• Convergence Security Journal
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• v.18 no.2
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• pp.33-40
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• 2018

ICT technology has been applied to various educational fields, but applying to educational test field is limited. Computer-based test (CBT) can overcome temporal and spatial constraints of conventional paper-based test, but is vulnerable to fraud by test parties. In this paper, we propose real-time monitoring and process management methods to enhance the security of CBT. In the proposed methods, the test screens of students are periodically captured and transferred to the professor screen to enable real-time monitoring, and the possible processes used for cheating can be blocked before testing. In order to monitor the screen of many students in real time, effective compression of the captured original image is important. We applied three-step compression methods: initial image compression, resolution reduction, and re-compression. Through this, the original image of about 6MB was converted into the storage image of about 3.8KB. We use the process extraction and management functions of Windows API to block the processes that may be used for cheating. The CBT system of this paper with the new security enhancement methods shows the superiority through comparison of the security related functions with the existing CBT systems.

• Journal of the Korea Computer Graphics Society
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• v.27 no.1
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• pp.1-8
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• 2021

This paper proposes a simple deformation method for editing the trajectory of a walking motion with preserving its style. To this end, our method analyzes the trajectory of the root joint into the graph and deforms it by applying the graph Laplace operator. The trajectory of the root joint is presented as a graph with a vertex defined the position and direction at each time frame on the motion dataThe graph transforms the trajectory into the differential coordinate, and if the constraints are set on the trajectory vertex, the solver iterative approaches to the solution. By modifying the root trajectory, we can continuously vary the walking motion, which reduces the cost of capturing a whole motion that is required. After computes the root trajectory, other joints are copied on the root and post-processed as a final motion. At the end of our paper, we show the application that the character continuously walks in a complex environment while satisfying user constraints.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.3
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• pp.155-163
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• 2011

Rumor or abusive web postings in internet has become a social issue. Web postings may be proposed on evidence in form of a screenshot in libel suit, but a screenshot can be easily modified by computer programs. A person can make ill use of the screenshot which is modified deliberately original contents to opposite meaning in a lawsuit. That makes an innocent person to be punished because it can have difficulties to verify despite analyzing the server data. A screenshot of web postings is likely to fail to prove its authenticity and it is not able to reflect the fact. If notarization for web postings is offered, clear and convincing evidence can be submitted in a court. So, related techniques and policies should be established In this paper, we propose some technical and legal conditions and design for notarization and archive system of web postings for litigation.

• Journal of IKEEE
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• v.24 no.4
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• pp.1050-1057
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• 2020

Immersive 360-degree media has a problem of slowing down the video recognition speed when the video is processed by the conventional method using a variety of rendering methods, and the video size becomes larger with higher quality and extra-large volume than the existing video. In addition, in most cases, only one scene is captured by fixing the camera in a specific place due to the characteristics of the immersive 360-degree media, it is not necessary to extract feature information from all scenes. In this paper, we propose a reference frame selection method for immersive 360-degree media and describe its application process to copyright protection technology. In the proposed method, three pre-processing processes such as frame extraction of immersive 360 media, frame downsizing, and spherical form rendering are performed. In the rendering process, the video is divided into 16 frames and captured. In the central part where there is much object information, an object is extracted using an RGB vector per pixel and deep learning, and a reference frame is selected using object feature information.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.403-412
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• 2021

As the number of mobile apps increases exponentially, automation of tests performed in the app development process is becoming more important. Until the app is released, iterative verification is performed through various types of tests, and this study was conducted focusing on the GUI test among various types of tests. This study is meaningful in that it can contribute to the stable app distribution of the developer by suggesting the development direction of the GUI test. To develop Android's GUI test tool, I collected basic data before presenting the development method by researching Android's UI controls and Material design guideline. After that, for the existing GUI test automation tool, two tools based on screen capture test and four tools based on source code analysis test were studied. Through this, it was found that existing GUI test tools don't consider visual design, usability, and component arrangement. In order to supplement the shortcomings of existing tools, a new GUI test automation tool development method was presented based on the basic data previously studied.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.571-576
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• 2021

This study was carried out to overcome the problems of the existing fitness business and to build a fitness system that can meet the increased demand in the Corona situation. As a platform technology for non-face-to-face fitness edutainment service, it is a next-generation fitness exercise device that can use various body parts and synchronize network-type information. By synchronizing the exercise information of the fitness equipment, it was composed of learning contents through MR-based avatars. A quantified result was derived from examining the applicability of the customized evaluation system through momentum analysis with A.I analysis applying the LSTM-based algorithm according to the cumulative exercise effect of the user. It is a motion capture and 3D visualization fitness program for the application of systematic exercise techniques through academic experts, and it is judged that it will contribute to the improvement of the user's fitness knowledge and exercise ability.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.39-46
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• 2021

In this paper, we propose a method for the motion recognition method required in the industrial field in mixed reality. In industrial sites, movements (grasping, lifting, and carrying) are required throughout the upper full-body, from trunk movements to arm movements. In this paper, we use a method composed of sensors and wearable devices that are not vision-based such as Kinect without using heavy motion capture equipment. We used two IMU sensors for the trunk and shoulder movement, and used Myo arm band for the arm movements. Real-time data coming from a total of 4 are fused to enable motion recognition for the entire upper body area. As an experimental method, a sensor was attached to the actual clothes, and objects were manipulated through synchronization. As a result, the method using the synchronization method has no errors in large and small operations. Finally, through the performance evaluation, the average result was 50 frames for single-handed operation on the HoloLens and 60 frames for both-handed operation.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.977-984
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• 2022

Recently, with the economic development of Southeast Asia, the use of information devices is widely spreading, and the demand for application services using intelligent character recognition is increasing. This paper discusses deep learning-based feature extraction and recognition of Myanmar, one of the Southeast Asian countries. Myanmar alphabet (33 letters) and Myanmar numerals (10 numbers) are used for feature extraction. In this paper, the number of nine features are extracted and more than three new features are proposed. Extracted features of each characters and numbers are expressed with successful results. In the recognition part, convolutional neural networks are used to assess its execution on character distinction. Its algorithm is implemented on captured image data-sets and its implementation is evaluated. The precision of models on the input data set is 96 % and uses a real-time input image.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.827-835
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• 2022

In order to use online financial services, user authentication technology is necessary. Password check through keyboard typing is the most common technique. However, since it became known that key stokes on the keyboard can be intercepted easily, many Internet banking services and easy payment services have adopted the virtual keyboard. However, contrary to the expectation that the virtual keyboard will be safe, there is a risk that key strokes on the virtual keyboard can be leaked. In this paper, we analyzed the possibility of password leaking on the virtual keyboard and presented a password leaking method using mouse event hooking and screen capture in PC operating system. In addition, we inspected the possibility of password leak attacks on several famous Korea Internet banking websites and simple payment services, and as a result, we verified that the password input method through the virtual keyboard in the PC operating system is not secure.

• Smart Media Journal
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• v.12 no.7
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• pp.59-67
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• 2023

Recently, research on behavior analysis tracking human posture and movement has been actively conducted. In particular, OpenPose, an open-source software developed by CMU in 2017, is a representative method for estimating human appearance and behavior. OpenPose can detect and estimate various body parts of a person, such as height, face, and hands in real-time, making it applicable to various fields such as smart healthcare, exercise training, security systems, and medical fields. In this paper, we propose a method for classifying four exercise movements - Squat, Walk, Wave, and Fall-down - which are most commonly performed by users in the gym, using OpenPose-based deep learning models, DNN and CNN. The training data is collected by capturing the user's movements through recorded videos and real-time camera captures. The collected dataset undergoes preprocessing using OpenPose. The preprocessed dataset is then used to train the proposed DNN and CNN models for exercise movement classification. The performance errors of the proposed models are evaluated using MSE, RMSE, and MAE. The performance evaluation results showed that the proposed DNN model outperformed the proposed CNN model.