• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.654-656
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• 2016

MACsec is a cryptographic function that operates on Layer 2. As industries such as IoT(Internet of Things) devices are receiving attention recently are connected to the network and Internet traffic is increasing rapidly. Because of today, Becoming the increase in traffic and complex situations to protect the overall traffic, not just certain parts. The MACsec technology has received attention. In this paper, Layer 2 security technology to MACsec. Design the technology MACsec adapter that can easily and readily added to existing Layer 2 network.

• Annual Conference of KIPS
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• 2015.04a
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• pp.312-314
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• 2015

2015년 현재 정보통신기술(ICT)중 사물인터넷 (IoT : Internet of Things)이 화두에 오르고 있다. 언제 어디서나 통신으로 연결만 되어 있으면 스마트폰으로 주변에 있는 사물들의 제어가 가능하다. 또, 주목 받고 있는 기술로서 근거리통신기능(NFC : Near Field Communication)이 IoT와 결합해 우리 주변을 편리하게 해주고 있다. NFC 발달과 함께, 본 연구에서는 NFC를 통해 메뉴를 공유하고 종업원 없이도 주방으로 Order를 보낼 수 있는 제어기능이 탑재된 어플리케이션을 기획한다. 여러 명의 Order를 한 사람의 스마트폰으로 NFC를 이용한 기술인 P2P 기능을 이용해 모아준다. 그 후, 한 데 모은 주문내역을 대표 한 사람이 주방으로 Order를 보내는 기능과 두 번 이상의 방문을 하게 될 경우 그 동안의 주문내역 히스토리를 분석해서 주문에 대한 피드백을 제공함으로써 편리하게 사용할 수 있도록 연구하고자 한다.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.905-917
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• 2021

In recent years, edge computing technology consists of several Internet of Things (IoT) devices with embedded sensors that have improved significantly for monitoring, detection, and management in an environment where big data is commercialized. The main focus of edge computing is data optimization or task offloading due to data and task-intensive application development. However, existing offloading approaches do not consider correlations and associations between data and tasks involving edge computing. The extent of collaborative offloading segmented without considering the interaction between data and task can lead to data loss and delays when moving from edge to edge. This article proposes a range segmentation of dynamic offloading (RSDO) algorithm that isolates the offload range and collaborative edge node around the edge node function to address the offloading issue.The RSDO algorithm groups highly correlated data and tasks according to the cause of the overload and dynamically distributes offloading ranges according to the state of cooperating nodes. The segmentation improves the overall performance of edge nodes, balances edge computing, and solves data loss and average latency.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.113-114
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• 2019

다수의 센서 노드로 구성된 IoT 환경에서는 네트워크 수명, 센서 노드의 통신 범위 제한과 같은 제약 사항들이 있다. 이러한 한계점을 해결하기 위해 밀집된 센서 노드 간의 협력이 필요하다. 이때, 밀집된 센서 노드들은 에너지 낭비 및 전송 데이터의 정확도를 저하시킨다. 본 연구에서는 데이터 집중으로 인해 발생하는 네트워크의 에너지 낭비 및 전송 데이터의 정확도 문제를 해결하기 위해 자체조직지도(Self Organized Map, SOM)를 기반으로 한 클러스터링 기법을 제안한다. 결과적으로 제안된 기법을 통하여 클러스터링 된 노드들은 다른 클러스터링 기법과 비교했을 때 밀도 기반의 정확한 예측 값을 얻을 수 있다.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.121-128
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• 2021

In order to design a real time big data collection and analysis system of manufacturing data in a smart factory, it is important to establish an appropriate wired/wireless communication system and protocol. This paper introduces the latest communication protocol, OPC-UA (Open Platform Communication Unified Architecture) based client/server function, applied user interface technology to configure a network for real-time data collection through IoT Integration. Then, Database is designed in MES (Manufacturing Execution System) based on the analysis table that reflects the user's requirements among the data extracted from the new cutting process automation process, bush inner diameter indentation measurement system and tool monitoring/inspection system. In summary, big data analysis system introduced in this paper performs SPC (statistical Process Control) analysis and visualization analysis with interface of OPC-UA-based wired/wireless communication. Through AI learning modeling with XGBoost (eXtream Gradient Boosting) and LR (Linear Regression) algorithm, quality and visualization analysis is carried out the storage and connection to the cloud.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.1-8
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• 2021

With the rapid growth of intelligent devices and communication technologies, 5G network environment has become more heterogeneous and complex in terms of service management and orchestration. 5G architecture requires supportive technologies to handle the existing challenges for improving the Quality of Service (QoS) and the Quality of Experience (QoE) performances. Among many challenges, traffic steering is one of the key elements which requires critically developing an optimal solution for smart guidance, control, and reliable system. Mobile edge computing (MEC), software-defined networking (SDN), network functions virtualization (NFV), and deep learning (DL) play essential roles to complementary develop a flexible computation and extensible flow rules management in this potential aspect. In this proposed system, an accurate flow recommendation, a centralized control, and a reliable distributed connectivity based on the inspection of packet condition are provided. With the system deployment, the packet is classified separately and recommended to request from the optimal destination with matched preferences and conditions. To evaluate the proposed scheme outperformance, a network simulator software was used to conduct and capture the end-to-end QoS performance metrics. SDN flow rules installation was experimented to illustrate the post control function corresponding to DL-based output. The intelligent steering for network communication traffic is cooperatively configured in SDN controller and NFV-orchestrator to lead a variety of beneficial factors for improving massive real-time Internet of Things (IoT) performance.

• ETRI Journal
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• v.45 no.2
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• pp.346-357
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• 2023

Hardware security primitives, also known as physical unclonable functions (PUFs), perform innovative roles to extract the randomness unique to specific hardware. This paper proposes a novel hardware security primitive using a commercial off-the-shelf flash memory chip that is an intrinsic part of most commercial Internet of Things (IoT) devices. First, we define a hardware security source model to describe a hardware-based fixed random bit generator for use in security applications, such as cryptographic key generation. Then, we propose a hardware security primitive with flash memory by exploiting the variability of tunneling electrons in the floating gate. In accordance with the requirements for robustness against the environment, timing variations, and random errors, we developed an adaptive extraction algorithm for the flash PUF. Experimental results show that the proposed flash PUF successfully generates a fixed random response, where the uniqueness is 49.1%, steadiness is 3.8%, uniformity is 50.2%, and min-entropy per bit is 0.87. Thus, our approach can be applied to security applications with reliability and satisfy high-entropy requirements, such as cryptographic key generation for IoT devices.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.224-226
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• 2021

Recently, in order to increase the efficiency of the product production process, the automation of facilities and devices in the factory is in progress, and a smart factory is being built using ICT and IoT technologies. In order to organically solve many problems occurring in the smart factory, a system for monitoring the wireless communication function between facilities and devices and the manufacturing process environment of the smart factory is required. In this paper, we propose a monitoring system using a Bluetooth module, a temperature/humidity sensor and a fine dust sensor to remotely monitor the process environment of a smart factory. The proposed monitoring system collect Arduino sensor values wirelessly through Bluetooth communication.

• Journal of Information Processing Systems
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• v.20 no.1
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• pp.116-130
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• 2024

In the Internet-of-Things (IoT) or blockchain-based network systems, secure keys may be stored in individual devices; thus, individual devices should protect data by performing secure operations on the data transmitted and received over networks. Typically, secure functions, such as a physical unclonable function (PUF) and fully homomorphic encryption (FHE), are useful for generating safe keys and distributing data in a network. However, to provide these functions in embedded devices for IoT or blockchain systems, proper inspection is required for designing and implementing embedded system-on-chip (SoC) modules through overhead and performance analysis. In this paper, a virtual platform (SoC VP) was developed that includes a secure key generation module with a PUF and FHE. The SoC VP platform was implemented using SystemC, which enables the execution and verification of various aspects of the secure key generation module at the electronic system level and analyzes the system-level execution time, memory footprint, and performance, such as randomness and uniqueness. We experimentally verified the secure key generation module, and estimated the execution of the PUF key and FHE encryption based on the unit time of each module.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.9-16
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• 2017

Recently, more users have been using IoT embedded systems. Since the wireless network function is a basic and core function in most embedded systems, new security threats and weaknesses are expected to occur. In order to resolve these threats, it is necessary to investigate the security issues in the development stages according to the Security Development Lifecycle (SDL). This study analyzes the vulnerabilities of the embedded systems equipped with the wireless network function, and derives possible security threats and how dangerous such threats are. We present security risks including bypassing the authentication stage required for accessing to the embedded system.