• Convergence Security Journal
• /
• v.19 no.5
• /
• pp.107-118
• /
• 2019

Based on the Internet of Things technology, one of the core technologies of the fourth industrial revolution, our Ministry of Defense is also pushing to establish M-IoT in defense area to improve management efficiency, innovate military culture and strengthen military power. However, devices connected to the Military Internet of Things can be easily exposed to various of cyber threats as most of them are developed and with a focus on improving sensing and communication skills that collect and transmit data. And it is not easy to uniquely identify the numerous heterogeneous devices, and to establish a secure communication channel between devices or between devices and management servers. In this paper, based on PUF technology, we propose a novel key management scheme that can uniquely identify the various devices, and generate the secret keys needed for the establishment of a secure communication channel using non-replicable information generated by the PUF. We also analyze the efficiency of our proposed scheme through comparison with existing key management scheme and verify the logic and security using BAN Logic.

• Information and Communications Magazine
• /
• v.34 no.3
• /
• pp.74-79
• /
• 2017

사물인터넷(Internet of Things, IoT) 기술의 발전에 따라 서비스 또한 다양해지고 있으며 실제 삶 속에 스며들어가고 있다. 이러한 사물인터넷 기술은 산업체에게 새로운 시장 창출의 기회를 제공하고 있고 사용자에게는 더욱 스마트한 삶을 영위할 수 있도록 해준다. 그러나 빠르게 증가하면서 연결되는 사물들에 보안 기술이 안전하게 적용되지 않을 경우 새로운 위협 요소가 된다. 본고에서는 미흡한 보안 설정으로 인해 야기되는 IoT 장치에 대한 보안 공격 동향과 이에 대응하기 위해 제안되는 안전한 초기 설정 방법들에 대해 알아본다.

• Journal of Dental Anesthesia and Pain Medicine
• /
• v.24 no.3
• /
• pp.223-225
• /
• 2024

• Journal of Integrative Natural Science
• /
• v.11 no.3
• /
• pp.148-153
• /
• 2018

In this paper, we propose a hybrid-recognition system to obtain the state information and control the Internet of Things (IoT) based smart devices using two recognitions. First, we use a facial recognition for checking the owner of the mobile devices, i.e., smartphones, tablet PCs, and so on, and obtaining the state information of the IoT based smart devices, i.e., smart cars, smart appliance, and so on, and then we use a fingerprint recognition to control them. Further, in the conventional system, the message of the state and control information between the mobile devices and smart devices is only exchanged through the cellar mobile network. Thus, we also propose a direct communication to reduce the total transmission time. In addition, we develop a testbed of the proposed system using smartphones, desktop computers, and Arduino vehicle as one of the smart devices. We evaluate the total transmission time between the conventional and direct communications and show that the direct communication with the proposed system has better performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.10a
• /
• pp.845-847
• /
• 2014

In recent years, the mobile OS market, enlargement and, at the same time, Android has mounted various smart phones and feature air conditioning, smart TV, cleaning robot, camera, etc. that the number is being spread at a rapid pace. But a lot of devices to control the modules and applications at once, this is not a device for controlling the dissemination of applications all in one place, and in charge of the devices that allow you to manage applications are lacking. Accordingly, in this paper, use the Web Server registered in the appliance can be controlled by management, Web access, is proposing and designing the system. This is the current research is actively in progress in the field of IoT (Internet of Things) would be utilized.

• The Journal of the Convergence on Culture Technology
• /
• v.5 no.2
• /
• pp.45-52
• /
• 2019

The human genome project decoded 99% of human genes for $ 3 billion by 1990-2003. However, as many studies on genes have progressed, it has become clear that there are many cases where diseases occur without structural alteration of genes. The latest study, Epigenetics, has come up with the answer to this problem. The famine that hit Jeju until 1670-1795, the ban on the exclusion of Jeju Island to the outside 200 years of suffering, and in 1948, one third of the citizens were killed by the 4.3 incident generate Epigenetic. It has been shown in the world history science that starving-stress can be manifested as obesity and disease in progeny due to hereditary phenomena. 5G-based healthcare IoT technology can be used for the treatment of obesity by enabling Epigenetic analysis of this phenomenon.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.1
• /
• pp.130-133
• /
• 2020

Smart pig farm which is based on IoT has been widely adopted by many pig farmers. In order to achieve optimal control of smart pig farm, the relation between environmental conditions and performance metric should be characterized. In this study, the relation between multiple environmental conditions including temperature, humidity and various performance metrics, which are daily gain, feed intake, and MSY, is analyzed based on data obtained from 55 real pig farm. Especially, based on preprocessing of data, various regression based machine learning algorithms are considered. Through performance evaluation, we show that the performance can be predicted with high precision, which can improve the efficiency of management.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.21 no.5
• /
• pp.1009-1015
• /
• 2017

Recently, the wide spread of IoT (Internet of Things) based technology enables the accumulation of big biometric data on livestock. The availability of big data allows the application of diverse machine learning based algorithm in the field of agriculture, which significantly enhances the productivity of farms. In this paper, we propose an abnormal livestock detection algorithm based on deep learning, which is the one of the most prominent machine learning algorithm. In our proposed scheme, the livestock are divided into two clusters which are normal and abnormal (disease) whose biometric data has different characteristics. Then a deep neural network is used to classify these two clusters based on the biometric data. By using our proposed scheme, the normal and abnormal livestock can be identified based on big biometric data, even though the detailed stochastic characteristics of biometric data are unknown, which is beneficial to prevent epidemic such as mouth-and-foot disease.