• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.95-102
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• 2023

The emergence of Internet of Things (IoT) into our daily lives has grown rapidly. It's been integrated to our homes, cars, and cities, increasing the intelligence of devices involved in communications. Enormous amount of data is exchanged over smart devices through the internet, which raises security concerns in regards of privacy evasion. This paper is focused on the forensics and intrusion detection on one of the most common protocols in IoT environments, especially smart home environments, which is the Message Queuing Telemetry Transport (MQTT) protocol. The paper covers general IoT infrastructure, MQTT protocol and attacks conducted on it, and multiple network forensics frameworks in smart homes. Furthermore, a machine learning model is developed and tested to detect several types of attacks in an IoT network. A forensics tool (MQTTracker) is proposed to contribute to the investigation of MQTT protocol in order to provide a safer technological future in the warmth of people's homes. The MQTT-IOT-IDS2020 dataset is used to train the machine learning model. In addition, different attack detection algorithms are compared to ensure the suitable algorithm is chosen to perform accurate classification of attacks within MQTT traffic.

• Journal of IKEEE
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• v.22 no.3
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• pp.590-598
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• 2018

Recently, interest in IoT(Internet of Things) technology, which provides Internet services to objects, is increasing. IoT offers a variety of services in home networks, healthcare, and disaster alerts. IoT with LLN(Low Power & Lossy Networks) feature frequently loses sensor node. RPL, the standard routing protocol of IoT, performs global repair when data loss occurs in a sensor node. However, frequent loss of sensor nodes due to lower sensor nodes causes network performance degradation due to frequent full path reset. In this paper, we propose an additional selection method of the storage mode sensor node to solve the network degradation problem due to the frequent path resetting problem even after selecting the storage mode sensor node, and propose a method of equalizing the total path resetting number of each instance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.778-783
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• 2018

With the rapid advancement of information and communication technology and industrial technologies, a hyper-connected society is being realized to connect human beings, all programs and things via the Internet. IoT (Internet of Thing), which connects a thing and another thing, and things and human beings, gathers information to realize the hyper-connected society. MQTT (Message Queuing Telemetry Transport) is a push-technology-based light message transmission protocol that was developed to be optimized to the limited communication environment such as IoT. In pursuing the hyper-connected society, IoT's sensor environment information is now being used as a wide range of information on people's diseases and health management. Thus, security problems of such MQTT include not only the leak of environmental information but also the personal information infringement. To resolve such MQTT security problems, we have designed a new security MQTT communication by applying the initial-value sensitivity and pseudorandomness of the chaotic system to the integrity and confidentiality. The encryption method using our proposed chaotic system offers a simple structure and a small amount of calculation, and it is deemed to be suitable to the limited communication environment such as IoT.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.29-34
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• 2019

In Recently, as the interest in health has increased and the spread of smart phones has become common, the development of smart health care related contents has been active. In this paper, we introduce the design, implementation and effects of game-based content that can make walking exercise fun in the Internet of Things environment. This content calculates the consumed calories by walking the stairs with the Beacon installed, and incorporates games to encourage continuous fun activities. It also provides event functions that enable on-off-line coordination. The goal of this content is to enable busy modern people to exercise lightly, funly, and constantly in the surrounding activity space. The effect of this content has been confirmed through the review of many users participating in offline events. This content is expected to be able to converge with various types of healthcare systems with the expansion of the application space.

• Journal of Sensor Science and Technology
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• v.32 no.1
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• pp.1-9
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• 2023

Recently, the digital healthcare technologies including non-invasive diagnostics based on Internet of Things (IOT) are getting attention. Human exhaled breath contains a variety of volatile organic compounds (VOCs), which can provide information of malfunctions of the body and presence of a specific disease. Detection of VOCs in exhaled breath using gas sensors are easy to use, safe, and cost-effective. However, accurate diagnosis of diseases is challenging because changes in concentration of VOCs are extremely small and lots of body factors directly or indirectly influence to the conditions. To overcome the limitations, highly selective nanosensors and artificial intelligent electronic nose (E-nose) systems have been mainly researched in recent decades. This review provides brief reviews of the recent studies for diabetes and lung cancer diagnosis using nanosensors and E-nose systems.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.11a
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• pp.57-58
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• 2018

The number of deaths in the korean construction industry is more than three times the OECD average. Although safety management system should be improved to prevent the safety accidents, it is difficult to improve due to domestic safety conditions. Especially, in order to prevent accidents at construction sites, there is an increasing tendency to monitor the movement of workers and equipment in real time by introducing a location positioning system. Therefore, this study proposes a system that can monitor the position of workers and heavy equipments in real - time, detect danger and transmit alarms so that workers can pay attention to safety and keep safety. The system is expected to reduce safety accidents by transmitting alarms to workers so that they can pay attention.

• Korea Journal of Hospital Management
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• no.spc
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• pp.74-84
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• 2016

This research is for an innovative health information service cases based on Information Communication Technology (ICT), conducted at a general hospital in Korea. This study introduces a personal use self-diagnosis & self management device for pulmonary chronic disease patients, a mobile communication application service for doctor rounds, a surgical education system providing natural-user-interface with virtual reality for surgeons, and an Internet of things(IOT) technology using personal electrocardiogram (ECG) measurement device cases. Due to every case is on developing, there are still many issues needed to be improved. For this reason, various opinions with constructive critiques from the readers of this paper will be welcomed for better practical implementation.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.184-191
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• 2020

With the emergence of the 4th Industrial Revolution, core technologies that will lead the 4th Industrial Revolution such as AI (artificial intelligence), big data, and Internet of Things (IOT) are also at the center of the topic of the general public. In particular, there is a growing trend of attempts to present future visions by discovering new models by using them for big data analysis based on data collected in a specific field, and inferring and predicting new values with the models. In order to obtain the reliability and sophistication of statistics as a result of big data analysis, it is necessary to analyze the meaning of each variable, the correlation between the variables, and multicollinearity. If the data is classified differently from the hypothesis test from the beginning, even if the analysis is performed well, unreliable results will be obtained. In other words, prior to big data analysis, it is necessary to ensure that data is well classified according to the purpose of analysis. Therefore, in this study, data is classified using a decision tree technique and a random forest technique among classification analysis, which is a machine learning technique that implements AI technology. And by evaluating the degree of classification of the data, we try to find a way to improve the classification and analysis rate of the data.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.16-25
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• 2019

The Internet of things (IOT) is remodeling the agribusiness empowering the agriculturists through the extensive range of strategies, for example, accuracy as well as practical farming to deal with challenges in the field. The paper aims making use of evolving technology i.e. IoT and smart agriculture using automation. The objective of this research paper to present tools and best practices for understanding the role of information and communication technologies in agriculture sector, motivate and make the illiterate farmers to understand the best insights given by the big data analytics using machine learning. The methodology used in this system can monitor the humidity, moisture level and can even detect motions. According to the data received from all the sensors the water pump, cutter and sprayer get automatically activated or deactivated. we investigate a remote monitoring system using Wi-Fi. These nodes send data wirelessly to a central server, which collects the data, stores it and will allow it to be analyzed then displayed as needed and can also be sent to the client mobile.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.135-147
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• 2023

Internet of things has revolutionaries every field of life due to the use of artificial intelligence within Machine Learning. It is successfully being used for the study of Radiation monitoring, prediction of Ultraviolet and Electromagnetic rays. However, there is no particular system available that can monitor and detect waves. Therefore, the present study designed in which IOT enables intelligence system based on machine learning was developed for the prediction of the radiation and their effects of human beings. Moreover, a sensor based system was installed in order to detect harmful radiation present in the environment and this system has the ability to alert the humans within the range of danger zone with a buzz, so that humans can move to a safer place. Along with this automatic sensor system; a self-created dataset was also created in which sensor values were recorded. Furthermore, in order to study the outcomes of the effect of these rays researchers used Support Vector Machine, Gaussian Naïve Bayes, Decision Trees, Extra Trees, Bagging Classifier, Random Forests, Logistic Regression and Adaptive Boosting Classifier were used. To sum up the whole discussion it is stated the results give high accuracy and prove that the proposed system is reliable and accurate for the detection and monitoring of waves. Furthermore, for the prediction of outcome, Adaptive Boosting Classifier has shown the best accuracy of 81.77% as compared with other classifiers.