• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2003.12a
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• pp.307-310
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• 2003

웹서비스에 대한 높은 관심과 함께 그 실현이 점차 가시화되고 XML로 이루어진 지원 기술들의 전폭적인 지지로 잠재력은 더욱 확대되고 있다. 웹서비스는 기존 웹 기반의 디스플레이에 그쳤던 단순정보 교환을 애플리케이션 차원에서 데이터를 통신할 수 있어 개발 가능성이 무한한 프레임워크로 각광받고 있다. 그러나 현재 자원 관리에서의 효율성 문제가 드러나게 되었고 인증분야와의 접목에서도 한계를 드러내고 있다. XACML은 리소스에 대한 미세한 접근제어를 할 수 있는 XML기반의 언어이다. 접근하려는 리소스는 XML을 사용하여 표현되는 어떠한 객체도 될 수 있으며 XPath나 LDAP과 같은 프로토콜과 함께 바인딩하여 사용될 수도 있다. 보다 효율적인 접근 제어를 위하여 XACML 적용 모델을 연구하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.358-360
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• 2002

자바 기술의 특성은 자바가상머신(Java Virtual Machine 이하 JVM)이 탑재되어 있다면 어떤 환경에서라도 동일하게 수행되는 플랫폼 독립성과 온라인 서비스 상에서 신뢰성이 없는 정보로부터 사용자를 보호해 주는 강력한 보안성, 객체 직렬화와 원격 메소드 호출을 통한 네트워크 mobility 로 요약할 수 있다. 이 특성 중에 플랫폼 독립성은 자바 기술의 가장 큰 장점이라 할 수 있다. 그러나 플랫폼 독립성이 보장되기 위한 전제 조건이 있는데 JVM을 어느한 플랫폼에 탑재하기 위해 플랫폼에 의존적인 부분(입출력, 쓰레드, 그랙픽등)을 JVM 계층과 클래스 라이브러리 계층에서 구현해야 한다는 것이다. 이런 점은 자바 기술의 본 소유회사인 SUN 사에서 제공하는 specification 에서도 제대로 다루어지지 않아서 실제로 JVM 개발자나 클래스 라이브러리 개발자에게 아주 힘든 작업을 요한다. 본 논문에서는 플랫폼에 의존적인 부분 중 쓰레드를 지원하기 위한 클래스 라이브러리를 구현하고자 한다.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.47-58
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• 2022

In recent years, navigation aids, which plays as sea traffic lights, have been digitized, and are developing beyond simple sign purpose to provide various functions such as marine information collection, supervision, control, etc. For example, Busan Port which is located in South Korea is leading the application of the advanced technologies by installing cameras on buoys and recording video images to supervise maritime accidents. However, there are difficulties to perform their major functions since the advanced technologies require long-term battery operation and also management and maintenance of them are hampered by marine characteristics. This study proposes a system that can automatically notify maritime objects passing around buoys by analyzing image information. In the existing sensor-based accident prevention systems, the alarms are generated by a collision detection sensor. The system can identify the cause of the accident whilst even though it is difficult not possible to fundamentally prevent the accidents. Therefore, in order to overcome these limitations, the proposed a maritime object detection system is based on marine characteristics. The experiments demonstrate that the proposed system shows about 5 times faster processing speed than other existing algorithms.

• Journal of Advanced Navigation Technology
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• v.12 no.5
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• pp.451-463
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• 2008

There are management and security of software source code equivalent to 10 assembly lines of important infrastructure in the early stage of information society directly. A support technology and framework to protect software source code are so poor state In this paper, the proposed model that is support protection and access control between software source code as object and subject that is not authenticated safely was named CRYPTEX model. And we propose active business model to provide delegate, mobile, and security/access control function for passive software source code in document state using CRYPTEX.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.161-169
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• 2011

Recent intelligent video surveillance system asks for development of more advanced technology for analysis and recognition of video data. Especially, machine learning algorithm such as Support Vector Machine (SVM) is used in order to recognize objects in video. Because SVM training demands massive amount of computation, parallel processing technique is necessary to reduce the execution time effectively. In this paper, we propose a parallel processing method of SVM training with a multi-core processor. The results of parallel SVM on a 4-core processor show that our proposed method can reduce the execution time of the sequential training by a factor of 2.5.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.5
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• pp.57-70
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• 2009

A CAD design drawing based on vector data that is very important art work in industrial fields has been considered to content that the copyright protection is urgently needed. This paper presents a watermarking scheme based on k-means++ for CAD design drawing. One CAD design drawing consists of several layers and each layer consists of various geometric objects such as LINE, POLYLINE, CIRCLE, ARC, 3DFACE and POLYGON. POLYLINE with LINE, 3DFACE and ARC that are fundamental objects make up the majority in CAD design drawing. Therefore, the proposed scheme selects the target object with high distribution among POLYLINE, 3DFACE and ARC objects in CAD design drawing and then selects layers that include the most target object. Then we cluster the target objects in the selected layers by using k-means++ and embed the watermark into the geometric distribution of each group. The geometric distribution is the normalized length distribution in POLYLINE object, the normalized area distribution in 3DFACE object and the angle distribution in ARC object. Experimental results verified that the proposed scheme has the robustness against file format converting, layer attack as well as various geometric editing provided in CAD editing tools.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.29-35
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• 2023

CCTV is used for various purposes such as crime prevention, public safety reinforcement, and traffic management. However, as the range and resolution of the camera improve, there is a risk of exposing personal information in the video. Therefore, there is a need for new technologies that can identify individuals while protecting personal information in images. In this paper, we propose histogram-based singular value decomposition for object identification and tracking. The proposed method distinguishes different objects present in the image using color information of the object. For object recognition, YOLO and DeepSORT are used to detect and extract people present in the image. Color values are extracted with a black-and-white histogram using location information of the detected person. Singular value decomposition is used to extract and use only meaningful information among the extracted color values. When using singular value decomposition, the accuracy of object color extraction is increased by using the average of the upper singular value in the result. Color information extracted using singular value decomposition is compared with colors present in other images, and the same person present in different images is detected. Euclidean distance is used for color information comparison, and Top-N is used for accuracy evaluation. As a result of the evaluation, when detecting the same person using a black-and-white histogram and singular value decomposition, it recorded a maximum of 100% to a minimum of 74%.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.23-37
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• 2024

Digital twin is an M&S (Modeling and Simulation) technology designed to solve or optimize problems in the real world by replicating physical objects in the real world as virtual objects in the digital world and predicting phenomena that may occur in the future through simulation. Digital twins have been elaborately designed and utilized based on data collected to achieve specific purposes in large-scale environments such as cities and industrial facilities. In order to apply this digital twin technology to real life and expand it into user-customized service technology, practical but sensitive issues such as personal information protection and personalization of simulations must be resolved. To solve this problem, this paper proposes a federated learning-based accelerated client training method (FACTS) for personalized digital twins. The basic approach is to use a cluster-driven federated learning training procedure to protect personal information while simultaneously selecting a training model similar to the user and training it adaptively. As a result of experiments under various statistically heterogeneous conditions, FACTS was found to be superior to the existing FL method in terms of training speed and resource efficiency.

• Journal of Platform Technology
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• v.11 no.3
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• pp.56-67
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• 2023

Recently, de-identification of personal information, which has been a long-cherished desire of the data-based industry, was revised and specified in August 2020. It became the foundation for activating data called crude oil[2] in the fourth industrial era in the industrial field. However, some people are concerned about the infringement of the basic rights of the data subject[3]. Accordingly, a development study was conducted on the Batch De-Identification Tool, a personal information de-identification automation tool. In this study, first, we developed an image labeling tool to label human faces (eyes, nose, mouth) and car license plates of various resolutions to build data for training. Second, an object recognition model was trained to run the object recognition module to perform de-identification of personal information. The automated personal information de-identification tool developed as a result of this research shows the possibility of proactively eliminating privacy violations through online services. These results suggest possibilities for data-based industries to maximize the value of data while balancing privacy and utilization.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.84-90
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• 2020

As the uploading and downloading of data through the Internet is becoming more common, data including personal information are easily exposed to unauthorized users. In this study, we detect a target area in images that contain personal information, except for the background, and we protect the detected target area by using a blocking method suitable for the surrounding situation. In this method, only the target area from color image input containing personal information is segmented based on skin color. Subsequently, blurring of the corresponding area is performed in multiple stages based on the surrounding situation to effectively block the detected area, thereby protecting the personal information from being exposed. Experimental results show that the proposed method blocks the object region containing personal information 2.3% more accurately than an existing method. The proposed method is expected to be utilized in fields related to image processing, such as video security, target surveillance, and object covering.