• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.4
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• pp.753-773
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• 2019

CV(Connected Vehicle) technology provides safety-related services and user convenience-related services to vehicle. Safety-related services can cause privacy problem by continuously transmitting vehicle information to nearby vehicles or base stations. Therefore, safety-related services should provide vehicle anonymity for privacy protection. However, if convenience-related services such as payment services fail to provide vehicle anonymity, driver information related to safety-related services may also be leaked. In this paper, we design a payment protocol based on ECQV(Elliptic Curve Qu-Vanstone) impicit certificate and group signature that provides BU-anonymity and traceability. The proposed payment protocol makes it impossible to track vehicles from payment transactions history by separating roles of payment system components. Moreover, we define the security requirements that the vehicle payment protocol must satisfy and show that the protocol satisfies the requirements.

• Journal of KIISE
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• v.43 no.12
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• pp.1420-1427
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• 2016

This paper proposes a method taking advantage of Fog computing and SDN in the connected vehicle environment which is having an unstable communication channel and a dynamic topology. For this purpose, the controller should understand the current state of the overall network by maintaining recent network topology, especially, the mobility information of mobile nodes. These are managed by the controller, and are important in unstable conditions in the mobile environment. The mobility levels are divided into 3 categories. We can efficiently exploit that information. By utilizing network state information, we suggest two outcomes. First, we reduce the control message overhead by adjusting the period of beacon messages. Second, we propose a recovery process to prepare the communication failure. We can efficiently recover connection failure through mobility information. Furthermore, we suggest a path recovery by decoupling the cloud level and the fog level in accordance with application data types. The simulation results show that the control message overhead and the connection failure time are decreased by approximately 55% and 5%, respectively in comparison to the existing method.

• Journal of Korean Society for Quality Management
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• v.48 no.1
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• pp.125-147
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• 2020

Purpose: This study would measure the users'perceived overall quality level of A automobile Company, which has leading market power in the domestic automobile market and analyze the causal relationships in the quality value process Model to quality capability, customer value and loyalty based on that. Especially, this study would analyze the relative impacts of the users'perceived risks appearing in the quality value process model of the formation of Quality Factors(QF), Customer Value(CV), and Customer Loyalty(CL) and analyze the moderating effect of the causal relationships among the components. Methods: For an analysis of causal relationships connected to QF, CV, and CL of the customers who purchased Auto manufacturer A's automobile users, 179 users who used within 3 years were utilized as samples for the analysis. As for QF, based on the Garvin(1988), the QF of automobiles were redesigned. For a structural equation analysis of the entire research model, the PLS(S(Partial Least Square) model was utilized. Results: As a result of an analysis, R2 of CV and CL was 0.652 for CV and 0.664 for CL, which was a very stable Goodness of fit. As a result of an analysis of the hypotheses of QF and CV, automobile performance, conformance, aesthetics, serviceability, and durability. In addition, it turned out that the perceived risk had a moderating effect on convenience, service availability, and perceived quality. Conclusion: This study found that the perceived quality risk appearing among automobile users had negative effects on the quality value process model to QF, CV and CL. In contrast, there were factors not affecting the users'quality value process in spite of the perceived risk. These factors can suggest important managerial implications in that they can be utilized as Auto manufacturer A's market-dominant strengths.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.28-41
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• 2022

A road system with CV(Connected Vehicle)s, which is often referred to as a cooperative intelligent transportation system (C-ITS), provides various road information to drivers using an in-vehicle warning system. Road environments with CVs induce drivers to reduce their speed or change lanes to avoid potential risks downstream. Such avoidance maneuvers can be considered to improve driving behaviors from a traffic safety point of view. Thus, empirically evaluating how a given in-vehicle warning information affects driving behaviors, and monitoring of the correlation between them are essential tasks for traffic operators. To quantitatively evaluate the effect of in-vehicle warning information, this study develops a method to calculate compliance rate of drivers where two groups of speed profile before and after road information is provided are compared. In addition, conventional indexes (e.g., jerk and acceleration noise) to measure comfort of passengers are examined. Empirical tests are conducted by using PVD (Probe Vehicle Data) and DTG (Digital Tacho Graph) data to verify the individual effects of warning information based on C-ITS constructed in Seoul metropolitan area in South Korea. The results in this study shows that drivers tend to decelerate their speed as a response to the in-vehicle warning information. Meanwhile, the in-vehicle warning information helps drivers to improve the safety and comport of passengers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3188-3207
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• 2017

In this paper, we propose an image enhancement algorithm to improve license plate extraction rate in various environments (Day Street, Night Street, Underground parking lot, etc.). The proposed algorithm is composed of image enhancement algorithm and license plate extraction algorithm. The image enhancement method can improve an image quality of the degraded image, which utilizes a histogram information and overall gray level distribution of an image. The proposed algorithm employs an interpolated probability distribution value (PDV) in order to control a sudden change in image brightness. Probability distribution value can be calculated using cumulative distribution function (CDF) and probability density function (PDF) of the captured image, whose values are achieved by brightness distribution of the captured image. Also, by adjusting the image enhancement factor of each part region based on image pixel information, it provides a function that can adjust the gradation of the image in more details. This processed gray image is converted into a binary image, which fuses narrow breaks and long thin gulfs, eliminates small holes, and fills gaps in the contour by using morphology operations. Then license plate region is detected based on aspect ratio and license plate size of the bound box drawn on connected license plate areas. The images have been captured by using a video camera or a personal image recorder installed in front of the cars. The captured images have included several license plates on multilane roads. Simulation has been executed using OpenCV and MATLAB. The results show that the extraction success rate is more improved than the conventional algorithms.