• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.27-33
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• 2018

The recent efforts in academia and industry represent a paradigm shift that will extend the IoT from the home environment so that it is interoperable with the Internet of Vehicles (IoV). IoV is a special kind of IoT. It allows to connect between vehicle and things located in infrastructure. Furthermore, IoV enable to create new intelligent services through collaboration with existing various services such as smart city and connected home. In this paper, we develop a service in order to realize IoV. To this end, we design a novel vehicle service platform which could automatical controlling the IoT device according to drivers' voice. To show practical usability of our proposed platform, we develop a prototype service could be call car-to-thing (C2T). We expect that our proposed platform could eventually contribute to realizing IoV.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.4
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• pp.33-40
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• 2017

Internet of Vehicles (IoV) is a subset of Internet of Things (IoT) and it is an infrastructure for vehicles. Therefore, IoV consists of three main network including inter-vehicle network, intra-vehicle network, and vehicular mobile internet. IoV mainly used in urban traffic environment to provide network access for drivers, passengers and traffic management. Accordingly, many research works have focused on network technology. But, recent concerted efforts in academia and industry point to paradigm shift in IoV system. In this paper, we proposed a knowledge base for intelligence service in IoV. A detailed design and implementation of the proposed knowledged base is illustrated. We hope this work will show power of IoV as a disruptive technology.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.209-211
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• 2023

ICT 기술을 통해 데이터를 수집하고 수집된 데이터를 활용하여 시민의 삶의 질을 향상시키는 스마트시티는 대표적으로 전기, 건물, 냉난방 시스템, 교통이 있다. 스마트시티의 교통 문제를 해결하기 위하여 IoV의 데이터를 활용할 수 있으나, IoV에 대한 네트워크 공격이 급증함에 따라 블록체인을 사용하여 데이터를 안전하게 수집하고 스마트시티에 활용하는 다양한 연구가 진행되고 있다. 본 논문에서는 스마트시티 환경의 IoV 시스템을 위한 블록체인 기반 차량 네트워크 보안 기술 연구 동향을 기술하고 향후 연구 방향을 제시한다.

• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.309-313
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• 2019

This study examined the response of the EMG of URA, LRA, IO, EO and RFM of various types of abdominal motion (crunch, spine V-up on ball, prone V-up on slide board, prone V-up on TRX, and prone V-up power wheel). The subjects performed anisometric contact of abs during these exercises. Tests have shown that there were no statistically significant differences between EO, URA and LRA between any movements. However, during the inspection of IO, the positive-wawed V-up motion showed significantly greater muscle activity than during the slide movement. Also, EMG activity during crunch was significantly lower than any other five exercises. These results indicate that in the implementation of equilateral absolutism, the equipment-free based exercise gives an impetus similar to equipment-based exercise. Abdominal muscle tissue is considered one of the five components that make up an individual's core. The abdominal muscles also ensure proper functioning of the lumbar spine. Although all abdominal muscles contribute to lumbar stabilization, TA & IO has been shown to perform major stabilizers.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.389-401
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• 2022

The business of Internet of Vehicles (IoV) is growing rapidly, and the large amount of data exchange has caused problems of large mobile network communication delay and large energy loss. A strategy for resource allocation of IoV communication based on mobile edge computing (MEC) is thus proposed. First, a model of the cloud-side collaborative cache and resource allocation system for the IoV is designed. Vehicles can offload tasks to MEC servers or neighboring vehicles for communication. Then, the communication model and the calculation model of IoV system are comprehensively analyzed. The optimization objective of minimizing delay and energy consumption is constructed. Finally, the on-board computing task is coded, and the optimization problem is transformed into a knapsack problem. The optimal resource allocation strategy is obtained through genetic algorithm. The simulation results based on the MATLAB platform show that: The proposed strategy offloads tasks to the MEC server or neighboring vehicles, making full use of system resources. In different situations, the energy consumption does not exceed 300 J and 180 J, with an average delay of 210 ms, effectively reducing system overhead and improving response speed.

• Journal of the Korea Convergence Society
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• v.6 no.2
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• pp.65-70
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• 2015

As the new technologies like IoT and Fintech appear which have not existed before, security threat ranges in existing system are increasing. Especially, IoT has increasing ranges to cause malicious behaviors in specific systems because related IT infrastructure ranges are increasing. Fintech also requires the innovation of traditional security system because it has new structure which didn't exist in the past. As IoT and Fintech technologies are commercialized and related markets are developing in the future, structural security threats could be connected to actual attacks and secondary attacks by the attackers' imbedding of back door in IoT internet devices through remote access. Customer's device cannot be compulsively controlled for security in new system where these various security threats exist. Therefore, these services should minimize the collected information, and now is the time to politically control the utilizing methods of the collected information. In this thesis, security threats are to be suggested which could occur in newly appearing mobile services like IoT and Fintech.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.5
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• pp.889-899
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• 2021

This paper proposes a reliable data sharing scheme on the internet of vehicles (IoV) by utilizing blockchain technology for constructing a decentralized system approach. In our model, to maintain the credibility of the information messages sent by the vehicles to the system, we propose a reputation rating mechanism, in which neighboring vehicles validate every received information message. Furthermore, we incorporate an incentive mechanism based on smart contracts, so that vehicles will get certain rewards from the system when they share correct traffic information messages. We simulated the IoV network using a discrete event simulator to analyze network performance, whereas the incentive model is designed by leveraging the smart contract available in the Ethereum platform.

• Current Optics and Photonics
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• v.6 no.3
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• pp.323-331
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• 2022

Electro-optic modulator (EOM) takes a vital role in connecting the electric and optical fields. Here, we present a heterogeneously integrated EOM based on the lithium niobate-on-insulator (LNOI) platform. The key modulation waveguide structure is a field-enhanced slot waveguide formed by embedding silicon nanowires in a thin-film lithium niobate (LN), which is different from the previously reported LN ridge or etchless LN waveguides. Based on such slot structure, optical mode field area is reduced and enhanced electric field in the slot region can interact well with LN material with high Electro-optic (EO) coefficient. Therefore, the improvements in both aspects have positive effects on enhancing the modulation performance. From results, the corresponding EOM by adding such modulation waveguide structure achieves better performance, where the key half-wave-voltage-length product (V_𝜋L) and 3 dB EO bandwidth are 1.78 V·cm and 40 GHz under the electrode gap width of only 6 ㎛, respectively. Moreover, Lower V_𝜋L can also be achieved. With these characteristics, such field-enhanced waveguide structure could further promote the development of LNOI-based EOM.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4573-4594
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• 2020

Announcement protocol in Internet of Vehicles (IoV) is an intelligent application to enhance public safety, alleviate traffic jams and improve transportation quality. It requires communication between vehicles, roadside units and pedestrian to disseminate safety-related messages. However, as vehicles connected to internet, it makes them accessible globally to a potential adversary. Safety-related application requires a message to be reliable, however it may intrude the privacy of a vehicle. Contrarily, if some misbehaviour emerges, the malicious vehicles must be able to traceable and revoke from the network. This is a contradiction between privacy and accountability since the privacy of a user should be preserved. For a secure communication among intelligent entities, we propose a novel announcement protocol in IoV using group signature. To the best of our knowledge, our work is the first comprehensive construction of an announcement protocol in IoV that deploys group signature. We show that our protocol efficiently solves these conflicting security requirements of message reliability, privacy and accountability using 5G communication channel. The performance analysis and simulation results signify our work achieves performance efficiency in IoV communication.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.443-456
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• 2022

An efficient and reasonable resource allocation strategy can greatly improve the service quality of Internet of Vehicles (IoV). However, most of the current allocation methods have overestimation problem, and it is difficult to provide high-performance IoV network services. To solve this problem, this paper proposes a network resource allocation strategy based on deep learning network model DDQN. Firstly, the method implements the refined modeling of IoV model, including communication model, user layer computing model, edge layer offloading model, mobile model, etc., similar to the actual complex IoV application scenario. Then, the DDQN network model is used to calculate and solve the mathematical model of resource allocation. By decoupling the selection of target Q value action and the calculation of target Q value, the phenomenon of overestimation is avoided. It can provide higher-quality network services and ensure superior computing and processing performance in actual complex scenarios. Finally, simulation results show that the proposed method can maintain the network delay within 65 ms and show excellent network performance in high concurrency and complex scenes with task data volume of 500 kbits.