• Journal of the Korea Society of Computer and Information
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• v.26 no.9
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• pp.89-96
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• 2021

In this paper, we analyzed that the user authentication scheme for TMIS(Telecare Medicine Information System) proposed by Al-Saggaf et al. In 2019, Al-Saggaf et al. proposed authentication scheme using biometric information, Al-Saggaf et al. claimed that their authentication scheme provides high security against various attacks along with very low computational cost. However in this paper after analyzing Al-Saggaf et al's authentication scheme, the Al-Saggaf et al's one are missing random number s from the DB to calculate the identity of the user from the server, and there is a design error in the authentication scheme due to the lack of delivery method. Al-Saggaf et al also claimed that their authentication scheme were safe against a variety of attacks, but were vulnerable to password guessing attack using login request messages and smart cards, session key exposure and insider attack. An attacker could also use a password to decrypt the stored user's biometric information by encrypting the DB with a password. Exposure of biometric information is a very serious breach of the user's privacy, which could allow an attacker to succeed in the user impersonation. Furthermore, Al-Saggaf et al's authentication schemes are vulnerable to identity guessing attack, which, unlike what they claimed, do not provide significant user anonymity in TMIS.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.1
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• pp.85-93
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• 2018

Biometric user authentications, day after day, propagate more to human life instead of traditional systems which use passwords and ID cards. However, most of these systems have many problems for given biometric information such noisy data, low-quality data, a limitation of recognition rate, and so on. To deal with these problems, I used Dual QML which is non-linear classification for classifying correctly the real-world data and then proposed preprocessing method for increasing recognition rate and performance by segmenting a specific region on an image. The previous published Dual QML used face, palmprint, ear for the experiment. In this paper, I used iris for experiment and then proved excellence of Dual QML at iris recognition. Finally I demonstrated these results (e.g. increasing recognition rate and performance, suitability for iris recognition) through experiments.

• The KIPS Transactions:PartC
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• v.19C no.3
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• pp.167-172
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• 2012

Mobile phone devices and memory card can be robbed and lost due to the carelessness that might be caused to leak personal information, and also company's confidential information can be disclosed. Therefore, the importance of user authentication to protect personal information is increasing exponentially. However, there are the limitations that criminals could easily obtain and abuse information about individuals, because the input method of personal identification number or the input method of password might not be safe for Shoulder Surfing Attack(SSA). Although various biometric identification methods were suggested to obstruct the SSA, it is the fact that they also have some faults due to the inconvenience to use in mobile environments. In this study, more complemented service for the user authentication was proposed by applying Keystroke method in the mobile environments to make up for the faults of existing biometric identification method. Lastly, the effectiveness and validity of this study were confirmed through experimental evaluations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.12
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• pp.2348-2354
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• 2016

In recent days, IoT (Internet of Things) technology has been widely used in the field of agriculture, which enables the collection of environmental data and biometric data into the database. The availability of big data on agriculture results in the increase of the machine learning based analysis. Through the analysis, it is possible to forecast agricultural production and the diseases of livestock, thus helping the efficient decision making in the management of smart farm. Herein, we use the environmental and biometric data of Smart Pig farm to derive the accurate relationship model between the environmental information and the daily weight increase of swine and verify the accuracy of the derived model. To this end, we applied the M5P tree algorithm of machine learning which reveals that the wind speed is the major factor which affects the daily weight increase of swine.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8C
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• pp.690-696
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• 2012

Recently, the need for telemedicine services and user's service requirements are increasing, the research for more convenient telemed service is underway in various fields. In this paper, we propose that Integrated telemedicine system possible to regular health care. unlike the existing telemedicine system, we combine the voice communications systems and biometric information based on CPS (Cyber Physical System) using wireless communication sensor and elderly people who disabilities are transmit the information comfortably, Also doctors in correspondent site are able to improves the accuracy of the medical treatment by received information about biometric and audio communication. In addition Health status information is stored selectively and then doctor can check the elders status everytime and everywhere. In this paper, we designed the telemedicine system suitable for korea aging society situation, therefore we could offer the Elderly-friendly medical service for seniors who live in silver town.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1898-1908
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• 2017

Accurately Diagnosing and managing disease in livestock can help sustainable livestock productivity and maintain human health. Maintaining the health of livestock is an important part of human health. The prediction of calf diseases is carried out by pre-processing the calf biometric data. calf information is used as information for calf birth history, calf biometric information, environmental information on housing, and disease management. It can be developed as an ontology and used as a knowledge base. The Bayesian network was used and inferred in the process of analyzing the correlations of calf diseases. Prediction of diseases based on knowledge of calf disease on calf diseases name, causes, occur timing, care and symptoms, etc., will be able to respond to accurate disease treatment and prevent other livestock from being infected in advance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.215-222
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• 2021

As the importance of human-computer interaction (Human Computer Interface) technology grows and research on HCI is progressing, it is inferred about the research emotion inference or the computer reaction according to the user's intention, not the computer reaction by the standard input of the user. Stress is an unavoidable result of modern human civilization, and it is a complex phenomenon, and depending on whether or not there is control, human activity ability can be seriously changed. In this paper, we propose an intelligent emotional recommendation system using music as a way to relieve stress after measuring heart rate variability (HRV) and acceleration photoplethymogram (APG) increased through stress as part of human-computer interaction. The differential evolution algorithm was used to extract reliable data by acquiring and recognizing the user's biometric information, that is, the stress index, and emotional inference was made through the semantic web based on the obtained stress index step by step. In addition, by searching and recommending a music list that matches the stress index and changes in emotion, an emotional recommendation system suitable for the user's biometric information was implemented as an application.

• Journal of Digital Policy
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• v.1 no.1
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• pp.15-20
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• 2022

Recently, the healthcare field is trying to develop a model that can improve service quality by reflecting the requirements of various industrial fields. In this paper, we propose an Internet of Behavior (IoB) environment model that can process users' healthcare information in real time in a 5G environment to improve healthcare services. The purpose of the proposed model is to analyze the user's healthcare information through deep learning and then check the health status in real time. In this case, the biometric information of the user is transmitted through communication equipment attached to the portable medical equipment, and user authentication is performed through information previously input to the attached IoB device. The difference from the existing IoT healthcare service is that it analyzes the user's habits and behavior patterns and converts them into digital data, and it can induce user-specific behaviors to improve the user's healthcare service based on the collected data.

• Smart Media Journal
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• v.11 no.2
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• pp.25-30
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• 2022

With the recent development of device performance such as smartphones, cameras, and video cameras, it has become possible to obtain human biometric information from images and photos. A German hacker group obtained human iris information from high-definition photos and revealed hacking into iris scanners on smartphones. As high-quality images and photos can be obtained with such advanced devices, the need for a suitable security system is also emerging. Therefore, in this paper, we propose a method of automatically masking human iris information in images and photos using Haar Cascades and Blur models from openCV. It is a technology that automatically masks iris information by recognizing a person's eye in a photo or video and provides the result. If this technology is used in devices and applications such as smartphones and zoom, it is expected to provide better security services to users.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.301-303
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• 2003

기존의 아이디와 패스워드를 이용한 사용자 인증방식의 문제점 및 한계를 해결하기 위하여 생체인식 기술 (Biometric technology)이 연구되었다. 하지만 단일 생체인식 기술은 오인식률(False Acceptance Rate), 오거부율(False Rejection Rate)등의 문제점을 가지고있다. 최근에 단일 생체인식 기술의 한계를 극복하고 사용자 인증 성능 향상과 신뢰도를 높이기 위하여 다중 생체 인식(Multi-modal biometrics)에 관한 연구개발이 활발하다. 이 논문은 지문인식과 얼굴인식 기술을 활용하여 사용자 인증을 수행함으로써 단일 시스템에서 발생하는 한계점을 극복함과 동시에 좀더 안정적인 사용자 인증이 가능한 방법을 제시한다.