• KIPS Transactions on Computer and Communication Systems
• /
• v.3 no.10
• /
• pp.377-382
• /
• 2014

Analysis techniques of the data over time from the mobile environment and IoT, is mainly used for extracting patterns from the collected data, to find meaningful information. However, analytical methods existing, is based to be analyzed in a state where the data collection is complete, to reflect changes in time series data associated with the passage of time is difficult. In this paper, we introduce a method for analyzing multi-block streaming data(AM-MBSD: Analysis Method for Multi-Block Stream Data) for the analysis of the data stream with multiple properties, such as variability of pattern and large capacitive and continuity of data. The multi-block streaming data, define a plurality of blocks of data to be continuously generated, each block, by using the analysis method of the proposed method of analysis to extract meaningful patterns. The patterns that are extracted, generation time, frequency, were collected and consideration of such errors. Through analysis experiments using time series data.

• Journal of Industrial Convergence
• /
• v.17 no.2
• /
• pp.21-27
• /
• 2019

The Internet of things is the infrastructure that can communicate with each other by exchanging information by installing antennas that can communicate with all things in the world. The reason why the Internet of Things is the core of the Fourth Industrial Revolution is that data is collected through the Internet to be. Technology of things Internet and Trend of Things Internet IoT (Internet of Things) is a concept that enables internet connection and communication between devices equipped with various sensors. It is the core IT trend of lot, technology such as big data, mobile, cloud And to provide information for the development of the industrial environment through research on the importance of the Internet of things, the core of the Fourth Industrial Revolution and the processing and analysis techniques of Big Data. By providing various security measures and future technologies, This study was conducted to contribute to management.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.10a
• /
• pp.540-542
• /
• 2014

The Universal Plug and Play (UPnP) specification permits networked devices to discover each other and to provide diverse services in the home network environment. Recently, new paradigms such as mobile connected computing, cloud-based service delivery, smart device content sharing, and Internet of Things (IoT) have emerged, but the home network based UPnP shows functional limitations in supporting such paradigms. To support them, the UPnP Forum has recently extended the capabilities of the existing UPnP, calling it UPnP+. In this paper, the UPnP Device Architecture V2.0 (UDA 2.0), which forms the basis of UPnP+, is presented. We present how UDA 2.0 enables the expansion of the home network to wide-area networks and non-IP device domains.

• KNOM Review
• /
• v.22 no.1
• /
• pp.42-51
• /
• 2019

Recently, the amount of internet traffic is increasing due to the increase in speed and capacity of the network environment, and protocol data is increasing due to mobile, IoT, application, and malicious behavior. Most of these private protocols are unknown in structure. For efficient network management and security, analysis of the structure of private protocols must be performed. Many protocol reverse engineering methodologies have been proposed for this purpose, but there are disadvantages to applying them. In this paper, we propose a methodology for inferring a detailed protocol structure based on network trace analysis by hierarchically combining CSP (Contiguous Sequential Pattern) and SP (Sequential Pattern) Algorithm. The proposed methodology is designed and implemented in a way that improves the preceeding study, A²PRE, We describe performance index for comparing methodologies and demonstrate the superiority of the proposed methodology through the example of HTTP, DNS protocol.

• Journal of Broadcast Engineering
• /
• v.25 no.2
• /
• pp.200-207
• /
• 2020

Recently, deep neural networks such as CNN are showing excellent performance in various fields such as image classification, object recognition, visual quality enhancement, etc. However, as the model size and computational complexity of deep learning models for most applications increases, it is hard to apply neural networks to IoT and mobile environments. Therefore, neural network compression algorithms for reducing the model size while keeping the performance have been being studied. In this paper, we apply few compression methods to CNN models and evaluate their performances in the embedded environment. For evaluate the performance, the classification performance and inference time of the original CNN models and the compressed CNN models on the image inputted by the camera are evaluated in the embedded board equipped with QCS605, which is a customized AI chip. In this paper, a few CNN models of MobileNetV2, ResNet50, and VGG-16 are compressed by applying the methods of pruning and matrix decomposition. The experimental results show that the compressed models give not only the model size reduction of 1.3~11.2 times at a classification performance loss of less than 2% compared to the original model, but also the inference time reduction of 1.2~2.21 times, and the memory reduction of 1.2~3.8 times in the embedded board.

• Journal of Convergence for Information Technology
• /
• v.11 no.4
• /
• pp.83-101
• /
• 2021

This study is to investigate, using AHP, what technologies should be applied first to Korean SMEs in order to respond to the 4th industrial revolution and change to a smart enterprise. To this end, technologies related to the 4th industrial revolution and smart factory are synthesized, and the classification criteria of Dae-Hoon Kim et al. (2019) are applied, but additional opinions of experts are collected and related technologies are converted to artificial intelligence (AI), Big Data, and Cloud Computing. As a base technology, mobile, Internet of Things (IoT), block chain as hyper-connected technology, unmanned transportation (autonomous driving), robot, 3D printing, drone as a convergence technology, smart manufacturing and logistics, smart healthcare, smart transportation and smart finance were classified as smart industrial technologies. As a result of confirming the priorities for technical use by AHP analysis and calculating the total weight, manufacturing companies have a high ranking in mobile, artificial intelligence (AI), big data, and robots, while service companies are in big data and robots, artificial intelligence (AI), and smart healthcare are ranked high, and in all companies, it is in the order of big data, artificial intelligence (AI), robot, and mobile. Through this study, it was clearly identified which technologies should be applied first in order to respond to the 4th industrial revolution and change to a smart company.

• Asian Journal of Innovation and Policy
• /
• v.12 no.1
• /
• pp.054-074
• /
• 2023

With the advent of the '4th Industrial Revolution', digitalization using AI (Artificial Intelligence), big data, IoT (Internet of Things), cloud computing and mobile is accelerating across all industries and global companies have fundamentally reorganized customer experiences, business models, and operations centering on digital transformation. Business innovation drives productivity improvement, process simplification, price, competitiveness and sustainable expansion. Whether digital transformation will be necessary for the current industrial environment is no longer important, and how quickly companies achieve digitalization has emerged as the utmost crucial element in industrial continuity. As non-face-to-face and remote technologies have begun in earnest, and accelerated in the pharmaceutical industry. They are looking for ways to provide value, generate profits, improve efficiency, and sustain the future. Compared to other industries, the pharmaceutical-related sectors have shown high interest in digital transformation especially to reduce costs and meet the challenge of delivering products during the pandemic environment.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.8 no.10
• /
• pp.1-9
• /
• 2018

The purpose of this exploratory study is to identify the mobile phone applications (apps) used by foreign tourists visiting South Korea through a pilot study using focus groups and individual interviews. Concentrating on tourist mobile app use in a smart tourism environment and categorized through a taxonomy of mobile applications lays the framework and determines the factors boosting tourism smartphone app trends by foreign tourists visiting South Korea. Researchers collected data through ethnographic methods and analyzed it through qualitative research to uncover major themes within the smart tourism app use phenomenon. The researchers coded, counted, analyzed, and then divided the findings gleaned from a pilot study and interviews into a taxonomy of seven logical smartphone app categories. The labeling and coding of all the data accounting for similarities and differences can be recognized and are logically discussed in the implications of the apps used by tourists to assist tourist destinations. More specifically these findings will assist smart tourism destinations by better understanding foreign tourist smartphone app use behavior. Tourists visiting South Korea interviewed in this study exhibited significant mastery of Internet of Things (IoT) technologies, craved free WiFi access, and utilized smartphone apps for all facets of their travel. Findings show major concentrations of app use in bookings of accommodations, tourist attractions, online shopping, navigation, wayfinding, augmented reality, information searching, language translation, gaming, and online dating while traveling in South Korea.

• Journal of IKEEE
• /
• v.19 no.4
• /
• pp.548-556
• /
• 2015

When the variety of personal health services are provided in the ICBM(IoT, Cloud, Bigdata, and Mobile) environment, the security requirements of personal health service(PHS) including privacy issues is proposed in this paper. Because it is expected that the services related to personal health are provided in the cloud environment, the security requirements of a cloud environment is firstly investigated and then security threats including direct and indirect threats in a cloud environment are analyzed in terms of the security of PHS. In addition, the security requirements of PHS is developed based on the security requirements of electronic medical record(EMR) for medical service in this paper, then the validity of the proposed security requirements is shown by the relation between security requirements of cloud environment and PHS to indicate that a security requriement is supported by several security requirements of PHS.

• Journal of the Korea Convergence Society
• /
• v.9 no.12
• /
• pp.61-68
• /
• 2018

As the smartphone and mobile environment develop, the time and space constraints for individual work performance are disappearing. Companies can reduce costs and expand their business quickly through cloud computing. As the use of various cloud expands, the boundaries of users, data, and applications are disappearing. Traditional security approaches based on boundaries (Perimeter) are losing their utility in the cloud environment. This paper describes the limitations of existing network access control (NAC) in a cloud environment and suggests network security technology that complements it. The study explains the SDP and combines SDP(Software Defined Perimeter) to overcome the limitations of NAC, while at the same time explaining its role as a new framework for supporting the cloud environment. The new framework proposed in this paper suggests a software-based network security solution that supports physical and software parts, providing identity-based access control, encrypted segment management, and dynamic policy management, not IP-based.