• The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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• v.24 no.6
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• pp.649-663
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• 1995

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.895-896
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• 2015

With the development of sensor, wireless mobile communication, embedded system and cloud computing, the technologies of Internet of Things have been widely used in logistics, Smart devices security, intelligent building and o on. Bridging between wireless sensor networks with traditional communication networks or Internet, IoT gateway plays n important role in IoT applications, which facilitates the integration of wireless sensor networks and mobile communication networks or Internet, and the management and control with wireless sensor networks. The IoT Gateway is a key component in IoT application systems but It has lot of security issues. We analyzed the trends of security and privacy matters.

• Convergence Security Journal
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• v.16 no.3_1
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• pp.87-98
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• 2016

As the informative society becomes intensified, the rise of the convergence security offers an alternative strategic correspondence to the technology leaks that are becoming more advanced, complex, and intelligent. In order to the convergence security to provide its efficacy, training convergence security specialists is essential. However, research on the subject has yet to be considered sufficient. Thus this research focuses on defense industry security specialists to define the duty and analze critical task as well as drawn and therefore the required academic level of the critical task was examined. These research work contributes to the competence development of convergence security specialists and further enhancement on convergence security training process of academic institutions and job training institutions.

• Convergence Security Journal
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• v.19 no.4
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• pp.143-150
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• 2019

Recently, As ICT technology develops, cyber attacks are becoming more intelligent and advanced. In order to cope with such cyber attacks, the security control system must be maintained 24 hours a day, 365 days a year. Security personnel should be able to respond in real time to cyber attacks through shift work for 24 hours, but the workforce law was revised in 2018 to affect manpower and security control work systems. Therefore, in this paper, we propose an effective security control work system by reducing 52 working hours per week.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.127-133
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• 2016

In this paper, an intelligent dimming control system is designed and implemented with the human visual response function using CDS sensor, PIR sensor and temperature sensor, etc. The proposed system is designed to detect a moving object by PIR sensor and to control the LED dimming considering the human visual response. Also, the dimming of LED light can modulate on the app, and simultaneously control dimming in real-world environments with smart phone app. A high-temperature warning or a fire hazard information is transmitted to user's smart phone according to sensor values and Data graph are provided as part of data visualization. Connecting the hardware controller, the proposed intelligent smart dimming control system is expected to contribute to the power reduction interior LED, smart grid building and saving home combining with internet of things.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.628-631
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• 2003

In this paper, we present real-time, accurate face region detection and tracking technique for an intelligent surveillance system. It is very important to obtain the high-resolution images, which enables accurate identification of an object-of-interest. Conventional surveillance or security systems, however, usually provide poor image quality because they use one or more fixed cameras and keep recording scenes without any cine. We implemented a real-time surveillance system that tracks a moving person using four pan-tilt-zoom (PTZ) cameras. While tracking, the region-of-interest (ROI) can be obtained by using a low-pass filter and background subtraction. Color information in the ROI is updated to extract features for optimal tracking and zooming. The experiment with real human faces showed highly acceptable results in the sense of both accuracy and computational efficiency.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.255-260
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• 2013

Nowadays, the intelligent education system has been studied using the self-directed learning ability. It can connect to the online virtual university and it is based on web technology that can be accessed anywhere anyplace. In order to implement the intelligent tutoring system, the student's weak and strong subjects must be first determined in real time, it proposed level learning capabilities and security algorithms in this paper. Moreover, in this paper, to implement the intelligent education tutoring system it proposed qr code and student level learning simulation.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.3
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• pp.267-276
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• 2020

Threats targeting cyberspace are becoming more intelligent and increasing day by day. To cope with such cyber threats, it is essential to improve the coping ability of system security officers. In this paper, we propose a stateful traffic generator that provide network background traffic for cyber warfare training. The proposed architecture is designed for generating traffic similar to real system traffic, so the trainee can perform more realistic training.

• Electronics and Telecommunications Trends
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• v.36 no.2
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• pp.12-21
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• 2021

Intelligent radar sensors are applied in many industries, such as the automobile, aerospace, and defense industries (for security and surveillance), and for traffic monitoring and management as well as environmental and weather monitoring. Furthermore, they are used in smart cities, homes, and buildings, wherein intelligent motion sensing is required in daily life. It is mentioned that it is being used. In addition, ETRI introduces a phased array-based intelligent radar for drone detection and a human name detection radar technology based on which humans can be detected in case of a disaster.

• Journal of Korea Multimedia Society
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• v.23 no.5
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• pp.641-649
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• 2020

As the usage of mobile devices extremely increases, malicious mobile apps(applications) that target mobile users are also increasing. It is challenging to detect these malicious apps using traditional malware detection techniques due to intelligence of today's attack mechanisms. Deep learning (DL) is an alternative technique of traditional signature and rule-based anomaly detection techniques and thus have actively been used in numerous recent studies on malware detection. In order to develop DL-based defense mechanisms against intelligent malicious apps, feeding recent datasets into DL models is important. In this paper, we develop a DL-based model for detecting intelligent malicious apps using KU-CISC 2018-Android, the most up-to-date dataset consisting of benign and malicious Android apps. This dataset has hardly been addressed in other studies so far. We extract OPcode sequences from the Android apps and preprocess the OPcode sequences using an N-gram model. We then feed the preprocessed data into LSTM and apply the concept of Information Gain to improve performance of detecting malicious apps. Furthermore, we evaluate our model with numerous scenarios in order to verify the model's design and performance.