• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1871-1890
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• 2021

The transition toward a contactless society has been rapidly progressing owing to the recent COVID-19 pandemic. As a result, the IT environment of organizations and enterprises is changing rapidly; in particular, data security is expanding to the private sector. To adapt to these changes, organizations and companies have started to securely transfer confidential data to residential PCs and personally owned devices of employees working from home or from other locations. Therefore, organizations and companies are introducing streaming data services, such as the virtual desktop infrastructure (VDI) or cloud services, to securely connect internal and external networks. These methods have the advantage of providing data without the need to download to a third terminal; however, while the data are being streamed, attacks such as screen shooting or capturing are performed. Therefore, there is an increasing interest in prevention techniques against screen capture threats that may occur in a contactless environment. In this study, we analyze possible screen capture methods in a PC and a mobile phone environment and present techniques that can protect the screens against specific attack methods. The detection and defense for screen capture of PC applications on Windows OS and Mac OS could be solved with a single agent using our proposed techniques. Screen capture of mobile devices can be prevented by applying our proposed techniques on Android and iOS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.226-228
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• 2021

We propose a fall recognition system using the Pose Detection of Google ML kit using video data. Using the Pose detection algorithm, 33 three-dimensional feature points extracted from the body are used to recognize the fall. The algorithm that recognizes the fall by analyzing the extracted feature points uses k-NN. While passing through the normalization process in order not to be influenced in the size of the human body within the size of image and image, analyzing the relative movement of the feature points and the fall recognizes, thirteen of the thriteen test videos recognized the fall, showing an 100% success rate.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.745-747
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• 2023

깃허브는 개발자의 명함이라는 말이 있듯, 많은 수의 개발자들이 깃허브를 활용해 자신의 개발 이력과 프로젝트들을 관리한다. 이를 위해 기존의 깃허브 정보 요약 서비스들이 제공되어졌으나, 정보 공유의 불편함과 많은 정보를 담지 못한다는 불편함이 존재했다. 본 논문에서는 이러한 불편함을 해소하기 위해 서버 기반의 깃허브 웹 명함 제작 및 멀티플랫폼에서의 서비스를 기반으로 한 효율적인 개발자 명함 생태계 구축을 제안한다. 본 서비스에서는 Next.js 기술을 활용한 한 명함 제작 및 웹, 앱 클라이언트를 통한 명함 관리 기능을 제공한다. Github oauth를 통해 인증된 정보를 바탕으로 Next.js를 활용해 사용자에 대한 정보를 정해진 형식으로 요약한 명함을 제작한다. 제작된 명함은 웹 / 앱 플랫폼을 기반으로 관리되며, 추가적으로 명함의 공유 및 저장 기능을 수행한다. 이를 통해, 명함 공유를 바탕으로 한 개발자 네트워크 형성을 목표로 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.704-719
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• 2024

Botnet pandemics are becoming more prevalent with the growing use of mobile phone technologies. Mobile phone technologies provide a wide range of applications, including entertainment, commerce, education, and finance. In addition, botnet refers to the collection of compromised devices managed by a botmaster and engaging with each other via a command server to initiate an attack including phishing email, ad-click fraud, blockchain, and much more. As the number of botnet attacks rises, detecting harmful activities is becoming more challenging in handheld devices. Therefore, it is crucial to evaluate mobile botnet assaults to find the security vulnerabilities that occur through coordinated command servers causing major financial and ethical harm. For this purpose, we propose a hybrid analysis approach that integrates permissions and API and experiments on the machine-learning classifiers to detect mobile botnet applications. In this paper, the experiment employed benign, botnet, and malware applications for validation of the performance and accuracy of classifiers. The results conclude that a classifier model based on a simple decision tree obtained 99% accuracy with a low 0.003 false-positive rate than other machine learning classifiers for botnet applications detection. As an outcome of this paper, a hybrid approach enhances the accuracy of mobile botnet detection as compared to static and dynamic features when both are taken separately.

• The KIPS Transactions:PartA
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• v.16A no.3
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• pp.159-168
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• 2009

In this paper, we present an efficient way of implementing OpenGL ES 1.1 standard for the environments with hardware-supported OpenGL API, such as desktop PCs. Although OpenGL ES was started from the existing OpenGL features, it becomes a new three-dimensional graphics library customized for embedded systems through introducing fixed-point arithmetic operations, buffer management with fixed-point data type supports, completely new texture mapping functionalities and others. Currently, it is the official three dimensional graphics library for Google Android, Apple iPhone, PlayStation3, etc. In this paper, we achieved improvements on the arithmetic operations for the fixed-point number representation, which is the most characteristic data type for OpenGL ES. For the conversion of fixed-point data types to the floating-point number representations for the underlying OpenGL, we show the way of efficient conversion processes even with satisfying OpenGL ES standard requirements. We also introduced a simple memory management scheme to mange the converted data for the buffer containing fixed-point numbers. In the case of texture processing, the requirements in both standards are quite different and thus we used completely new software-implementations. Our final implementation result of OpenGL ES library provides all of over than 200 functions in OpenGL ES 1.1 standard and completely passed its conformance test, to show its compliance with the standard. From the efficiency viewpoint, we measured its execution times for several OpenGL ES-specific application programs and achieved at most 33.147 times improvements, to become the fastest one among the OpenGL ES implementations in the same category.

• KIISE Transactions on Computing Practices
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• v.21 no.10
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• pp.658-669
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• 2015

The paradigm of game development changes with technological trends. If the system can analyze and determine undefined inputs, users' input choices are not restricted. Therefore, game scenarios can have multifarious flows depending upon the user's input data. In this paper, we propose a method of including an output plan in the game system that is based on the user's input but is not restricted to predefined choices. We have implemented an experimental game on the Android platform by combining network communication and APIs. The game interface works as follows: first, the user's input data is transmitted to the server using HTTP protocol; then, the server carries out an analysis on the input data; and finally, the server returns the decision result to the game device. The game can provide users a scenario that corresponds to the decision results. In this paper, we used an image file for the user's input data format. The server calculates similarities between the user's image file and reference images obtained from the Naver Image Search API and then returns determination results. We have confirmed the value of integrating the game development framework with other computing technologies demonstrating the potential of the proposed methods for application to various future game interfaces.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.569-572
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• 2014

많은 사람들이 자동차를 교통수단으로 이용함에 따라서 다양한 자동차 액세서리 및 관심을 가지게 되면서, 자동차에서 다양한 여가 활용을 즐길 수 있게 되었다. 그와 함께 스마트폰 보급이 활성화가 되게 되면서 음악을 스마트폰으로 이용하여 들으면서 차에서도 많이들 활용하게 되었다. 하지만, 이러한 스마트폰 사용을 하게 됨으로 인해서 자동차 안에서 스마트폰을 사용하여 사고가 일어나는 빈도가 점점 많아지게 되었다. 그로 인해서 운전자들이 안심하고 사용할 수 있는 어플리케이션 개발이 필요로 하게 되었다. 현재 나와 있는 어플리케이션 중에 Bugs Driver라는 음악 재생 어플리케이션이 있지만, 이 어플리케이션은 차량 운전자를 위한 특별한 기능을 가지고 있지는 않고, 기존 음악 어플리케이션에서 기능을 축소한 음악 어플리케이션이다. 또한, 직관적이지 않은 UI(User Interface)를 가지고 있으며, 속도 또한 충분히 빠르지 않아 운전자가 이용하기에 적합한 어플리케이션이 아니다. 이에 본 연구에서는, 차량 안에서도 안전하고 편리하게 사용할 수 있는 음악 어플리케이션을 개발하였다. 이 어플리케이션은 움직임을 최소화 할 수 있는 UI 와 모션인식을 이용한 어플리케이션 조작, 일정 속도 이상으로 주행 시 어플리케이션을 조작하지 못하도록 하는 기능을 가지고 있다. 음악 관련 정보는 (주)네오위즈의 벅스 어플리케이션 API 를 이용하였고, 모션인식은 OPENCV를 이용하여 구현 하였다.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.99-106
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• 2024

In this paper, we design and implement the HealthSchedule app, which records exercise data based on the GPS sensor embedded in smartphones. This app utilizes the smartphone's GPS sensor to collect real-time location information of the user and displays the movement path to the designated destination. It records the user's actual path using latitude and longitude coordinates. Users register exercise activities and destination points when scheduling, and initiate the exercise. When measuring the current location, a lime green departure marker is generated, and the movement path is displayed in blue, with the destination marker and a surrounding 25-meter radius circle shown in sky blue. Using the coordinates of the starting point or the previous location and the current GPS sensor-transmitted location coordinates, it measures the distance traveled, time taken, and calculates the speed. Furthermore, it accumulates measurement data to provide information on the total distance traveled, movement path, and overall average speed. Even when reaching the destination during exercise, the movement path continues to accumulate until the completion button is clicked. The completion button is activated when the user moves into the sky blue circular area with a radius of 25 meters, centered around the initially set destination. This means that the user must reach the designated destination, and if they wish to continue exercising without clicking the completion button, they can do so. Depending on the selected exercise type, the app displays the calories burned, aiming to increase user engagement and a sense of accomplishment.