• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.10a
• /
• pp.485-488
• /
• 2010

Recently, as the dissemination of the Internet and development of computer network technology, Research is actively underway for realization of the next-generation computing paradigm called Ubiquitous Computing. It will not be constrained by Space-time and It will be a cornerstone of human-oriented services. Such ubiquitous computing as a core technology for USN (Ubiquitous Sensor Network) is presented. In this paper, the sensor information into a standardized form to describe the information describing standards and USN sensor applications for the service standard for directory services protocols were investigated.

• International Journal of Computer Science & Network Security
• /
• v.21 no.6
• /
• pp.286-293
• /
• 2021

Recently, the quick development rate of apps in the Android platform has led to an accelerated increment in creating malware applications by cyber attackers. Numerous Android malware detection tools have utilized conventional signature-based approaches to detect malware apps. However, these conventional strategies can't identify the latest apps on whether applications are malware or not. Many new malware apps are periodically discovered but not all malware Apps can be accurately detected. Hence, there is a need to propose intelligent approaches that are able to detect the newly developed Android malware applications. In this study, Radial Basis Function (RBF) networks are trained using known Android applications and then used to detect the latest and new Android malware applications. Initially, the optimal permission features of Android apps are selected using Information Gain Ratio (IGR). Appropriately, the features selected by IGR are utilized to train the RBF networks in order to detect effectively the new Android malware apps. The empirical results showed that RBF achieved the best detection accuracy (97.20%) among other common machine learning techniques. Furthermore, RBF accomplished the best detection results in most of the other measures.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2010.11a
• /
• pp.175-176
• /
• 2010

SaaS 플랫폼은 메타데이타를 기반으로 사용자에게 다중 사용자 지원 및 용이한 환경 설정으로 다양한 사용자 요구를 충족시키려 하고 있다. 따라서, 여러 고객이 하나의 서비스 인스턴스를 공유하고, 데이터베이스 안의 정보를 각자 관리할 수 있어 서비스로서 애플리케이션의 비용을 절감할 수 있다. 본 논문에서는 SaaS 플랫폼의 하나로 개발중인 SaaSpia 플랫폼에서 다중 사용자 지원 및 용이한 환경 설정을 위해 관리되어야 할 메타데이타를 알아보고, SaaSpia 애플리케이션에서 메타데이타 지원을 연구한다. SaaSpia 플랫폼에서 메타데이타는 일반 웹 애플리케이션을 SaaSpia 애플리케이션으로 변환하거나, 운용중인 SaaSpia 애플리케이션의 사용자별 설정 변경 시, 이용된다.

• Journal of Korea Society of Industrial Information Systems
• /
• v.13 no.5
• /
• pp.149-157
• /
• 2008

In the field of computing service, there is a copernican revolution indebted to development of network & computer technology. Computer system, which is set to mainframe in the 1960's, is advancing torwards to the paradigm of server based computing, so-called thin-client. In thin-client computing, network is the platform which is responsible for transfer of application, so that client execute application installed on server. It is also possible that each system share the computing resource connected with network. In this parer, we suggest component & distributed computing technology as a measn for the implementation of thin-client architecture hence, make the best use of COM(Component Object Model and PYRO(PYthon Remote Objects). We talk about the concept and mechanism of thin-client at the beginning, and propose the design of network architecture for the implementation thin-client.

• Journal of Internet Computing and Services
• /
• v.17 no.4
• /
• pp.19-26
• /
• 2016

In this paper, the dynamic buffering based smart OTT platform was proposed, and analyzed for adaptive bit-rate video delivery with the optimization of HLS (HTTP Live Streaming). This platform consists of the software platform between sever and client which detects the bandwidth capacity, and adjusts the quality of the streaming for multiple bit-rates resolutions. In order to apply adaptive buffering, two buffers are added to the basic HLS player, and each buffer is responsible for constantly buffering a previous and the next channels relative to the current channel. This adaptive transmitting with smart OTT platform is superior to delivering a static video file at a single buffering, because the video stream of adaptive double buffers can be switched streaming according to client's available network speed. As a result, this proposed smart OTT can be cooperated to the application of HLS server with segmented H.265 MPEG-2 TS video & m3u8 files with its information based on the optimized transmission channel state of live and VOD, and applied to PLC transmission, too.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.5
• /
• pp.1022-1029
• /
• 2009

What Ubiquitous means "being or existing anywhere, anytime"in Latin, which is, in other words, the users are able to access the network no matter where they are, what kind of network or computer terminals they use. This paper focuses on the implementation of hardware system. The first part of the sytem is the sensor node which transmits the sensor data from node to ARM11 platform through the Zigbee network wirelessly. The other part of the system is the ARM11 platform which receives and displays the sensor data. ARM11 platform is sink node. The ARM11 platform is based on ARM11 architecture and ported with Linux OS. Qtopia is used as Window Manager in order to make applications. The highly efficient ARM11 processor, S3C6400 MPC is the main part of the ARM11 platform.

• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.11
• /
• pp.1091-1095
• /
• 2010

The existing smart-phone software is dependent on the platform, which should be developed per each different platform, Each vendor will develop its own platform such as Apple's Cocoa platform, Google Android, Microsoft Windows Mobile, etc. In this paper, we apply model transformation technique for developing heterogenous software at a time in heterogenous smart phone area. This approach separates the independent model and dependent model. and automatically transforms the difference between them with model transformation language. To execute model transformation, it is required with meta model, model transformation language. In this paper, we are applied to smart-phones as follows: model will be UMLmodel, metamodel be UML metamodel, and choose ATL as Model transformation language. We show examples of the Windows Mobile platform environment to be developed using model transformation. As a result, if we use platform-independent model in this paper and redefine model transformation rules for the iPhone or Android, it will be automatically transformed into heterogenous platforms.

• Journal of KIISE:Computing Practices and Letters
• /
• v.6 no.2
• /
• pp.206-215
• /
• 2000

This paper is concerned with the development of PCS(Platform for Collaborative System), which is a platform for development of remote collaborative experiment systems. Platform does not aim at the development of special-domain applications. This system implies the common development environments which can develop all-domain applications. PCS consists of collaborative experimental objects such as communication, session, user, application, media, message object and management objects that have management functions. Management objects are made up of collaborative experimental objects and operations which manipulate control information and data. It also supports application sharing for making single user interface of experimental applications to multi-user interface. Application sharing also supports instruments control on the remote site. PCS platform supports total environments for remote collaborative experiment and can be used as infrastructure to all kinds of collaboratory systems.

• Journal of Convergence for Information Technology
• /
• v.7 no.5
• /
• pp.177-182
• /
• 2017

As major ICT technologies such as IoT, cloud computing, and Big Data are being applied to manufacturing, smart factories are beginning to be built. The key of smart factory implementation is the ability to acquire and analyze data of the factory. Therefore, the need for a big data analysis platform is increasing. The purpose of this study is to construct a platform for big data analysis of manufacturing process and propose integrated method for analysis. The proposed platform is a RHadoop-based structure that integrates analysis tool R and Hadoop to distribute a large amount of datasets. It can store and analyze big data collected in the unit process and factory in the automation system directly in HBase, and it has overcome the limitations of RDB - based analysis. Such a platform should be developed in consideration of the unit process suitability for smart factories, and it is expected to be a guide to building IoT platforms for SMEs that intend to introduce smart factories into the manufacturing process.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.10a
• /
• pp.496-499
• /
• 2016

The smartfarm is a leader in the Field of environmental monitoring in agriculture. By the use of wireless remote systems, monitoring applications of the smartfarm are able to provide vital information to the farmer wherever he may be. Absentee farmers are finding the ease of viewing the application graphs on their mobile phone is providing them with peace of mind. We design system and technical requirements of service for managing and operating smart-farm based on cloud technology. It describes requirements of cloud technology for monitoring, controlling, managing, and operating cloud-based smart farm. Smart farm system and service with cloud platform contains 3 interfaces and 3 services. In addition, smart-farm using cloud platform could have several cases so it should be established and managed in varying way depending on cultivars, its size and type. This paper will focus the industry's attention on the importance of Open/Standard Cloud platform thereby stimulating the smartfarm in agriculture.