• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.669-674
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• 2017

Due to the depletion of fossil fuels and the increase in environmental pollution, electric vehicles are attracting attention as next-generation transportation and are becoming popular all over the world. As the interest in electric vehicles and the penetration rate increase, studies on the charging infrastructure with vehicle-to-grid (V2G) technology and information technology are actively under way. In particular, communication with the grid network is the most important factor for stable charging and load management of electric vehicles. However, with the existing centralized infrastructure, there are problems when control-message requests increase and the charging infrastructure cannot efficiently operate due to slow response speed. In this paper, we propose a new charging infrastructure using mobile edge computing (MEC) that mitigates congestion and provides low latency by applying distributed cloud computing technology to wireless base stations. Through a performance evaluation, we confirm that the proposed charging infrastructure (with low latency) can cope with peak conditions more efficiently than the existing charging infrastructure.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.107-118
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• 2021

The deployment of 5G is in full swing, with a significant yearly growth in the data traffic expected to reach 26% by the year and data consumption to reach 122 EB per month by 2022 [10]. In parallel, the idea of smart cities has been implemented by various governments and private organizations. One of the main objectives of 5G deployment is to help develop and realize smart cities. 5G can support the enhanced data delivery requirements and the mass connection requirements of a smart city environment. However, for specific high-demanding applications like tactile Internet, transportation, and augmented reality, the cloud-based 5G infrastructure cannot deliver the required quality of services. We suggest using multi-access edge computing (MEC) technology for smart cities' environments to provide the necessary support. In cloud computing, the dependency on a central server for computation and storage adds extra cost in terms of higher latency. We present a few scenarios to demonstrate how the MEC, with its distributed architecture and closer proximity to the end nodes can significantly improve the quality of services by reducing the latency. This paper has surveyed the existing work in MEC for 5G and highlights various challenges and opportunities. Moreover, we propose a unique framework based on the use of MEC for 5G in a smart city environment. This framework works at multiple levels, where each level has its own defined functionalities. The proposed framework uses the MEC and introduces edge-sub levels to keep the computing infrastructure much closer to the end nodes.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.4
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• pp.731-751
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• 2021

The Internet of Things is a huge group of devices communicating each other and the interconnection of objects in the network is a basic requirement. Choosing a reliable device is critical because malicious devices can compromise networks and services. However, it is difficult to create a trust management model due to the mobility and resource constraints of IoT devices. For the centralized approach, there are issues of single point of failure and resource expansion and for the distributed approach, it allows to expand network without additional equipment by interconnecting each other, but it has limitations in data exchange and storage with limited resources and is difficult to ensure consistency. Recently, trust management models using fog nodes and blockchain have been proposed. However, blockchain has problems of low throughput and delay. Therefore, in this paper, a trust management model for selecting reliable devices in a fog-based IoT environment is proposed by applying IOTA, a blockchain technology for the Internet of Things. In this model, Directed Acyclic Graph-based ledger structure manages trust data without falsification and improves the low throughput and scalability problems of blockchain.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.419-421
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.238-240
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.755-778
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• 2024

In recent years, the number of devices being connected to the internet has grown enormously, as has the intrusive behavior in the network. Thus, it is important for intrusion detection systems to report all intrusive behavior. Using deep learning and machine learning algorithms, intrusion detection systems are able to perform well in identifying attacks. However, the concern with these deep learning algorithms is their inability to identify a suitable network based on traffic volume, which requires manual changing of hyperparameters, which consumes a lot of time and effort. So, to address this, this paper offers a solution using the extended compact genetic algorithm for the automatic tuning of the hyperparameters. The novelty in this work comes in the form of modeling the problem of identifying attacks as a multi-objective optimization problem and the usage of linkage learning for solving the optimization problem. The solution is obtained using the feature map-based Convolutional Neural Network that gets encoded into genes, and using the extended compact genetic algorithm the model is optimized for the detection accuracy and latency. The CIC-IDS-2017 and 2018 datasets are used to verify the hypothesis, and the most recent analysis yielded a substantial F1 score of 99.23%. Response time, CPU, and memory consumption evaluations are done to demonstrate the suitability of this model in a fog environment.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.333-335
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• 2017

모바일 사용과 사물 인터넷 기술의 발전으로 인해 이를 적용할 수 있는 분야가 점점 다양해지고 이러한 기술들을 이용하는 사용자들의 수도 비약적으로 증가하였다. 기존에 존재하던 클라우드 컴퓨팅 기술은 사물 인터넷 환경에 방대한 데이터를 실시간으로 처리하는데 적합하지 않으며, 이러한 문제를 해결하기 위해 사용자와 조금 더 근접한 영역에서 응답 시간을 최소화하고 병목 현상을 해결할 수 있는 포그 컴퓨팅이 제안되었다. 이 논문에선 클라우드 컴퓨팅의 혼잡도 증가와 속도 감소로 인한 문제점을 극복하기 위해 포그 컴퓨팅이라는 새로운 시스템의 개념과 이에 따른 보안 이슈를 정리하고, 연구방향을 제시한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.563-564
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• 2018

최근 차량 네트워크에서 포그 컴퓨팅 기능을 적용하는 새로운 연구가 진행 중이다. 특히, 최근 개발 중인 차량 포그 컴퓨팅 기술은 교통 정보를 실시간으로 수집하여 빠른 처리가 가능하며 이를 장법을 통해 안정된 차량 및 교통 서비스를 제공할 수 있다. 이런 차량 포그 컴퓨팅 기술은 교통 정보 수집, 운전 정보 제공, 스마트 교통 통제 및 도로 안전 메시지 등의 정보를 차량에 빠르게 전달할 수 있다. 본 논문에서는 차량 포그 컴퓨팅 기술을 리뷰하고 교차로 환경에서 차량 포그 컴퓨팅 기반 안전 메시지 전달을 위한 교통 시스템을 제안한다. 특히, 제안하는 기법은 대기 시간에 민감한 안전 메시지를 빠르게 전송할 수 있는 장점을 가지고 있다.

• International Journal of Advanced Culture Technology
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• v.10 no.2
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• pp.225-232
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• 2022

When we drive a vehicle in an IoT environment, there is a problem in that information of car users is collected without permission. The security measures used in the existing wired network environment cannot solve the security problem of cars running in the Internet of Things environment. Information should only be shared with entities that have been given permission to use it. In this paper, we intend to propose a method to prevent the illegal use of vehicle information. The method we propose is to use attribute-based encryption and dynamic threshold encryption. Real-time processing technology and cooperative technology are required to implement our proposed method. That's why we use fog computing's proxy servers to build smart gateways in cars. Proxy servers can collect information in real time and then process large amounts of computation. The performance of our proposed algorithm and system was verified by simulating it using NS2.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.140-143
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• 2021

IoBT시장은 2023년까지 317억 달러로 성장할 것으로 예측되며, 센서 및 웨어러블 디바이스와 같은 IoBT 장비의 수가 급격히 늘어나고 있다. IoBT 장비들로부터 수집된 생체 정보와 같은 민감한 데이터를 효율적이고 안전하게 처리하기 위해 많은 노력이 필요하다. 하지만 초경량화, 저전력화된 IoBT 장비들은 보안적인 측면에서 취약한 상황이다. 본 논문은 Fog computing을 적용하여 전장과 지휘관 사이에서 결심 및 통제에 필요한 시각화 자료를 신속하게 제공하고 IoBT 장비의 보안 사항과 공격에 따른 완화 기법을 수행할 수 있는 새로운 네트워크 아키텍처를 제공하고자 한다.