital signature scheme provides integrity of the document, authentication and non-repudiation of a signer. Usually the key for digital signature is stored in hard disk or removal disk storage. The drawback of this approach is that the signer can let the agent to sign instead of the signer by providing the key information. It can be abused in applications such as electronic election. In this paper, we propose the undeniable biometric digital multi-signature scheme suitable for applications where the signer should not make an agent sign instead of himself/herself. The undeniable multi-signature scheme requires many signers and only the designated user can confirm the authenticity of multi-signature. The proposed scheme satisfies undeniable property and it is secure against active attacks such as modification and denial of the multi-signature by signers. As the key is generated through the signer's fingerprint image, it's also secure against signing by an agent.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.381-391
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• 2017

Biometric technology is a technology for authenticating a user using the physical or behavioral features of the inherent characteristics of the individual. With the necessity and efficiency of the technology in the fields of finance, security, access control, medical welfare, inspection, and entertainment, the service range has been expanding. Biometrics using biometric information such as fingerprints and faces have been exposed to counterfeit and disguised threats and become a social problem. Recent studies using a bio-signal from the inside of the body other than the bio-information of the external body are being developed. This paper analyzes the recent research and technology of biometric systems using bio-signals, ECG, heart sounds, EEG, and EMG to present the skills needed for the development direction. In the future, utilizing the deep learning to build and analyze database to manage bio-signal based big data for the complex condition of individuals, biometrics technologies suitable for real time environment are expected to be researched.

• Journal of IKEEE
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• v.25 no.3
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• pp.445-450
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• 2021

Bio-impedance measurement is a measurement device that can be used to obtain biometric information and diagnose skin diseases using convenience, low cost, and low cost devices. In this study, the bio-impedance was measured using a direct dry gold electrode and a simulation study through animal bio modeling to obtain biometric information in a biometric form. Impedance was measured by inserting electrodes into subcutaneous areas of animal tissue and applying frequencies of 100 uA, 1-100 kHz using a two-electrode method. As a result of the measurement, the resistance of the electrodes is measured high at 5 mm electrodes compared to 7.5 mm and 10 mm electrodes based on 5 mm electrodes. Based on the 5 mm electrode, an average difference of 1.49% was found for the 7.5 mm electrode in the total frequency range, and the impedance difference was confirmed to be 2.624% for the 10 mm electrode. In the future, the research results are expected to be valuable in designing and manufacturing electrodes for bio-inserted electrocardiogram sensors.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.1
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• pp.11-21
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• 2008

Biometrics-based user authentication has several advantages over traditional password-based systems for standalone authentication applications. This is also true for new authentication architectures known as crypto-biometric systems, where cryptography and biometrics are merged to achieve high security and user convenience at the same time. Recently, a cryptographic construct, called fuzzy vault, has been proposed for crypto-biometric systems. This construct aims to secure critical data(e.g., secret key) with the fingerprint data in a way that only the authorized user can access the secret by providing the valid fingerprint, and some implementations results for fingerprint have been reported. However, the previous results had some limitation of the provided security due to the limited numbers of chaff data fer hiding real fingerprint data. In this paper, we propose an approach to provide both the automatic alignment of fingerprint data and higher security by using a 3D geometric hash table. Based on the experimental results, we confirm that the proposed approach of using the 3D geometric hash table with the idea of the fuzzy vault can perform the fingerprint verification securely even with more chaff data included.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.1
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• pp.125-133
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• 2009

Security of biometric data is particularly important as the compromise of the data will be permanent. To protect the biometric data, we need to store it in a non.invertible transformed version. Thus, even if the transformed version is compromised, its valid biometric data are securely remained. Fuzzy vault mechanism was proposed to provide cryptographic secure protection of critical data(e.g., encryption key) with the fingerprint data in a way that only the authorized user can access the critical data by providing the valid fingerprint. However, all the previous results cannot operate on the fingerprint image with a few minutiae, because they use fixed degree of the polynomial without considering the number of fingerprint minutiae. To solve this problem, we use adaptive degree of polynomial considering the number of minutiae. Also, we apply multiple polynomials to operate the fingerprint with a few minutiae. Based on the experimental results, we confirm that the proposed approach can enhance the security level and verification accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.503-523
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• 2022

Nowadays, many attendance applications utilise biometric techniques such as the face, fingerprint, and iris recognition. Biometrics has become ubiquitous in many sectors. Due to the advancement of deep learning algorithms, the accuracy rate of biometric techniques has been improved tremendously. This paper proposes a web-based attendance system that adopts facial recognition using open-source deep learning pre-trained models. Face recognition procedural steps using web technology and database were explained. The methodology used the required pre-trained weight files embedded in the procedure of face recognition. The face recognition method includes two important processes: registration of face datasets and face matching. The extracted feature vectors were implemented and stored in an online database to create a more dynamic face recognition process. Finally, user testing was conducted, whereby users were asked to perform a series of biometric verification. The testing consists of facial scans from the front, right (30 - 45 degrees) and left (30 - 45 degrees). Reported face recognition results showed an accuracy of 92% with a precision of 100% and recall of 90%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1365-1369
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• 2013

Recently, the Personal Health Device(PHD) that measures various biometric data easily are highlighted for ensuring portability, scalability and interoperability among the device as well as needs for a standardization of managing information measured by. In this paper, we'd like to propose u-healthcare monitoring system that measure biometric data(Oxygen saturation, Body weight, ECG and Blood pressure) by PHD featured with transferring data into devices such as smartphone using Bluetooth Health Device Profile(HDP) based on the ISO/IEEE 11073.