• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.2
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• pp.439-448
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• 2015

IoT (Internet of Things) propels current networked communities into a advanced hyper-connected society/world where uniquely identifiable embedded computing devices are associated with the existing internet infrastructure. Therefore, the IoT services go beyond mere M2M (Machine-to-Machine communications) and should be able to empower users with more flexible communication capabilities over protocols, domains, and applications. In addition, The access control in IoT need a differentiated methods from the traditional access control to increase a security and dependability. In this paper, we describe implementation and design of the capability token based system for secure access control in IoT environments. In the proposed system, Authorities are symbolized into concepts of the capability tokens, and the access control systems manage the tokens, creation, (re)delegation and revocation. The proposed system is expected to decrease the process time of access control by using capability tokens.

• Smart Media Journal
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• v.9 no.3
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• pp.41-45
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• 2020

Recently, artificial intelligence (AI) and the Internet of things (IoT), which are represented by machine learning and deep learning among IT technologies related to the Fourth Industrial Revolution, are applied to our real life in various fields through various researches. In this paper, IoT and AI using object recognition technology are applied to classify clothing. For this purpose, the image dataset was taken using webcam and raspberry pi, and GoogLeNet, a convolutional neural network artificial intelligence network, was applied to transfer the photographed image data. The clothing image dataset was classified into two categories (shirtwaist, trousers): 900 clean images, 900 loss images, and total 1800 images. The classification measurement results showed that the accuracy of the clean clothing image was about 97.78%. In conclusion, the study confirmed the applicability of other objects using artificial intelligence networks on the Internet of Things based platform through the measurement results and the supplementation of more image data in the future.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.65-72
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• 2016

This study built the theoretical frameworks for empirical analysis based on the analysis of the relationship among the concepts of risk of information privacy, the experience of information privacy, the policy of information privacy and information control via the provision intention studies. Also, in order to analyze the relationship among the factors such as the risk of information privacy, intention to offer the personal information, this study investigated the concepts of information privacy and studies related with the privacy, established a research model about the information privacy. Followings are the results of this study: First, the information privacy risk, information privacy experience, information privacy policy, and information control have positive effects upon the information privacy concern. Second, the information privacy concern has the negative effects upon the provision intention of personal information.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.1
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• pp.29-37
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• 2020

Work to improve network throughput has been focused on network coding as the utilization of IoT-based application services increases and network usage increases rapidly. In network coding, nodes transform packets received from neighboring nodes into a combination of encoded packets for transmission and decoding at the destination. This scheme is based on trust among nodes, but in the IoT environment where nodes are free to join, a malicious node can fabricate the packet if it legally participates in the configuration. It is difficult to identify the authenticity of the encoded packet since the packet received at destination is not a single source but a combination of packets generated by several nodes. In this paper, we propose a method to detect "look-like-valid" packets that have been attacked and disguised in packets received at destination, and to identify valid messages in the reconstructions. This method shows that network coding performance is significantly improved because the destination can reconstruct a valid message with only received packets without retransmission with a high probability, despite the presence of disguised packets.

• Journal of Digital Contents Society
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• v.19 no.2
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• pp.377-383
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• 2018

Internet of Things (IoT) is producing various data as the smart environment comes. The IoT data collection is used as important data to judge systems's status. Therefore, it is important to monitor the anomaly state of the sensor in real-time and to detect anomaly data. However, it is necessary to convert the IoT data into a normalized data structure for anomaly detection because of the variety of data structures and protocols. Thus, we can expect a good quality effect such as accurate analysis data quality and service quality. In this paper, we propose an anomaly detection system based on big data from collected sensor data. The proposed system is applied to ensure anomaly detection and keep data quality. In addition, we applied the machine learning model of support vector machine using anomaly detection based on time-series data. As a result, machine learning using preprocessed data was able to accurately detect and predict anomaly.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.74-79
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• 2016

The Seoul Metropolitan Subway, which started operating in 1974, plays a major role in transporting 7,289 thousands passengers daily. This trend of a steadily increase in passengers from 2012 has increased the congestion rate because of the limited capacity and time. To solve this problem, Seoul city is consistently working on improving the subway facilities, such as the construction of a detour path. This project, however, has only a slight effect on improving the congestion rate and is too expensive to construct the facilities. Hence, this study suggests The Congestion Standardization System based on the IoT for improving the subway congestion rate. Based on the system, the expected effect analysis was performed, which resulted in a decrease in ride passengers from 34 to 20. In addition, this expected effect analysis shows that the number of subway vehicles can increase from 20 to 24. The suggested system will have a significant effect on the efficiency of the management system.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.5
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• pp.91-102
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• 2020

The Internet of Things (IoT) is characterized as the market where various companies compete for the same consumers. Thus, there are differences in functions and performance provided by the main business area and other characteristics of the service providers. This paper investigates whether satisfaction with the service provided depends on the characteristics of the operator by using sentiment analysis of comments. To achieve this goal, word importance analysis and sensitivity analysis are conducted on 34,310 reviews of 41 applications registered in the Google Play. The review analysis was conducted at various levels, including TD-IDF (Term frequency-inverse document frequency) value of keywords, service sectors, the origin of providers, and domestic/foreign providers. The results show that users' overall assessment of IoT services was found to be low, and smart homes received relatively high reviews compared to other services, and manufacturing-based and overseas providers received relatively higher evaluations than others.

• Journal of Advanced Navigation Technology
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• v.25 no.5
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• pp.390-396
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• 2021

In this research, design and fabrication of marine repeater capable to extend communication coverage in monitoring system of fishing gear automatic identification, which is one of implementation method of the real-name electric fishing gear system declared by Ministry of Oceans and Fisheries in 2016, is reported. The proposed marine repeater is fabricated in a form of RF repeater with interference cancellation system (ICS), which can cancel the oscillation due to feedback signal between service antenna and link antenna. In design process, we secure the isolation of 30 dB between service antenna and link antenna. It is confirmed that when the level of feedback signal into repeater input be lower of 15 dB than repeater gain, error vector magnitude due to oscillation can be lower than the performance criterion of 6%, from the test verification. It is expected that the service coverage will be extended by applying the developed marine ICS RF repeater into marine IoT network including monitoring system of fishing gear automatic identification.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.61-73
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• 2020

Real-time location-sensing technology using location information collected from IoT devices is being applied for safety management purposes in many industries, such as ports. On the other hand, positional error is always present owing to the characteristics of GPS. Therefore, accident-risk detection algorithms must consider positional error. This paper proposes an methodology of calibration for falling object accident-risk-zone approach detection algorithm considering GPS errors. A probability density function was estimated, with positional error data collected from IoT devices as a probability variable. As a result of the verification, the algorithm showed a detection accuracy of 93% and 77%. Overall, the analysis results derived according to the GPS error level will be an important criterion for upgrading algorithms and real-time risk managements in the future.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.3
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• pp.83-90
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• 2022

Diabetes is a common disease today, and there are also many cases of developing into serious complications called Diabetic Foot Ulcers(DFU). Diagnosis and prevention of DFU in advance is an important task, and this paper proposes the method. Based on existing studies introduced in the paper, it can be seen that foot pressure and temperature information are deeply correlated with DFU. Introduce the process and architecture of SmarTinsole, an IoT device that measures these indicators. Also, the paper describes the preprocessing process for AI-based diagnosis of DFU. Through the comparison of the measured pressure graph and the actual human step distribution, it presents the results that multiple information collected in real-time from SmarTinsole are more efficient and reliable than the previous study.