• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1137-1144
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• 2020

This paper aims to provide strategic suggestions by analyzing technology trends related to big data, IoT, and artificial intelligence. To this end, analysis was performed using the 2018 national R&D information, and major basic analysis and language network analysis were performed. As a result of the analysis, research and development related to big data, IoT, and artificial intelligence are being conducted by focusing on the basic and development stages, and it was found that universities and SMEs have a high proportion. In addition, as a result of the language network analysis, it is judged that the related fields are mainly research for use in the smart farm and healthcare fields. Based on these research results, first, big data is essential to use artificial intelligence, and personal identification research should be conducted more actively. Second, they argued that full-cycle support is needed for technology commercialization, not simple R&D activities, and the need to expand application fields.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.315-320
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• 2021

While blockchain platforms for various purposes have been developed and the blockchain ecosystem is being developed, interoperability problems are emerging in which each blockchain is isolated and operated. In this study, we introduce interchain and sidechain technologies, which are blockchain that connect blockchain, and explain examples of using heterogeneous blockchain transactions and functions by applying them. In addition, blockchain, artificial intelligence, and IoT technologies, which are drawing attention in the fourth industrial revolution, are going through a process of converging and developing beyond their own development. In this regard, we present processes for combining artificial intelligence or IoT in blockchain, and propose a model that can operate without intervention by applying the combination of blockchain and artificial intelligence IoT to processes for trading and exchange between heterogeneous blockchain.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.185-196
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• 2022

The Internet of Things (IoT) has become more and more widespread in recent years, thus attackers are placing greater emphasis on IoT environments. The IoT connects a large number of smart devices via wired and wireless networks that incorporate sensors or actuators in order to produce and share meaningful information. Attackers employed IoT devices as bots to assault the target server; however, because of their resource limitations, these devices are easily infected with IoT malware. The Distributed Denial of Service (DDoS) is one of the many security problems that might arise in an IoT context. DDOS attempt involves flooding a target server with irrelevant requests in an effort to disrupt it fully or partially. This worst practice blocks the legitimate user requests from being processed. We explored an intelligent intrusion detection system (IIDS) using a particular sort of machine learning, such as Artificial Neural Networks, (ANN) in order to handle and mitigate this type of cyber-attacks. In this research paper Feed-Forward Neural Network (FNN) is tested for detecting the DDOS attacks using a modified version of the KDD Cup 99 dataset. The aim of this paper is to determine the performance of the most effective and efficient Back-propagation algorithms among several algorithms and check the potential capability of ANN- based network model as a classifier to counteract the cyber-attacks in IoT environments. We have found that except Gradient Descent with Momentum Algorithm, the success rate obtained by the other three optimized and effective Back- Propagation algorithms is above 99.00%. The experimental findings showed that the accuracy rate of the proposed method using ANN is satisfactory.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.9
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• pp.283-290
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• 2023

With the recent steady development of IoT technology, it is widely used in medical systems and smart TV watches. 66% of software development is developed through language C, which is vulnerable to memory attacks, and acts as a threat to IoT devices using language C. A stack-smashing overflow attack inserts a value larger than the user-defined buffer size, overwriting the area where the return address is stored, preventing the program from operating normally. IoT devices with low memory capacity are vulnerable to stack smashing overflow attacks. In addition, if the existing vaccine program is applied as it is, the IoT device will not operate normally. In order to defend against stack smashing overflow attacks on IoT devices, we used canaries among several detection methods to set conditions with random values, checksum, and DSLR (random storage locations), respectively. Two canaries were placed within the buffer, one in front of the return address, which is the end of the buffer, and the other was stored in a random location in-buffer. This makes it difficult for an attacker to guess the location of a canary stored in a fixed location by storing the canary in a random location because it is easy for an attacker to predict its location. After executing the detection program, after a stack smashing overflow attack occurs, if each condition is satisfied, the program is terminated. The set conditions were combined to create a number of eight cases and tested. Through this, it was found that it is more efficient to use a detection method using DSLR than a detection method using multiple conditions for IoT devices.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1106-1112
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• 2017

As the Internet of Things (IOT) is evolving into an industry-wide service and expanded to the concept of Internet of Everything (IoE), services using IoT devices are easily accessible in everyday life. IoT requires more devices to collect information and is expected to increase the number of devices by 50 billion by 2020, and is about the number of devices currently available. Gradually, the number of mobile devices, smart devices, and Internet devices is increasing, and energy resources are required to operate such a large number of Internet devices, and the energy consumed by each device is small. In this paper, we consider the number of devices to be increased and generate a signal irrespective of transmission information so that power other than the energy required for signal transmission is consumed. When transmission information is generated and near to a receiver to receive information, The method to be used as an analysis is designed through experiments.

• Smart Media Journal
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• v.5 no.3
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• pp.74-80
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• 2016

In this paper, we propose an accident-prevention smart monitoring system for Haenyeo(Woman diver) using Zigbee module and GPS sensor. This system can collect such information as the diving location, the body temperature, the depth of diving, and the diving time of a Woman diver working under the water and then respond immediately to an accident occurring. The research developed a smart Teawak and smart swimming goggles which can measure the state of a Woman diver and her diving activities. Smart Teawak, the buoy tool while a Woman diver is collecting seafoods under water, is able to receive GPS and transmit the data from smart swimming goggles and Zigbee Module to IHSS(IoT based Haenyeo Safety service Software) server. In addition, IHSS, a responsive web, provides the diving location and the state of a Woman diver on the smart phone. As a result, the system will be useful in the aspects of Woman diver' health care and the safety, furthermore, which will significantly contribute to global marketing of Woman diver with its being designated as a UNESCO intangible cultural asset.

• Smart Media Journal
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• v.10 no.2
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• pp.92-99
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• 2021

Smart space is a technology that supports humans by interacting with the surrounding environment. Smart space has a built-in dynamic intelligent environment. This paper proposes a framework that provides user-customized dynamic intelligent environments in smart spaces. In the existing research that provides user-customized intelligent services, users' interests are only explicitly analyzed, and smart spaces are not considered. Implicit interest analysis can suggest a service that may be of interest to users rather than explicit interest analysis, but it requires higher performance than explicit interest analysis. Smart spaces can obtain useful information by interacting with information in the space. The framework proposed in the study uses a proximity-based social network of things to fit into a smart space. In addition, the implicit interest analysis provides intelligent information for smart spaces using the social media information and spatial information objects. In addition, we propose a method to prevent performance degradation while maintaining accuracy in consideration of the characteristics of the smart space.

• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.1-12
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• 2016

Internet of Things (IoTs) technologies have been computerized information generated from a variety of objects and humans, and have been applied to various fields by connecting via the Internet. In order to compensate for the marginal characteristics of IoT smart devices, such as low-power, limited processing and capacities, combining IoT and cloud computing technologies is now established itself as one of the paradigms. In this paper, we look at the definition, features and services of IoT and cloud computing technology, and we investigate and analyze the conversing needs of IoT and could computing, existing conversion paradigms, convergence cases, and platforms. In results, there are challenges to be solved, even though the cloud technologies complement a number of restrictions of IoT and offer various advantages such as scalability, interoperability, reliability, efficiency, availability, security, ease of access, ease of use, and reduced cost of deployment. We analyze the new research issues of convergence paradigm, and finally suggest a research challenges for convergence.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.661-667
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• 2018

Recently, the smart home market is growing due to the development of wireless communication technology and sensor devices, and various devices are being utilized. Such an IoT environment collects various vast amount of device information for intelligent services, receives services based on user information, controls various devices, and provides communication between different types of devices. However, with this growth, various security threats are occurring in the smart home environment. In fact, Proofpoint and HP warned about the cases of damage in a smart home environment and the severity of security vulnerabilities, and cases of infringement in various environments were announced. Therefore, in this paper, we have studied secure mutual authentication method between smart nodes used in smart home to solve security problems that may occur in smart home environment. In the case of the proposed thesis, security evaluations are performed using random numbers and frequently updated session keys and secret keys for well-known vulnerabilities that can occur in IoT environments and sensor devices such as sniffing, spoofing, device mutual authentication, And safety. In addition, it is confirmed that it is superior in security and key management through comparison with existing smart home security protocol.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.109-115
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• 2019

Smart Factory is a part of and a key point of the 4th industrial revolution. It performs optimization from the whole viewpoint, using comprehensive data of the post-process data by utilizing various sensors, controllers, and mobile devices beyond the existing factory automation level. In this paper, we design and implement an IoT platform that can detect the safety factors of the workers, the environmental factors of the factory, and real time monitoring at the control center, among the fields to implement smart factory. To accomplish this, we construct a monitoring device that provides sensor information control, server transmission of sensor information, and visualization of collected information. By using this system, it is possible to maintain the temperature and humidity for the optimum working environment in the factory. and also, By using the beacon, it is possible to measure the working time of the worker and trace the position.