• 한국디지털정책학회:학술대회논문집
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• 2006.06a
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• pp.45-53
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• 2006

Ever since the computer came into being in early 20th century, rapid development of the information technology has led to the opening of the ubiquitous age where daily works can be done anywhere, anytime, and with any devices. The information technology has drawn attention from Customs around the world as a key means to fulfill multi-faced responsibilities of strengthening regional cooperation in the international trade, simplifying clearance procedures, expediting logistics flow, and ensuring security in the global supply chain. Korea Customs Service, which began the informatization effort by establishing the electronic export declaration system in 1992, completed the 100% electronic clearance system in 2000, with a number of countries now conducting benchmarking studies on the successful use of IT by KCS. This paper is to address the changes brought to the Customs administration in the information age, the progress and achievement of the Customs informatization as a proactive strategy to deal with the changing environment, and the exportation to overseas administration of the e-clearance system of KCS which strives to become the global leader of Customs informatization. The exportation. in particular, will not only lead to increased foreign currency earnings and shared know how, but also create an opportunity to reflect Korea's system in the standardization of Customs procedures around the world.

• International Commerce and Information Review
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• v.14 no.1
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• pp.273-299
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• 2012

Japan's customs ensure the safety of international trade and trade facilitation has been pursuing. To do this, AEO was introduced to this system and expanding the supply chain currently maintain security and improve customer convenience is necessary to continue to be pursued. In addition, the imposition of customs duties in accordance with changes in the environment to Tariff offenders and increased the amount of tax evasion, smuggling of narcotics, including amphetamines and response, the increase in access is required. In this paper, Japan's tariff and customs administration for the change in the future for Japan-related materials around the Treasury Department's analysis will attempt to draw implications for this.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.1
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• pp.1-7
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• 2019

The objective of this study is to examine the trends in big data. Research abstracts were extracted from 4,019 articles, published between 1995 and 2018, on Web of Science and were analyzed using topic modeling and time series analysis. The 20 single-term topics that appeared most frequently were as follows: model, technology, algorithm, problem, performance, network, framework, analytics, management, process, value, user, knowledge, dataset, resource, service, cloud, storage, business, and health. The 20 multi-term topics were as follows: sense technology architecture (T10), decision system (T18), classification algorithm (T03), data analytics (T17), system performance (T09), data science (T06), distribution method (T20), service dataset (T19), network communication (T05), customer & business (T16), cloud computing (T02), health care (T14), smart city (T11), patient & disease (T04), privacy & security (T08), research design (T01), social media (T12), student & education (T13), energy consumption (T07), supply chain management (T15). The time series data indicated that the 40 single-term topics and multi-term topics were hot topics. This study provides suggestions for future research.

• Korea Trade Review
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• v.47 no.5
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• pp.289-304
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• 2022

Korea's LNG and crude oil are the most important energy and export raw materials, but 100% import resources by overseas. However, tanker shipping companies, which play the most crucial role in energy cargo security, are very small in number and size, which can be a factor in the supply chain crisis. Therefore, this paper studied the policy of expanding tanker transportation necessary for the transport of crude oil and LNG in Korea. In the existing literature, there was no policy study necessary for tanker ships, but referring only to the importance of overseas energy development and transportation, so we tried to derive various demands necessary for expanding the tanker fleet through expert interviews and AHP which was conducted on 89 related energy institutions to derive policies and their priorities. The results of the study are as follows. As for the policy, the financial support policy was the highest priority, followed by the business and the mutual cooperation policy of related agencies. Tax support (22.6%) and ship financing (19.4%) were the highest priorities, followed by the Energy Intermediate Promotion Act (11.9%), Tanker Guarantee Insurance (10.6%), Energy Budget Independence (9.3%), and Korea Trader Development (8.2%). Energy governance (6.3%), information center establishment (6.2%), and energy procurement committee (5.5%) ranked seventh, eighth, and ninth. The research results show that it is necessary to supply sufficient ships to the market through the expansion of ship finance for tankers and to follow business support policies such as guarantee insurance. In addition, it was also possible to derive that the financial resources need to be determined by law and independent budgets for consistency and continuity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2B
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• pp.296-301
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• 2010

Radio frequency identification(RFID) system can identify an object using wireless transmission. RFID applications are numerous and far reaching. The most interesting and widely used applications are supply chain management for companies. Currently, RFID tags must be detached or killed for security and privacy reasons when tagged objects are purchased. In this paper, we present a new architecture that transfers information about products from the electronic product code information services (EPCIS) server of a company to an individual's personal purchases management (PPM) server when products with RFID codes are sold. It solves the security and privacy issues without detaching the tag. Moreover, the PPM server described in this paper allows customers to handle the expiration dates, updates, location management, and group management of products.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.6
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• pp.57-68
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• 2004

Recently, Radio Frequency Identification (RFID) systems stands in the spotlight of industry as a common and useful tool in manufacturing, supply chain management (SCM) and stock management. In the near future, low-cost RFID Electronic Product Code; (EPC) or smart-labels may be a practical replacement for optical barcodes on consumer items. However, manufacturing cheap and small RFID tags, and developing secure RFID authentication Protocols are problems which need to be solved. In spite of advances in semiconductor technology, computation and storage ability of the tag are so limited that it is difficult and too expensive to apply existing crypto-systems to RFID tags. Thus it is necessary to create a new protocol which would require less storage space and lower computation costs and that is secure in the RFID system's environments. In this paper, we propose a RFID authentication protocol that is secure against location tracking and spoofing attacks. Our protocol can be used as a practical solution for privacy protection because it requires less computations in database than the previous RFID authentication protocol.

• Ocean and Polar Research
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• v.45 no.1
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• pp.23-31
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• 2023

The core of the foreign policy of the Yoon Suk-yeol government is the promotion of active economic and security diplomacy as indicated in Policy Tasks No. 98. To this end, economic consultative bodies such as Regional Comprehensive Economic Partnership Agreement(RCEP), Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP), and Indo-Pacific Economic Framework (IPEF) are taking the initiative to respond to the formation of supply chain, human rights, environment, and digital-related norms, and actively support Korean companies' overseas expansion. Due to the nature of the Ministry of Oceans and Fisheries (MOF) as an organization established centered on the space of the ocean, the MOF faces difficulties in bringing the functions of other ministries into the space of the ocean. Considering the vision, objectives, and detailed plans of the MOF, the contribution of the MOF in the field of active economic security, one of the main foreign policies of the Yoon Suk-yeol government, is perhaps too obvious. However, since the re-launch of the MOF, the ODA budget for the oceans and fisheries sector is too small compared to other ministries, so even if new policy demands are discovered, there are many difficulties in implementing these policies in practice. Recognizing these problems, this paper examines the background and contents of foreign policies that have been promoted for the efficient promotion of RCEP, CPTPP and IPEF and introduces the areas of cooperation in the oceans and fisheries sector in these foreign policies.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.1-7
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.210-216
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.5
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• pp.59-69
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• 2009

RFID tag search system which is used to find a specific tag has an application such as asset management, supply chain, and this search scheme has been given much attention so far. In RFID tag search system, especially, mobility of the reader is important in order to search tags. Therefore, even though the handheld reader cannot connect with the central database because of unreliable wireless connection or remote location, handheld reader should search the specific tag without help of the central database. In addition, in RFID tag search system, users hold not the tag but the reader, the privacy of users should be considered. Since the signal strength of the reader is stronger than that of the tag, the privacy of the reader holder is very important. Recently, in order to solve these problems, a number of RFID tag search schemes have been proposed. However, since these schemes did not consider the privacy of reader holders, there are serious privacy breaches of reader holders. In this paper, we propose efficient RFID tag search protocol for passive tags. Our proposed scheme preserves the privacy of reader holders.