• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.5
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• pp.1211-1221
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• 2016

In IoT environment, making sure of trust of IoT devices is the most important one than others. The security threats of nowadays almost stay at exposure or tampering of information. However, if human life is strongly connected to the Internet by IoT devices, the security threats will probably target human directly. In case of devices, authentication is verified using the device-known private key. However, if attacker can modify the device physically, knowing the private key cannot be the evidence of trust any more. Thus, we need stronger verification method like code attestation. In this paper, we use software-based code attestation for efficiency. We also suggest secure code attestation method against copy of original code and implement it on embedded device and analyze its performance.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.217-223
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• 2018

Real-time controllability has been a major challenge that should be addressed to ascertain the practical usage of the management systems. In this regards, for the first time, we proposed and implemented an IoT(Internet of Things)-based water tank system to improve convenience and efficiency. The reservoir can be effectively controlled by notifying the user if the condition of the reservoir is unstable. The proposed system consists of embedded H/W unit for sensor data measuring and controling, application S/W for deployment of management server via web and mobile app, and efficient database structure for managing and monitoring statistics. And machine learning algorithms can be applied for further improvements of efficiency in practice.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.91-102
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• 2022

With the evolution of wireless sensor network (WSN) technology, the routing policy has foremost importance in the Internet of Things (IoT). A systematic routing policy is one of the primary mechanics to make certain the precise and robust transmission of wireless sensor networks in an energy-efficient manner. In an IoT environment, WSN is utilized for controlling services concerning data like, data gathering, sensing and transmission. With the advantages of IoT potentialities, the traditional routing in a WSN are augmented with decision-making in an energy efficient manner to concur finer optimization. In this paper, we study how to combine IoT-based deep learning classifier with routing called, Kriging Regressive Deep Belief Neural Learning (KR-DBNL) to propose an efficient data packet routing to cope with scalability issues and therefore ensure robust data packet transmission. The KR-DBNL method includes four layers, namely input layer, two hidden layers and one output layer for performing data transmission between source and destination sensor node. Initially, the KR-DBNL method acquires the patient data from different location. Followed by which, the input layer transmits sensor nodes to first hidden layer where analysis of energy consumption, bandwidth consumption and light intensity are made using kriging regression function to perform classification. According to classified results, sensor nodes are classified into higher performance and lower performance sensor nodes. The higher performance sensor nodes are then transmitted to second hidden layer. Here high performance sensor nodes neighbouring sensor with higher signal strength and frequency are selected and sent to the output layer where the actual data packet transmission is performed. Experimental evaluation is carried out on factors such as energy consumption, packet delivery ratio, packet loss rate and end-to-end delay with respect to number of patient data packets and sensor nodes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1500-1505
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• 2019

Currently, as part of the ICT Smart City, the company is building C-ITS(Cooperative-Intelligent Transport Systems) for solving urban traffic problems. In order to realize autonomous driving service with C-ITS, the role of advanced road infrastructure is important. In addition to the study of mid- to long-term C-ITS and autonomous driving services, it is necessary to present more realistic solutions for road traffic safety in the short term. Therefore, in this paper, we propose a highway accident detection alarm system that can detect and analyze traffic flow and risk information, which are essential information of C-ITS, based on IoT guard rail and provide immediate alarm and remote control. Intelligent IoT guard rail is expected to be used as an intelligent advanced road infrastructure that provides data at actual road sites that are required by C-ITS and self-driving services in the long term.

• The Journal of Society for e-Business Studies
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• v.21 no.4
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• pp.81-93
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• 2016

Internet of Things (IoT) has been established in various industries and IoT technology is highlighted as a new value creation technology. Especially, Korean government has launched Manufacturing Innovation 3.0 Strategy for developing Smart Factory concept to improve national and corporate's competitiveness. This study tries to present new industry classification scheme considering 10 national key manufacturing industries. Based on the new scheme, 10 national main forces industries are categorized into 6 segments. We have conducted SWOT analysis to comprehend Korean IoT environment. Based on the analysis, we have positioned 6 segments at the strategic decision-making grid to analyze industries' IoT practical usage.

• Journal of KIISE
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• v.44 no.10
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• pp.1071-1080
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• 2017

With today's complex networks, asset identification of network devices is becoming an important issue in management and security. Because these assets are connected to the network, it is also important to identify the network structure and to verify the location and connection status of each asset. This can be used to identify vulnerabilities in the network architecture and find solutions to minimize these vulnerabilities. However, in an IoT(Internet of Things) network with a small amount of resources, the Traceroute packets sent by the monitors may overload the IoT devices to determine the network structure. In this paper, we describe how we improved the existing the well-known double-tree algorithm to effectively reduce the load on the network of IoT devices. To balance the load, this paper proposes a new destination-matching algorithm and attempts to search for the path that does not overlap the current search path statistically. This balances the load on the network and additionally balances the monitor's resource usage.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.336-342
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• 2017

Traffic can be localized by reducing the traffic load on the physical network by causing traffic to be generated at the end of the packet network. By localizing traffic, the IoT-based sensitive data-related security issues can be supported effectively. In addition, it can be applied effectively to the next-generation smart network environment without changing the existing network infrastructure. In this paper, a content priority scheme was applied to smart network-based IoT data. The IoT contents were localized to efficiently pinpoint the flow of traffic on the network to enable smart forwarding. In addition, research was conducted to determine the effective network traffic routes through content localization. Through this study, the network load was reduced. In addition, it is a network structure that can guarantee user quality. In addition, it proved that the IoT service can be accommodated effectively in a smart network-based environment.

• 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.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.214-219
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• 2021

As the number of elderly increased rapidly every year, many elderly still choose to stay independent despite of difficulties and challenges faced in their daily routine. Elderly has desperate needs for support for their living. Internet of Things helps to support and improve elderly's life in many ways to meet the needs and requirements. Home Automation Control (EHAC) is a research based system that support elderly with controlled automation solution that control and operates various home electrical appliances based on the measurement of heart pulse rate and environment temperature. This paper works on EHAC system to evaluate the performance of the system in elderly's daily routine. This paper presented experiments conducted with approach of IoT testing and discussion on analysis of the results.

• International journal of advanced smart convergence
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• v.11 no.3
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• pp.36-41
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• 2022

In the 21st century, information collection and information provision based on digital informatization and intelligent automation are emerging as one of the social problems in the society for the elderly and the vulnerable groups in the welfare society including the disabled, and various methods are being studied to find realistic alternatives. Among these factors, the problem of the elderly living alone is emerging as the most serious, and as a realistic approach to solve some problems by applying information devices, it is a monitoring system using the Internet of Things(IoT). The need for an optimized system is emerging. In this study, the state of the elderly and the elderly living alone can be measured remotely by applying IoT technology. We present the research cases of a Breathing Sensor-based Smart Monitoring System that is used as a smart information system and used as a monitoring system for the elderly and infirm when it is identified as deceased through state detection