• Informatization Policy
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• v.23 no.3
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• pp.26-42
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• 2016

Recently, with the rapid growth of the O2O market, Fintech combining the finance and ICT technology is drawing attention as innovation to lead "O2O of finance", along with Fintech-based payment, authentication, security technology and related services. For new technology industries such as Fintech, technical sources, related systems and regulations are important but previous studies on Fintech lack in-depth research about systems and technological trends of the domestic Fintech industry. Therefore, this study aims to analyze domestic Fintech trends and find the insights for the direction of technology and systems of the future domestic Fintech industry by comparing Kakao Pay and Samsung Pay, the two domestic representative mobile payment services. By conducting a complete enumeration survey about the tweets mentioning Fintech until June 2016, this study visualized topics extraction, sensitivity analysis and keyword analyses. According to the analysis results, it was found that various topics have been created in the technologies and systems between 2014 and 2016 and different keywords and reactions were extracted between topics of Samsung Pay based on "devices" such as Galaxy and Kakao Pay based on "service" such as KakaoTalk. This study contributes to analyzing the unstructured data of social media by period by using social media mining and quantifying the expectations and reactions of consumers to services through the sentiment analysis. It is expected to be the foundation of Fintech industry development by presenting a strategic direction to Fintech related practitioners.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.374-380
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• 2017

The Internet of Things (IoT) refers to intelligent technologies and services that connect all things to the internet so they can interactively communicate with people, other things, and other systems. The development of the IoT environment accompanies advances in network protocols applicable to more lightweight and intelligent sensors, and lightweight and diverse environments. The development of those elemental technologies is promoting the rapid progress in smart car environments that provide safety features and user convenience. These developments in smart car services will bring a positive effect, but can also lead to a catastrophe for a person's life if security issues with the services are not resolved. Although smart cars have various features with different types of communications functions to control the vehicles under the existing platforms, insecure features and functions may bring various security threats, such as bypassing authentication, malfunctions through illegitimate control of the vehicle via data forgery, and leaking of private information. In this paper, we look at types of smart car services in the IoT, deriving the security threats from smart car services based on various scenarios, suggesting countermeasures against them, and we finally propose a safe smart car application plan.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.33-40
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• 2021

Automatic Speech Recognition(ASR) is a technology that analyzes human speech sound into speech signals and then automatically converts them into character strings that can be understandable by human. Speech recognition technology has evolved from the basic level of recognizing a single word to the advanced level of recognizing sentences consisting of multiple words. In real-time voice conversation, the high recognition rate improves the convenience of natural information delivery and expands the scope of voice-based applications. On the other hand, with the active application of speech recognition technology, concerns about related cyber attacks and threats are also increasing. According to the existing studies, researches on the technology development itself, such as the design of the Automatic Speaker Verification(ASV) technique and improvement of accuracy, are being actively conducted. However, there are not many analysis studies of attacks and threats in depth and variety. In this study, we propose a cyber attack model that bypasses voice authentication by simply manipulating voice frequency and voice speed for AI voice recognition service equipped with automated identification technology and analyze cyber threats by conducting extensive experiments on the automated identification system of commercial smartphones. Through this, we intend to inform the seriousness of the related cyber threats and raise interests in research on effective countermeasures.