• Journal of Industrial Convergence
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• 제20권7호
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• pp.65-71
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• 2022

With the development of ICT, as the era of the 4th industrial revolution arrives, the amount of data is enormous, and as big data technologies emerge, technologies for processing, storing, and processing data are becoming important. In this paper, we propose a system that detects events through monitoring and judges them using hash values because the damage to important files in case of leakage in industries and public places is serious nationally and property. As a research method, an optional event method is used to compare the hash value registered in advance after performing the encryption operation in the event of a file leakage, and then determine whether it is an important file. Monitoring of specific events minimizes system load, analyzes the signature, and determines it to improve accuracy. Confidentiality is improved by comparing and determining hash values pre-registered in the database. For future research, research on security solutions to prevent file leakage through networks and various paths is needed.

• Journal of the Korean BIBLIA Society for library and Information Science
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• 제34권4호
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• pp.259-283
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• 2023

This study acknowledges that prevailing regulation concerning for the long-term preservation of electronic records focus mainly on document types, neglecting the preservation of electronic records from various administrative information systems. With the growing interest in data management in the era of big data, it is imperative to establish clear standards for the long-term preservation of datasets. The choice of preservation format for electronic records is based on the specific standards for each type of electronic record. These standards are formulated according to the significant properties relevant to the electronic record type. This study aims to identify the significant properties of electronic records of each record type, before creating specific preservation format selection criteria for these record types. To achieve this, we reviewed and analyzed R&D studies by the National Archives of Korea and the NARA in the United States. As a result of the research, 9 significant properties were identified for database-type entities, and 7 significant properties were identified for structured data-type entities.

• Journal of Korean Home Economics Education Association
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• 제31권4호
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• pp.149-161
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• 2019

At present, we are at the point of change of the 4th industrial revolution era due to the development of artificial intelligence(AI) and rapid technological innovation that no one can predict until now. This study started from the question of 'What role should home economics education play in the era of the Fourth Industrial Revolution?'. The Fourth Industrial Revolution is characterized by AI, cloud computing, Internet of Things(IoT), big data, and Online to Offline(O2O). It will drastically change the social system, science and technology and the structure of the profession. Since the dehumanization of robots and artificial intelligence may occur, the 4th Industrial Revolution Education should be sought to foster future human resources with humanity and citizenship for the future community. In addition, the implication of education in the fourth industrial revolution, which will bring about a change to a super-intelligent and hyper-connected society, is that the role of education should be emphasized so that humans internalize their values as human beings. Character education should be established as a generalized and internalized consciousness with a concept established in the integration of the curriculum, and concrete practical strategies should be prepared. In conclusion, home economics education in the 4th industrial revolution era should play a leading role in the central role of character education, and intrinsic improvement of various human lives. The fourth industrial revolution will change not only what we do, or human mental and physical activities, but also who we are, or human identity. In the information society and digital society, it is important how quickly and accurately it is possible to acquire scattered knowledge. In the information society, it is required to learn how to use knowledge for human beings in rapid change. As such, the fourth industrial revolution seeks to lead the family, organization, and community positively by influencing the systems that shape our lives. Home economics education should take the lead in this role.

• Journal of Digital Convergence
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• 제17권10호
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• pp.49-58
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• 2019

In the era of the 4th industrial revolution, the development of information technology brought various benefits, but it also increased social interest in privacy issues. As the possibility of personal privacy violation by big data increases, academic discussion about privacy management has begun to be active. While the traditional view of privacy has been defined at various levels as the basic human rights, most of the recent research trends are mainly concerned only with the information privacy of online privacy protection. This limited discussion can distort the theoretical concept and the actual perception, making the academic and social consensus of the concept of privacy more difficult. In this study, we analyze the privacy concept that is exposed on the internet based on 12,000 news data of the portal site for the past one year and compare the difference between the theoretical concept and the socially accepted concept. This empirical approach is expected to provide an understanding of the changing concept of privacy and a research direction for the conceptualization of privacy for current situations.

• Journal of the Society of Disaster Information
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• 제17권3호
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• pp.589-599
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• 2021

Purpose: A reliable indicator of congested traffic speed is essential in providing the information of traffic flow states about motorway sections. The aim of this study is to propose an adaptive indicator of congested speed which is employed for deciding the traffic flow states for individual motorway sections using disaggregated section-based speed data. Method: Typically, the state of traffic flow is categorized into the three: uncongested, mixed, congested states. A method, presented in this study, was developed for identifying boundary speed values of road sections through categorizing the three traffic flow states with individual vehicular speed values. The boundary speed state of each road segment is determined using the speed distributions of mixed and congested traffic states. Result: Analysis results revealed that boundary speed values between mixed and congested states for road sections were similar to those of US and EU criteria (i.e., 48.28~66.0 kph). This indicates that boundary speed values could be different according to road sections. Conclusion: It is expected that the method and indicator, proposed in this study, could be efficaciously used for providing ad-hoc real-time traffic states and computing traffic congestion costs for motorway sections in the era of big data.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제20권2호
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• pp.492-497
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• 2019

This study analysed the legal concept of personal information(PI), which was not differentiated from behavioral information, and established it clearly for invigorating online targeted advertising(OTA), which draw attention in big data era; by selecting Guidelines of Assessment of Data Breach Incident Factors and Guidelines of Measures for No-Identifying Personal Information based on Personal Information Protection Act(PIPA) and Enforcement Decree of the PIPA. As a result, PI was defined as any kind of information relating to (1)a living individual(not group, corporate body or things etc.); (2)makes possibly identify the individual by his or her identifiers such as name, resident registration number, image, etc. (not included if not identify the individual); and (3)including information like attribute values which makes possibly identify any specific individual, if not by itself, but combined with other information which can be actually collected and combined). Specifically, PI includes basic, proper distinguishable, sensitive and other PI. It is suggested that PI concept should be researched continually with digital technology development; the effectiveness of the Guidelines of PI Protection in OTA, the legal principles of PI protection from not only users' but business operators' perspectives and the differentiation between PI and behavioral information in OTA should be researched.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제22권5호
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• pp.317-324
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• 2021

This study deals with keywords from social media on domestic portal sites related to COVID-19, which is spreading widely. The data were collected between January 20 and August 15, 2020, and were divided into three stages. The precursor period is before COVID-19 started spreading widely between January 20 and February 17, the serious period denotes the spread in Daegu between February 18 and April 20, and the stable period is the decrease in numbers of confirmed infections up to August 15. The top 50 words were extracted and clustered based on TF-IDF. As a result of the analysis, the precursor period keywords corresponded to congestion of the Situation. The frequent keywords in the serious period were Nation and Infection Route, along with instability surrounding the Treatment of COVID-19. The most common keywords in all periods were infection, mask, person, occurrence, confirmation, and information. People's emotions are becoming more positive as time goes by. Cafes and blogs share text containing writers' thoughts and subjectivity via the internet, so they are the main information-sharing spaces in the non-face-to-face era caused by COVID-19. However, since selectivity and randomness in information delivery exists, a critical view of the information produced on social media is necessary.

• Journal of the Computational Structural Engineering Institute of Korea
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• 제37권2호
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• pp.77-84
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• 2024

In the fourth industrial-revolution era, the construction industry is transitioning from traditional methods to digital processes. This shift has been challenging owing to the industry's employment of diverse processes and extensive human resources, leading to a gradual adoption of digital technologies through trial and error. One critical area of focus is the safety management at construction sites, which is undergoing significant research and efforts towards digitization and automation. Despite these initiatives, recent statistics indicate a persistent occurrence of accidents and fatalities in construction sites. To address this issue, this study utilizes large-scale language-model artificial intelligence to analyze big data from a construction safety-management information network. The findings are integrated into on-site models, which incorporate real-time updates from detailed design models and are enriched with location information and spatial characteristics, for enhanced safety management. This research aims to develop a big-data-driven safety-management platform to bolster facility and worker safety by digitizing construction-site safety data. This platform can help prevent construction accidents and provide effective education for safety practices.

• Journal of the Korean Association of Geographic Information Studies
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• 제20권4호
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• pp.89-101
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• 2017

Crime occurs differently based on not only place locations and building uses but also the characteristics of the people who use the place and the spatial structures of the buildings and locations. Therefore, if spatial big data, which contain spatial and regional properties, can be utilized, proper crime prevention measures can be enacted. Recently, with the advent of big data and the revolutionary intelligent information era, predictive policing has emerged as a new paradigm for police activities. Based on 7420 actual crime incidents occurring over three years in a typical provincial city, "J city," this study identified the areas in which crimes occurred and predicted risky areas. Spatial regression analysis was performed using spatial big data about only physical and environmental variables. Based on the results, using the street width, average number of building floors, building coverage ratio, the type of use of the first floor (Type II neighborhood living facility, commercial facility, pleasure use, or residential use), this study established a Crime Incident Prediction Model (CIPM) based on Bayesian probability theory. As a result, it was found that the model was suitable for crime prediction because the overlap analysis with the actual crime areas and the receiver operating characteristic curve (Roc curve), which evaluated the accuracy of the model, showed an area under the curve (AUC) value of 0.8. It was also found that a block where the commercial and entertainment facilities were concentrated, a block where the number of building floors is high, and a block where the commercial, entertainment, residential facilities are mixed are high-risk areas. This study provides a meaningful step forward to the development of a crime prediction model, unlike previous studies that explored the spatial distribution of crime and the factors influencing crime occurrence.

• The Journal of Society for e-Business Studies
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• 제21권1호
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• pp.131-145
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• 2016

This study built the theoretical frameworks for empirical analysis based on the analysis of the relationship among the concepts of risk of information privacy, the policy of information privacy via the provision studies. Also, in order to analyze the relationship among the factors such as the concern of information privacy, trust, intention to offer the personal information, this study investigated the concepts of information privacy and studies related with the privacy, and established a research model about the information privacy. Followings are the results of this study: First, the information privacy risk has the positive effects upon the information privacy concern and it has the negative effects upon the trust. Second, the information privacy policy has the positive effects upon the information privacy concern and it has the negative effects upon the trust. Third, the information privacy concern has the negative effects upon the trust. At last, the information privacy concern has the negative effects upon the provision intention of personal information and the trust has positive effects upon the offering intention of personal information.