• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.4
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• pp.111-122
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• 2008

Web service is defined to support interoperable machine to machine interaction over a network and defined as distributed technologies. Recently in web service environment, security has become one of the most critical issues. An attacker may expose user privacy and service information without authentication. Furthermore, the users of web services must temporarily delegate some or all of their behalf. This results in the exposure of user privacy information by agents. We propose a delegation model for providing safety of web service and user privacy in ubiquitous computing environments. In order to provide safety of web service and user privacy, XML-based encryption and a digital signature mechanism need to be efficiently integrated. In this paper, we propose web service management server based on XACML, in order to manage services and policies of web service providers. For this purpose, we extend SAML to declare delegation assertions transferred to web service providers by delegation among agents.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.1
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• pp.343-364
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• 2021

In this study, as examples of domestic libraries currently using the cloud-based library system, the main characteristics and issues that appeared in the experience of use divided into the processes of introduction, conversion, and operation of each system were investigated, and the results are as follows. First, it is said that new systems were introduced as alternatives to problems caused by the operation of the existing system, and the current products were selected because they were cost-effective. Second, the main issues in the conversion process were data migration work, implementation of existing service functions, and linking problems of internal and external systems in the library. Third, the main advantages identified in the operation process were cost reduction, simple installation and automatic management and maintenance, and convenient use in mobile devices. The main drawbacks were the difficulty of customizing that reflects the characteristics of the library, and the need for stability of the network. The disappeared role of the information technology librarian is the regular system inspection and maintenance support, and various new roles have been suggested. The responses of librarians and users to the new system were generally satisfied rather than dissatisfied.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.850-858
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• 2022

To deploy Gate Recurrent Units (GRU) on resource-constrained embedded devices, this paper presents a reconfigurable FPGA-based GRU accelerator that enables structured compression. Firstly, a dense GRU model is significantly reduced in size by hybrid quantization and structured top-k pruning. Secondly, the energy consumption on external memory access is greatly reduced by the proposed reuse computing pattern. Finally, the accelerator can handle a structured sparse model that benefits from the algorithm-hardware co-design workflows. Moreover, inference tasks can be flexibly performed using all functional dimensions, sequence length, and number of layers. Implemented on the Intel DE1-SoC FPGA, the proposed accelerator achieves 45.01 GOPs in a structured sparse GRU network without batching. Compared to the implementation of CPU and GPU, low-cost FPGA accelerator achieves 57 and 30x improvements in latency, 300 and 23.44x improvements in energy efficiency, respectively. Thus, the proposed accelerator is utilized as an early study of real-time embedded applications, demonstrating the potential for further development in the future.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.3
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• pp.157-164
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• 2022

In this paper, we describe how to implement the mountainous terrain, radar, and air defense network for UAV path planning in a 3-D environment, and perform path planning and re-planning using the PRM algorithm, a sampling-based path planning algorithm. In the case of the original PRM algorithm, the calculation to check whether there is an obstacle between the nodes is performed 1:1 between nodes and is performed continuously, so the amount of calculation is greatly affected by the number of nodes or the linked distance between nodes. To improve this part, the proposed LineGridMask method simplifies the method of checking whether obstacles exist, and reduces the calculation time of the path planning through parallelization. Finally, comparing performance with existing PRM algorithms confirmed that computational time was reduced by up to 88% in path planning and up to 94% in re-planning.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.87-93
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• 2022

Since 99% of PCs operating in the defense domain use the Windows operating system, detection and response of Window-based malware is very important to keep the defense cyberspace safe. This paper proposes a model capable of detecting malware in a Windows PE (Portable Executable) format. The detection model was designed with an emphasis on rapid update of the training model to efficiently cope with rapidly increasing malware rather than the detection accuracy. Therefore, in order to improve the training speed, the detection model was designed based on a Bidirectional LSTM (Long Short Term Memory) network that can detect malware with minimal sequence data without complicated pre-processing. The experiment was conducted using the EMBER2018 dataset, As a result of training the model with feature sets consisting of three type of sequence data(Byte-Entropy Histogram, Byte Histogram, and String Distribution), accuracy of 90.79% was achieved. Meanwhile, it was confirmed that the training time was shortened to 1/4 compared to the existing detection model, enabling rapid update of the detection model to respond to new types of malware on the surge.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.705-710
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• 2021

Nowadays, cutting-edge information communication technology is the genuine core technology of the fourth Industrial Revolution and is still making great progress rapidly among various technology fields. The biggest issue in ICT fields is the machine learning based Artificial Intelligence applications using big data in cloud computing environment on the basis of wireless network, and also the technology fields of autonomous control applications such as Autonomous Car or Mobile Robot. Since value of the high-tech ICT technology depends on the surrounded environmental factors and is very flexible, the precise technology valuation method is urgently needed in order to get successful technology transfer, transaction and commercialization. In this research, we analyze the characteristics of the high-tech ICT technology and the main factors in technology transfer or commercialization process, and propose the precise technology valuation method that reflects the characteristics of the ICT technology through phased analysis of the existing technology valuationmodel.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.1-6
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• 2022

This paper presents a regionalized time slotted channel hopping (TSCH) slotframe-based aerial data collection using wake-up radio. The proposed scheme aims to minimize the delay and energy consumption when an unmanned aerial vehicle (UAV) collects data from sensor devices in the large-scale service area. To this end, the proposed scheme divides the service area into multiple regions, and determines the TSCH slotframe length for each region according to the number of cells required by sensor devices in each region. Then, it allocates the cells dedicated for data transmission to the TSCH slotframe using the ID of each sensor device. For energy-efficient data collection, the sensor devices use a wake-up radio. Specifically, the sensor devices use a wake-up radio to activate a network interface only in the cells allocated for beacon reception and data transmission. The simulation results showed that the proposed scheme exhibited better performance in terms of delay and energy consumption compared to the existing scheme.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.125-135
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• 2022

This study aims to explore variables using machine learning and provide analysis techniques suitable for predicting pharmacy sales whether government statistical indicators built to create an industrial ecosystem based on data, network, and artificial intelligence affect pharmacy sales. Therefore, this study explored predictive variables and performance through machine learning techniques such as Random Forest, XGBoost, LightGBM, and CatBoost using analysis data from January 2016 to December 2021 for 28 government statistical indicators and pharmacies in the retail sector. As a result of the analysis, economic sentiment index, economic accompanying index circulation change, and consumer sentiment index, which are economic indicators, were found to be important variables affecting pharmacy sales. As a result of examining the indicators MAE, MSE, and RMSE for regression performance, random forests showed the best performance than XGBoost, LightGBM, and CatBoost. Therefore, this study presented variables and optimal machine learning techniques that affect pharmacy sales based on machine learning results, and proposed several implications and follow-up studies.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.95-107
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• 2022

With the rapid development of Internet of Things sensor devices and big data processing techniques, Internet of Things sensor-based information systems have been applied in various industries. Depending on the industry in which the information systems are applied, the accuracy of the information derived can affect the industry's efficiency and safety. Therefore, security techniques that protect sensing data from security attacks and enable information systems to derive accurate information are essential. In this paper, we examine security threats targeting each processing step of an Internet of Things sensor-based information system and propose security mechanisms for each security threat. Furthermore, we present an Internet of Things sensor-based information system structure that is robust to security attacks by integrating the proposed security mechanisms. In the proposed system, by applying lightweight security techniques such as a lightweight encryption algorithm and obfuscation-based data validation, security can be secured with minimal processing delay even in low-power and low-performance IoT sensor devices. Finally, we demonstrate the feasibility of the proposed system by implementing and performance evaluating each security mechanism.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.83-88
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• 2022

Internet of Things (hereinafter referred to as IoT) related technologies are continuously developing in line with the recent development of information and communication technologies. IoT system sends and receives unique data through network based on various sensors. Data generated by IoT systems can be defined as big data in that they occur in real time, and that the amount is proportional to the amount of sensors installed. Until now, IoT systems have applied data storage, processing and computation through centralized processing methods. However, existing centralized processing servers can be under load due to bottlenecks if the deployment grows in size and a large amount of sensors are used. Therefore, in this paper, we propose a distributed processing system for applying a data importance-based algorithm aimed at the high availability of the system to efficiently handle real-time sensor data arising in IoT environments.