• Informatization Policy
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• v.21 no.2
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• pp.24-48
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• 2014

Smart working, along with the spread of smart device use, has recently garnered increased interest. The issue has become focused on low labor productivity over working time, work-life balance and social discussion. There has also been a shift in working styles due to the development of mobile, security, and cloud computing-related IT technology support and activation of the smart work environment. However, former research show concern that smart working may not meet the initially expected levels of productivity. This empirical study was carried out to introduce the impact of teleworking on increased productivity and satisfaction in companies and public institutions through user interviews, a socio-technical systems approach and surveys. To summarize the results of this study, 'Telework satisfaction' is directly influenced by 'Work-life balance', 'Telework-system fit, and 'Telework-job fit'. Direct impact factors of 'Telework productivity'are 'Telework-job fit', 'Telework satisfaction', and 'Telework environment quality'.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1152-1157
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• 2021

This paper proposes a face recognition method for access control of apartment building. Different from most existing face recognition methods, the proposed one does not require any manual process for face enrollment. When a person is exiting through the main entrance door, his/her face data (i.e., face image and face feature) are automatically extracted from the captured video and registered in the database. When the person needs to enter the building again, the face data are extracted and the corresponding face feature is compared with the face features registered in the database. If a matching person exists, the entrance door opens and his/her access is allowed. The face data of the matching person are immediately deleted and the database has the latest face data of outgoing person. Thus, a higher recognition accuracy could be expected. To verify the feasibility of the proposed method, Python based face recognition has been implemented and the cloud service provided by a web portal.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.3
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• pp.503-509
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• 2019

Order-revealing encryption which enables a range query over encrypted data is attracting attention as one of the important security technologies in industry such as IoT, smart manufacturing, and cloud computing. In 2015, an ideally-secure order-revealing encryption whose ciphertexts reveal no additional information beyond the order of the underlying plaintexts has been proposed. However, their construction is too inefficient for practical use and some security analysis of multilinear maps, which their construction relies on, have been proposed. Recently, more practical schemes have been proposed, focusing on achieving practically usable efficiency rather than the ideal security. In this paper, we propose a more storage-efficient order-revealing encryption scheme than the Lewi et al.'s scheme most recently published by presenting an idea that can generate shorter ciphertexts without any security loss.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1384-1389
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• 2020

Although the fintech industry is developing rapidly around the world, the domestic development situation is rather slow compared to the speed. Therefore, the future development direction can be set by analyzing the current status of the fintech industry in order to suggest the direction of development in the domestic fintech industry. The main services provided by companies belonging to the domestic fintech industry are in the areas of remittance settlement, financial investment, asset management, crowdfunding, P2P finance, overseas remittance, fintech SI, insurtech, virtual currency, security, and authentication. It is divided into. This study identifies the main technologies used in the service and grasps the current domestic status. In addition, it analyzes the distribution of workers by each service. This study is expected to play an important role in the development of the financial industry through technical analysis of fintech companies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1688-1696
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• 2020

The paradigm of Internet-of-things(IoT) systems is changing from a cloud-based system to an edge-based system to solve delays caused by network congestion, server overload and security issues due to data transmission. However, edge-based IoT systems have fatal weaknesses such as lack of performance and flexibility due to various limitations. To improve performance, application-specific hardware can be implemented in the edge device, but performance cannot be improved except for specific applications due to a fixed function. This paper introduces a edge-centric metamorphic IoT(mIoT) platform that can use a variety of hardware through on-demand partial reconfiguration despite the limited hardware resources of the edge device, so we can increase the performance and flexibility of the edge device. According to the experimental results, the edge-centric mIoT platform that executes the reconfiguration algorithm at the edge was able to reduce the number of server accesses by up to 82.2% compared to previous studies in which the reconfiguration algorithm was executed on the server.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.135-143
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• 2022

As the world has implemented social distancing and telecommuting due to the spread of COVID-19, real-time streaming sessions based on routing protocols have increased dependence on the Internet due to the activation of video and voice-related content services and cloud computing. BGP is the most widely used routing protocol, and although many studies continue to improve security, there is a lack of visual analysis to determine the real-time nature of analysis and the mis-detection of algorithms. In this paper, we analyze BGP data, which are powdered as normal and abnormal, on a real-world basis, using an anomaly detection algorithm that combines statistical and post-processing statistical techniques with Rule-based techniques. In addition, we present an interactive spatio-temporal analysis plan as an intuitive visualization plan and analysis result of the algorithm with a map and Sankey Chart-based visualization technique.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.267-277
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• 2022

Due to the increasing proportion of cloud and remote working environments, various information security incidents are occurring. Insider threats have emerged as a major issue, with cases in which corporate insiders attempting to leak confidential data by accessing it remotely. In response, insider threat detection approaches based on machine learning have been developed. However, existing machine learning methods used to detect insider threats do not take biases and variances into account, which leads to limited performance. In this paper, boosting-type ensemble learning algorithms are applied to verify the performance of malicious insider detection, conduct a close analysis, and even consider the imbalance in datasets to determine the final result. Through experiments, we show that using ensemble learning achieves similar or higher accuracy to other existing malicious insider detection approaches while considering bias-variance tradeoff. The experimental results show that ensemble learning using bagging and boosting methods reached an accuracy of over 98%, which improves malicious insider detection performance by 5.62% compared to the average accuracy of single learning models used.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.2
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• pp.47-60
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• 2023

This study proposed to adopt consortium blockchain for the database in the research support system of national R&D projects in order to increase efficiency, to reduce administrative burden, and to promote transparent research environment focusing on servicing researchers. Specifically, storage methods were classified according to data characteristics. First, data that requires integrity and transparency is stored in the blockchain, Second, confidentiality and data that require modification and deletion are stored in the database, Third, data that requires confidentiality, integrity, and transparency at the same time stores the original in the database, and the hash value of the data is separately stored in the blockchain. If research support system adopts blockchain, it is possible to operate the system stably, to share quick exchange of information between research institutes, to reduce administrative burden, to improve transparency of process, to resolve asymmetry of information, and to secure integrity, confidentiality, and availability of data.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.165-172
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• 2024

In this paper, we designed a smart home system that can be used intuitively and easily in everyday life, such as sending text messages to users, providing various information and scheduling using smart AI, and providing lighting and atmosphere suitable for the atmosphere in situations such as listening to music using neopixels, as well as using ESP32, RFID, and Google Cloude Console using raspberry pie. As a result of the experiment, it was confirmed that security characters were normally sent to users when RFID was recognized on ESP32 connected to Wi-Fi even if the power was reconnected, and smart AI using Neopixel lighting, Raspberry Pie, and voice recognition, which calculated frequency, also changed the recognition rate over distance, but it worked.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.49-59
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• 2017

Smart sensing plays a key role in a variety of IoT applications, and its importance is growing more and more together with the development of artificial intelligence. Therefore the importance of smart sensors cannot be overemphasized. However, most studies related to smart sensors have been focusing on specific application purposes, for example, security, energy saving, monitoring, and there are not much effort on researches on how to efficiently configure various types of smart sensors to be needed in the future. In this paper, a component-based framework with hierarchical structure for efficient construction of smart sensor is proposed and its application to smart home is designed and implemented. The proposed method shows that various types of smart sensors to be appeared in the near future can be configured through the design and development of necessary components within the proposed software framework. In addition, since it has a layered architecture, the configuration of the smart sensor can be expanded by inserting the internal or external layers. In particular, it is possible to independently design the internal and external modules when designing an IoT application service through connection with the external device layer. A small-scale smart home system is designed and implemented using the proposed method, and a home cloud operating as an external layer, is further designed to accommodate and manage multiple smart homes. By developing and thus adding the components of each layer, it will be possible to efficiently extend the range of applications such as smart cars, smart buildings, smart factories an so on.