• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.526-534
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• 2022

In August 2014, the Ministry of Land, Infrastructure, and Transport (MOLIT) devised an innovative ITS measure in which private and public sectors share roles to maximize investment efficiency and effectiveness in collecting and offering traffic information that had been separately implemented by the state and private sector. The main details of the innovative measure include the following: For communication information, the information collected by the private sector is used, and the state concentrates on safety-related information collection, such as unexpected situations, including construction, accidents, and deteriorating weather conditions. Consequently, safety-related information is offered in real-time through smartphones and navigation, in addition to electric road signs that have limitations in providing unexpected real-time situations due to installation at specific spots. This study presented a connected traffic information priority coordination plan to improve the accuracy of traffic information offering by analyzing problems of related traffic information, including a general national highway case study to enhance the efficiency of national highway ITS implementation, according to actual public-private traffic information sharing. In addition, this study reviewed whether to operate or demolish the information collection equipment by analyzing traffic volume level and availability of related traffic information in the existing ITS operation sections and presented ITS collection equipment installation judgment standards based on the cases concerned.

• 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.