• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.67-76
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• 2024

The Internet of Things (IoT) has revolutionized communication and device operation, but it has also brought significant security challenges. IoT networks are structured into four levels: devices, networks, applications, and services, each with specific security considerations. Personal Area Networks (PANs), Local Area Networks (LANs), and Wide Area Networks (WANs) are the three types of IoT networks, each with unique security requirements. Communication protocols such as Wi-Fi and Bluetooth, commonly used in IoT networks, are susceptible to vulnerabilities and require additional security measures. Apart from physical security, authentication, encryption, software vulnerabilities, DoS attacks, data privacy, and supply chain security pose significant challenges. Ensuring the security of IoT devices and the data they exchange is crucial. This paper utilizes the Random Forest Algorithm from machine learning to detect anomalous data in IoT devices. The dataset consists of environmental data (temperature and humidity) collected from IoT sensors in Oman. The Random Forest Algorithm is implemented and trained using Python, and the accuracy and results of the model are discussed, demonstrating the effectiveness of Random Forest for detecting IoT device data anomalies.

• Journal of Digital Convergence
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• v.15 no.7
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• pp.201-211
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• 2017

Wireless network using dynamic IP and mobile IP technology provides the user with convenience of access and movement. However, this causes the attacker who disguises normal user(pretending to be a regular user) to have more opportunity in regard to access and acquisition of information. This paper help the network administrator and the service provider quickly to recognize the attacker's intention to access network and service. Therefore network administrator and service provider can specify and respond the location of the attacker appropriately. To achieve above, we define an entity (W_L_M) that manages user information of WiFi and LTE network, and propose messages and procedures for attacker's location identification and alarm. The performance evaluation of this paper is based on qualitative analysis. By using the proposed method, some cost (message creation, processing and transmission) occurred but it was analyzed to be less than the total network operation cost. The proposal of this paper is a management method that utilizes existing network information and structure. This method can be used as a reference material to enhance security.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.4
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• pp.452-459
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• 2018

Conventional fire fighting robots are controlled by a remote control to monitor the fire scene or to suppress the fire. However, this method has a problem that it takes a long time to prepare robot and input it to fire place in the golden time after the fire, so that it can not sufficiently serve as a fire fighting robot. Using the autonomous driving fire monitoring robot, when a fire signal is generated, in conjunction with a fire receiver a moving robot takes a video of the fire scene and delivers the image to the fire department, so that the fire fighter can decide if it is real fire or not. Thereby it is possible to prevent a sudden spread of an accident by providing a quick judgment opportunity and at the same time suppressing the fire early. In this paper, we propose an architecture of the autonomous mobile fire monitoring robot and the communication protocol required for the robot to work with the fire receiver. A communication protocol is designed to control multiple fire monitoring robots in real time, and a communication with a fire receiver is designed as a hierarchical network to serve as an interface of an Ethernet network using wireless Wi-Fi. The fire monitoring robot and the wireless communication of the fire receiving period are implemented and the effectiveness of the operation is confirmed through the field test.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.117-124
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• 2017

A Smart Grid is a system that can efficiently use energy by exchanging real-time information in both directions between a consumer and a power supplier using ICT technology on an existing power network. DR(Demand response) is an arrangement in which electricity users can sell the electricity they save to the electricity market when the price of electricity is high or the power system is crisis. In this study, we developed a power meter data transmission device and power IT system that measure the demand information in real-time using a smart meter and transmit it to a cloud server. The power meter data transmission device developed in this study uses alight sensor connected to a Raspberry Pi 3 to measure the number of blinking lamps on the KEPCO meter per unit of power, in order to provide reliable data without any measurement errors with respect to the KEPCO power data. The power measurement data transmission device uses the standard communication protocol, OpenADR 2.0b. The measured data is transmitted to the power IT system, which consists of the VEN, VTN, and calculation program, via the LTE WiFi communication network and stored in its MySQL DB. The developed power measurement data transmission device issues a power supply instruction and performs a peak reduction DR when a power system crisis occurs. The developed power meter data transmission device has the advantage of allowing the user to adjust it every 1 minute, where as the existing smart metering time is fixed at once every 15 minutes.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.108-109
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• 2022

In this study analyzed experimental data on noise interference caused by engine operating apply surface wave communication in the engine room. For the experiment, 7 areas of the engine room on 256 ton tug boat and measured noise during engine on off using signal analyzer for effect surface wave communication. In order to construct and actual communication network based on the analysis of the noise and confirm the characteristics of surface wave communication in the area made metal bulkheads the actual communication network installed communication equipment between three metal bulkheads and conducted a comparative experiment with wireless communication. The difference was confirmed. As a result, in the case of surface wave communication, there was no significant difference in the transmission and reception rates before and after engine operation in an environment with three bulkheads, but in the case of Wi-Fi using wireless, the performance deteriorated significantly during operation. was confirmed. As a result of analyzing the experimental data, it was confirmed that noise caused by engine operation affects wireless communication but does not affect surface wave communication. Therefore, even in the area with a lot of electromagnetic wave noise in the ship, when the surface wave communication system is configured using the ship's metal structure, it is possible to replace the wireless communication and furthermore, it is possible to apply the surface wave communication in the enclosed space and the engine room in the ship.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.46-63
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• 2024

One of the biggest dangers in the globe is water contamination. Water is a necessity for human survival. In most cities, the digging of borewells is restricted. In some cities, the borewell is allowed for only drinking water. Hence, the scarcity of drinking water is a vital issue for industries and villas. Most of the water sources in and around the cities are also polluted, and it will cause significant health issues. Real-time quality observation is necessary to guarantee a secure supply of drinking water. We offer a model of a low-cost system of monitoring real-time water quality using IoT to address this issue. The potential for supporting the real world has expanded with the introduction of IoT and other sensors. Multiple sensors make up the suggested system, which is utilized to identify the physical and chemical features of the water. Various sensors can measure the parameters such as temperature, pH, and turbidity. The core controller can process the values measured by sensors. An Arduino model is implemented in the core controller. The sensor data is forwarded to the cloud database using a WI-FI setup. The observed data will be transferred and stored in a cloud-based database for further processing. It wasn't easy to analyze the water quality every time. Hence, an Optimized Neural Network-based automation system identifies water quality from remote locations. The performance of the feed-forward neural network classifier is further enhanced with a hybrid GA- PSO algorithm. The optimized neural network outperforms water quality prediction applications and yields 91% accuracy. The accuracy of the developed model is increased by 20% because of optimizing network parameters compared to the traditional feed-forward neural network. Significant improvement in precision and recall is also evidenced in the proposed work.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.2
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• pp.191-198
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• 2014

As an NMEA 2000 is a standard for communicate to other electronic equipment, it implemented a Universal gateway based on this ship's network. To implement a NMEA 2000 based Universal gateway, it is porting a NMEA 2000 stack source and CAN device driver source to board, and then it connected a board that equip with various communication protocol(CAN, RS232, USB, Ethernet port). To verify converted ship's data to a developed gateway, it connected pc based simulater program and monitoring program to a developed board. so we can see a ship's data through NEMA 2000 network. We verified a gateway performance and analyzed a generated ship's data from simulator program through a monitoring program that was connected a gateway and NMEA 2000 network. so it was designed, implemented to allow monitoring through utilizing a communication method that user wants.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1702-1707
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• 2010

As quantities of the data that transmitting by the wireless are more increased, the interest and application are extending about 802.11n that uses by combination two existing 20MHz wireless LAN Channel. 802.11n use dual band of 2.4GHz band and 5.8GHz. So this is expected in mass wireless transmission method because of interference evasion effect in compliance with the radio communication of existing 2GHz neighborhood band. Like this 802.11n uses the radio as well and transmits information there is not only a possibility of undergoing an influence in radio wave environment of circumference. Specially the interior environment and outdoor environment is a possibility of saying that will be defined with each other different modeling as affects in radio communication is different. In this paper, we'll compare the influence to RF feature (802.11n) by (Indoor/Outdoor) environment difference through compared with 802.11n RF feature and Network feature in (Indoor/Outdoor) environment and also examine the correlation between RF feature and Network feature.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5276-5298
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• 2019

Internet of Things (IoT) based sensor networks have gained unprecedented popularity in recent years. With the exponential explosion of the objects (sensors and mobiles), the bandwidth and the speed of data transmission are dwarfed by the anticipated emergence of IoT. In this paper, we propose a novel heterogeneous IoT model integrated the power line communication (PLC) and WiFi network to increase the network capacity and cope with the rapid growth of the objects. We firstly propose the mean transmission delay calculation algorithm based the 3D Markov chain according to the multi-priority of the objects. Then, the attractor selection algorithm, which is based on the adaptive behavior of the biological system, is exploited. The combined the 3D Markov chain and the attractor selection model, named MASM, can select the optimal path adaptively in the heterogeneous IoT according to the environment. Furthermore, we verify that the MASM improves the transmission efficiency and reduce the transmission delay effectively. The simulation results show that the MASM is stable to changes in the environment and more applicable for the heterogeneous IoT, compared with the other algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.12
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• pp.1102-1112
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• 2012

We propose a cell selection and resource allocation scheme that assigns users to nearby accessible cells in heterogeneous wireless networks consisting of macrocell, femtocells, and Wi-Fi access points, under overload situation. Given the current power level of all accessible cells nearby users, the proposed scheme finds all possible cell assignment mappings of which user should connect to which cell to maximize the number of users that the network can accommodate at the same time. We formulate the cell selection problem with heterogeneous cells into an optimization problem of binary integer programming, and compute the optimal solution. We evaluate the proposed algorithm in terms of network access failure compared to a local ad-hoc based cell selection scheme used in practical systems using network level simulations. We demonstrate that our cell selection algorithm dramatically reduces network access failure in overload situation by fully leveraging network resources evenly across heterogeneous networks. We also validate the practical feasibility in terms of computational complexity of our binary integer program by measuring the computation time with respect to the number of users.