• Journal of Digital Convergence
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• v.12 no.4
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• pp.335-342
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• 2014

According to the recent trends in the growing elderly population, the chronically ill have increased. Thus the importance of the health care issues for them has emerged. In this paper, we want to implement a chronic disease management system using smart mobile devices. Proposed chronic disease management system is consisted of the biometric sensor, smart mobile devices, the patient management server, patient management DB, and patient symptoms analysis agent. The biometric sensor detects a biological information. Smart mobile devices receive the patient information from the sensor and transmit the information to the patient management server. The patient management server, patient management DB, and patient symptoms agent analysis agent analyze to process data delivered through a wireless communication network. Bio-signals includes modules of ECG, blood pressure, blood sugar and PPG. We are able to determine the current health status by monitoring measured biometric data through chronically ill health management system. We will focus on the individual service to be appropriate for a patient group in a mobile environment.

• Journal of Digital Convergence
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• v.10 no.2
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• pp.141-146
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• 2012

U-healthcare, which grafted advanced IT technology onto medical technology, is in the limelight because it can provide medical services at anytime and anywhere. U-healthcare system applied RFID technology for Implantable Medical Device (IMD), but patient's biometric information can be easily exposed to third parties. In this article, RFID-based U-healthcare authentication protocol is proposed to prevent illegal usage for personal biometric information exposed to the third patty. The proposed protocol guarantees patients' biometric information integrity as compounding random numbers between administrators and hospital/clinic managers, and uses continuous number SEQ and time stamp T to synchronize IMD/administrators and administrators/hospital managers. Also, to protect user's privacy from the third party, patients' biometric information can be safely guarded by managing patients' security identifiers by administrators.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.3
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• pp.311-317
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• 2015

Phenotypic characterization and body biometric in 13 traits (height at withers, body length, chest girth, paunch girth, ear length, tail length, length of tail up to switch, face length, face width, horn length, circumference of horn at base, distances between pin bone and hip bone) were recorded in 233 adult Gojri buffaloes from Punjab and Himachal Pradesh states of India. Traits were analysed by using varimax rotated principal component analysis (PCA) with Kaiser Normalization to explain body conformation. PCA revealed four components which explained about 70.9% of the total variation. First component described the general body conformation and explained 31.5% of total variation. It was represented by significant positive high loading of height at wither, body length, heart girth, face length and face width. The communality ranged from 0.83 (hip bone distance) to 0.45 (horn length) and unique factors ranged from 0.16 to 0.55 for all these 13 different biometric traits. Present study suggests that first principal component can be used in the evaluation and comparison of body conformation in buffaloes and thus provides an opportunity to distinguish between early and late maturing to adult, based on a small group of biometric traits to explain body conformation in adult buffaloes.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.671-676
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• 2016

Recently, according to the limelight of Fintech, simple payment using biometric at smartphone is widely used. In this paper, we propose a new contactless biometric method using thumb image without additional sensors unlike previous biometrics such as fingerprint, iris, and vein recognition. In our method, length, width, and skin texture information are used as features. For that, illumination normalization, skin region segmentation, size normalization and alignment procedures are sequentially performed from the captured thumb image. Then, correlation coefficient is calculated for similarity measurement. To analyze recognition accuracy, genuine and imposter matchings are performed. At result, we confirmed the FAR of 1.68% at the FRR of 1.55%. In here, because the distribution of imposter matching is almost normal distribution, our method has the advantage of low FAR. That is, because 0% FAR can be achieved at the FRR of 15%, the proposed method is enough to 1:1 matching for payment verification.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.465-471
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• 2018

Recently, biometric technology has begun to be used as a fusion of IT technology and financial system. Using this biometric technology, FIDO(Fast Identity Online) technology, Samsung and Apple started Samsung Pay and Apple Pay service. FIDO authentication technology replaces existing authentication methods such as passwords. Among the biometric technologies, fingerprint recognition technology is attracting attention because it can minimize the device and user rejection at a relatively low price. However, fingerprint information has a limited number of users and it can not be reused if fingerprint information is leaked by an external attacker. Therefore, in this paper, we propose a method to authenticate a user using EEG signal which is one of biometrics technologies. W propose a method to use EEG signal measurement value in FIDO system by using convenience channel by using short channel EEG device. And propose a method to utilize EEG signal when the user recognizes a specific entity by measuring the EEG signal before and after recognizing a specific entity.

• Journal of KIISE
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• v.42 no.4
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• pp.419-426
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• 2015

This paper proposes a fingerprint verification system on a fuzzy vault with steganography for a smartphone. While biometric-based authentication can provide strong security, the biometric data must be handled carefully as it cannot be re-enrolled when it is revealed to other people. When the transformed data is used for authentication, the original biometric data can be protected. In this paper, we combine a fingerprint verification system with a fuzzy vault scheme to protect the fingerprint data of a smartphone user. In addition, the transformed data using a fuzzy vault scheme increases the security as it is concealed by the steganography scheme. The result of the experiment using fingerprint databases shows that the proposed scheme provides a high level of convenience and security for authentication of a smartphone having with a fingerprint sensor.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5847-5855
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• 2013

The purpose of this research is to develop Dementia-diagnosis application program through inter-working between biometric sensors and smart phone with diagnostic programs. Receiving data from 2 biometric sensors, SpO2 and HRV(heart rate variability) with Bluetooth and adding scores from questionnaires and memory test game, smart phone can draw a final Dementia Index(DI). Simple clinical tests provided threshold for Dementia, and diagnosis was made by comparing the DI with the threshold. We performed testing on persons aged over 60 and found out the proposed application can be used to diagnose Dementia easily and quickly. Additionally, we have shown the potential of oxygen chamber combined with Dementia-diagnosis application as a medical equipment to ease or cure Dementia in its early stages.

• Smart Media Journal
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• v.5 no.4
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• pp.124-130
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• 2016

Big data technologies are increasing the need for big data in many areas of the world. Recently, the health care industry has become increasingly aware of the importance of disease and health care services, as it has become increasingly immune to prevention and health care. To do this, we need a Big data system to collect and analyze the personal biometric data. In this paper, we design the biometric big data system using low cost wearable device. We collect basic biometric data, such as heart rate, step count and physical activity from Mi Band, and store the collected biometric data into MongoDB. Based on the results of this study, it is possible to build a big data system that can be used in actual medical environment by using Hadoop etc. and to use it in real medical service in connection with various wearable devices for medical information.

• The Journal of the Korea Contents Association
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• v.9 no.3
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• pp.28-38
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• 2009

Login process uses both ID and password information to authenticate someone and to permit its access privilege on system. However, an attacker can get those ID and password information by using existing packet sniffing or key logger programs. It cause privacy problem as those information can be used as a hacking and network attack on web server and web e-mail system. Therefore, a more secure and advanced authentication mechanism should be required to enhance the authentication process on existing system. In this paper, we propose a multi-factor authentication process by using software form of secure card system combined with existing ID/Password based login system. Proposed mechanism uses a random number generated from the his/her own handset with biometric information. Therefore, we can provide a one-time password function on web login system to authenticate the user using multi-factor form. Proposed scheme provide enhanced authentication function and security because it is a 'multi-factor authentication mechanism' combined with handset and biometric information on web login system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.513-516
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• 2013

In this paper, we present an information collecting system in medical information management domain. Our proposed system performs a systemized process, consisting of collection, transmission, and management, to develop intelligent medical information system and medical big data processing system. Our information collecting system consists of low-power biomedical sensors, biomedical information collecting devices, and storage systems. Currently, almost biomedical information of patients is collected manually by employees like nurses and medical doctors. Therefore, collected biometric data can be error-pronoun data. Since there is a lack to make big data of medical information, it is difficult to enhance the quality of medical services and researches. Accordingly, through our proposed system, we can overcome the problems like error-pronoun biometric data. In addition, we can extremely extend the area of collectable biometric data. Furthermore, using this system, we are able to make a real-time biomedical analysis system, like a real-time patient diagnosis system, and establish a strategy to against future medical markets changing rapidly.