• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.149-162
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• 2021

This paper established a new smart factory based on manufacturing data for an introductory company focusing on the personalized cosmetics manufacturing industry. We build on an example of a system that collects, manages, and analyzes documents and data that were previously managed by CGMP-based analog for data-driven use. To this end, we have established a system that can collect all data in real time at the production site by introducing artificial intelligence smart factory platform LINK5 MOS and POP system, collecting PLC data, and introducing monitoring system and pin board. It also aims to create a new business cluster space based on this project.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.77-82
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• 2020

As Korea enters an aging age, social efforts to improve the IADL of the elderly are increasing. In this study, to improve the performance of financial management activities that the elderly is particularly burdened, we aim to learn the elderly through ATM simulation education contents so that they can use ATM smoothly. To this end, interviews were conducted with seniors to derive four major financial activities (deposits, withdrawals, deposit inquiries and bank account arrangements), and developed tablet PC-based ATM education contents identical to the existing bank ATM interfaces. The experiment was conducted on 20 elderly people in the Elderly Day Care Center, and their satisfaction, fatigue and performance were measured before and after education. The results of this study can provide ATM design guidelines for the elderly who have difficulty using ATM.

• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.21-30
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• 2021

With the development of IoT technology, various cloud computing-based services such as smart cars, smart healthcare, smart homes, and smart farms are expanding. With the advent of a new environment, various problems continue to occur, such as the possibility of exposure of important information such as personal information or company secrets, financial damage cases due to hacking, and human casualties due to malicious attack techniques. In this paper, we propose a message communication protocol for smart home-based secure communication and user data protection. As a detailed process, secure device registration, message authentication protocol, and renewal protocol were newly designed in the smart home environment. By referring to the security requirements related to the smart home service, the stability of the representative attack technique was verified, and as a result of performing a comparative analysis of the performance, the efficiency of about 50% in the communication aspect and 25% in the signature verification aspect was confirmed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1043-1052
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• 2020

Signature-based malicious code detection methods share a common limitation; it is very hard to detect modified malicious codes or new malware utilizing zero-day vulnerabilities. To overcome this limitation, many studies are actively carried out to classify malicious codes using N-gram. Although they can detect malicious codes with high accuracy, it is difficult to identify malicious codes that uses very short codes such as Spectre. We propose a function level N-gram comparison algorithm to effectively identify the Spectre binary. To test the validity of this algorithm, we built N-gram data sets from 165 normal binaries and 25 malignant binaries. When we used Random Forest models, the model performance experiments identified Spectre malicious functions with 99.99% accuracy and its f1-score was 92%.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1141-1149
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• 2020

Most of the industrial control network is an independent closed network, which is operated for a long time after installation, and thus the OS is not updated, so security threats increase and security vulnerabilities exist. The zero-day attack defense must be applied with the latest patch, but in a large-scale industrial network, it requires a higher level of real-time and non-disruptive operation due to the direct handling of physical devices, so a step-by-step approach is required to apply it to a live system. In order to solve this problem, utility-specific patch impact assessment is required for reliable patch application. In this paper, we propose a method to test and safely install the patch using the regression analysis technique and show the proven results. As a patch impact evaluation methodology, the maximum allowance for determining the safety of a patch was derived by classifying test types based on system-specific functions, performance, and behavior before and after applying the patch. Finally, we report the results of case studies applied directly to industrial control networks, the OS patch has been updated while ensuring 99.99% availability.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.135-144
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• 2020

In graph theory, the least-cost path is discovered by searching the shortest path between a start node and destination node. The least cost is calculated as a one-dimensional value that represents the difference in distance or price between two nodes, and the nodes and edges that comprise the lowest sum of costs between the linked nodes is the shortest path. However, it is difficult to determine the shortest path if each node has multiple attributes because the number of cost types that can appear is equal to the number of attributes. In this paper, a shortest path search scheme is proposed that considers multiple attributes using the Euclidean distance to satisfy various user requirements. In simulation, we discovered that the shortest path calculated using one-dimensional values differs from that calculated using the Euclidean distance for two-dimensional attributes. The user's preferences are reflected in multi attributes and it was different from one-dimensional attribute. Consequently, user requirements could be satisfied simultaneously by considering multiple attributes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.600-608
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• 2020

Machine learning constructs an objective function from learning data, and predicts the result of the data generated by checking the objective function through test data. In machine learning, input data is subjected to a normalisation process through a preprocessing. In the case of numerical data, normalization is standardized by using the average and standard deviation of the input data. In the case of nominal data, which is non-numerical data, it is converted into a one-hot code form. However, this preprocessing alone cannot solve the problem. For this reason, we propose a method that uses ontology to normalize input data in this paper. The test data for this uses the received signal strength indicator (RSSI) value of the Wi-Fi device collected from the mobile device. These data are solved through ontology because they includes noise and heterogeneous problems.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.100-109
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• 2021

Flooding usually brings in disruptions and aggravated congestions to the roadway network. Hence, right information should be provided to road users to avoid the flood-impacted areas and for city officials to recover the network. However, the information about individual link congestion may not be conveyed to roadway users and city officials because too many links are congested at the same time. Therefore, more significant information may be desired, especially in a disastrous situation. This information may include 1) which places to avoid during flooding 2) which places are feasible to drive avoiding flooding. Hence, this paper aims to develop a framework to identify the flood-impacted areas in a roadway network and their criticality. Various impacted clusters and their spatiotemporal properties were identified with field data. From this data, roadway users can reroute their trips, and city officials can take the right actions to recover the affected areas. The information resulting from the developed framework would be significant enough for roadway users and city officials to cope with flooding.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.1
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• pp.1-7
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• 2022

It has been found through physiological experiments that the visual neurons constituting the human visual cortex do not respond to all visual stimuli, but to a visual stimuli with specific conditions. In order to interpret such physiological experiments, a model that can simulate the firing characteristics of neurons including a linear filter with random gain was proposed. It has been proven through experiments that subspaces are formed. To verify the validity of the implemented model, the distribution of values for two pixels randomly extracted from four different visual stimulus data was observed. The difference between the two distributions was confirmed by extracting the central coordinate value, that is, the coordinate value with the most values, from the distribution of the total stimulus data and the spike ignition stimulus data. In the case of the entire set, it was verified through experiments that the stimulus data generating spikes is a subset or subspace of the entire stimulus data. This study can be used as a basic study related to the mechanism of spikes in response to visual stimuli.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1323-1328
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• 2021

In this paper, we present a medical electric scooter sharing platform for the transportation vulnerable who are experiencing difficulties and inconveniences in moving. The proposed medical electric scooter sharing platform for the transportation vulnerable includes basic mobile rental, return, and functions that incorporate the IOT technology of the currently operating personal mobility sharing platform. The safety function has been strengthened. The medical electric scooter sharing platform for the transportation vulnerable stores driving data on the server in real time through GPS, and strengthens the alarm and call function in advance of an accident to enable rapid SOS processing. By making the quick contact and responding to the situation, people with disabilities can drive safely and comfortably.