• Journal of Service Research and Studies
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• v.5 no.2
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• pp.111-118
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• 2015

Although the development of mobile devices are made us a free life, they were displayed the subject of this financial crime and attacking forces in the other side. Among finance-related crime is become a serious crime that are targeting smartphones by SMS phishing, phishing, pharming, voice phishing etc. In particular, SMS phishing is increased according to phenomenon using the nature of a text message in the mobile. SMS phishing is become new crime due to the burden to the smartphone user. Their crime is also the advanced way from the existing fraud, such as making the malicious apps. Especially it generates loopholes in the law by a method such as using a foreign server. For safe from SMS phishing attacks, proactive pre-diagnosis is even more important rather than post responses. It is necessary to deploy blocking programs for detecting SMS phishing attacks in advance to do this. In this paper we are investigating the process of block types and block apps that are currently deployed and presenting the evaluation of the application of the detection block setting app.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.161-168
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• 2019

Recently, video equipments such as CCTV, which is spreading rapidly, is being used as a means to monitor and cope with abnormal situations in almost governments, companies, and households. However, in most cases, since recognizing the abnormal situation is carried out by the monitoring person, the immediate response is difficult and is used only for post-analysis. In this paper, we present the results of the development of video surveillance system that automatically recognizing the abnormal situations and sending such events to the smartphone immediately using the latest deep learning technology. The proposed system extracts skeletons from the human objects in real time using Openpose library and then recognizes the human behaviors automatically using deep learning technology. To this end, we reconstruct Openpose library, which developed in the Caffe framework, on Darknet framework to improve real-time processing. We also verified the performance improvement through experiments. The system to be introduced in this paper has accurate and fast behavioral recognition performance and scalability, so it is expected that it can be used for video surveillance systems for various applications.

• Journal of Industrial Convergence
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• v.20 no.9
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• pp.59-70
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• 2022

Background: Diabetes education is an important factor in blood glucose control. Reinforced education is necessary for effective diabetes education. However, it is difficult to provide reinforced diabetes education within Korea's medical environment. Therefore, we want to analyze the effect of continuous diabetes education using mobile health care that can effectively provide repeated education without having to face the patient. Methods: This study is a multicenter, randomized, controlled, pre-post design study conducted to analyze the effect of a continuous diabetes education method. A total of 109 people were registered at five hospitals in south Korea, and they were randomly assigned to the app group (34 people) who received real-time coaching and repetitive training, the logbook group (37 people) who received face-to-face training after writing a blood glucose logbook, and the general group (38 people) who received a one-time diabetes education. The study was conducted for a total of 24 weeks. Twenty-one patients withdrew their consent and failed to perform an HbA1c. A final 88 patients were analyzed. The difference in HbA1c, Self-management behavior, and Quality of life before and after education was analyzed. Results: The study involved 51 (58%) male subjects, mean age was 55.8 years and mean duration of diabetes was 7.6 years. After 24 weeks of intervention, there was no significant difference in self-care behavior and quality of life between the three groups, but the HbA1c of the app group significantly decreased after education compared to the logbook group and the general group (F=4.62, p=.013). Conclusion: It can be seen through the app group that receiving real-time education is more effective in improving blood glucose management and continuous diabetes education is important.