• Journal of Korea Society of Industrial Information Systems
• /
• v.22 no.4
• /
• pp.65-77
• /
• 2017

We Investigated the Two Additional Effects Regarding the Causal Relationship between the Perceived Risks of cloud Services on the Intention to use the Abandonment Option. First, we Empirically Tested the Moderation Effect of IS Maturity on the Causal Relationship between these Two Variables. Second, we also Investigated the Mediation Effect of Cloud Service Satisfaction on the same Causal Relationship. We could find the Moderation and Mediation Effect only on the Influence of Relational Risk (Which Occurs from the Power Abuse of Cloud Service Providers) on the Intention to sue the Abandonment Option. So, we have better Understanding when and how the Abandonment Option is Attractive in Reducing the Potential Influence of the Relational Risk in using the Cloud Services.

• Journal of Internet Computing and Services
• /
• v.14 no.3
• /
• pp.23-33
• /
• 2013

Recently in the field of IT, cloud computing technology has been deployed rapidly in the current society because of its flexibility, efficiency and cost savings features. However, cloud computing system has a big problem of vulnerability in security. In order to solve the vulnerability of cloud computing systems security in this study, impact types of virtual machine about the vulnerability were determined and the priorities were determined according to the risk evaluation of virtual machine's vulnerability. For analyzing the vulnerability, risk measurement standards about the vulnerability were defined based on CVSS2.0, which is an open frame work; and the risk measurement was systematized by scoring for relevant vulnerabilities. Vulnerability risk standards are considered to suggest fundamental characteristics of vulnerability and to provide the degree of risks and consequently to be applicable to technical guides to minimize the vulnerability. Additionally, suggested risk standard of vulnerability is meaningful as the study content itself and could be used in technology policy project which is to be conducted in the future.

• Journal of Advanced Technology Convergence
• /
• v.1 no.2
• /
• pp.01-09
• /
• 2022

Recently, safety issues in companies and public institutions are no longer a task that can be postponed, and when a major safety accident occurs, not only direct financial loss, but also indirect loss of social trust in the company and public institution is greatly increased. In particular, in the case of a fatal accident, the damage is even more serious. Accordingly, as companies and public institutions expand their investments in industrial safety education and prevention, open AI learning model creation technology that enables safety management services without being affected by user behavior in industrial sites where high-risk situations exist, edge terminals System development using inter-AI collaboration technology, cloud-edge terminal linkage technology, multi-modal risk situation determination technology, and AI model learning support technology is underway. In particular, with the development and spread of artificial intelligence technology, research to apply the technology to safety issues is becoming active. Therefore, in this paper, an open cloud platform design method that can support AI model learning for high-risk site safety management is presented.

• Journal of Information Technology Applications and Management
• /
• v.26 no.3
• /
• pp.135-157
• /
• 2019

Information technology has economic, social and cultural impacts is closely linked to our lives. This information technology is becoming a key to the change of human civilization through connecting people and objects on the earth. In addition, future information technology is becoming more intelligent and personalized with the development of computing technology, and due to the rapid development of alcohol, environment without time and space constraint is realized, Is spreading. Since existing portable storage media are made of physical form, there is a limit to usage due to the risk of loss and limitation of capacity. Cloud services can overcome these limitations. Due to the problems of existing storage media, it is possible to overcome the limitations of storing, managing and reusing information through cloud services. Despite the large number of cloud service users, the existing research has focused mainly on the concept of cloud service and the effect of introduction on the companies. This study aims to conduct a study on individual characteristics that affect the degree of cloud use. We will conduct research on the causes of IT knowledge, personal perception of security, convenience, innovation, economical trust, and platform dependency affecting the intention to use the cloud. These results show that the variables affecting individual 's use of cloud service are influenced by individuals, and this study can be used as a basic data for individuals to use cloud service.

• Journal of Information Processing Systems
• /
• v.15 no.3
• /
• pp.632-644
• /
• 2019

The remote monitoring and warning system for dangerous chemicals is designed with the concept of the Cyber-Physical System (CPS) in this paper. The real-time perception, dynamic control, and information service of major hazards chemicals are realized in this CPS system. The CPS system architecture, the physical layer and the applacation layer, are designed in this paper. The terminal node is mainly composed of the field collectors which complete the data acquisition of sensors and video in the physical layers, and the use of application layer makes CPS system safer and more reliable to monitor the hazardous chemicals. The cloud application layer completes the risk identification and the prediction of the major hazard sources. The early intelligent warning of the major dangerous chemicals is realized and the security risk images are given in the cloud application layer. With the CPS technology, the remote network of hazardous chemicals has been completed, and a major hazard monitoring and accident warning online system is formed. Through the experiment of the terminal node, it can be proved that the terminal node can complete the mass data collection and classify. With this experiment it can be obtained the CPS system is safe and effective. In order to verify feasible, the multi-risk warning based on CPS is simulated, and results show that the system solves the problem of hazardous chemicals enterprises safety management.

• Journal of Information Technology Services
• /
• v.11 no.1
• /
• pp.173-196
• /
• 2012

Cloud computing is provided on demand service via the internet, allowing users to pay for the service they actually use. Since cloud computing is emerging stage in industry, many companies and government consider adopting the cloud computing. Actually a variety of factors may influence on the adopting decision making of cloud computing. The objective of this study is to explore the significant factors affecting the adoption decision of enterprise cloud computing. A research model has been suggested based on TOE framework and outsourcing decision framework. Based on 302 data collected from managers in various industries, the major findings are following. First, the benefit factors of cloud computing service such as agility and cost reduction have direct and positive effects on adoption of the service. Second, lock-in as a risk factor of cloud computing service has a negative effect while security has not. Third, both internal and external environment factors have positive effects on adoption of the service.

• Smart Structures and Systems
• /
• v.30 no.5
• /
• pp.501-511
• /
• 2022

Three-dimensional (3D) models have become crucial for improving civil infrastructure analysis, and they can be used for various purposes such as damage detection, risk estimation, resolving potential safety issues, alarm detection, and structural health monitoring. 3D point cloud data is used not only to make visual models but also to analyze the states of structures and to monitor them using semantic data. This study proposes automating the generation of high-quality 3D point cloud data and removing noise using deep learning algorithms. In this study, large-format aerial images of civilian infrastructure, such as cut slopes and dams, which were captured by drones, were used to develop a workflow for automatically generating a 3D point cloud model. Through image cropping, downscaling/upscaling, semantic segmentation, generation of segmentation masks, and implementation of region extraction algorithms, the generation of the point cloud was automated. Compared with the method wherein the point cloud model is generated from raw images, our method could effectively improve the quality of the model, remove noise, and reduce the processing time. The results showed that the size of the 3D point cloud model created using the proposed method was significantly reduced; the number of points was reduced by 20-50%, and distant points were recognized as noise. This method can be applied to the automatic generation of high-quality 3D point cloud models of civil infrastructures using aerial imagery.

• Journal of information and communication convergence engineering
• /
• v.19 no.3
• /
• pp.166-174
• /
• 2021

A large volume of patient data is generated from various devices used in healthcare applications. With increase in the volume of data generated in the healthcare industry, more wellness monitoring is required. A cloud-enabled analysis of healthcare data that predicts patient risk factors is required. Machine learning techniques have been developed to address these medical care problems. A novel technique called the radix-trie-based Tanimoto kernel regressive infomax boost classification (RT-TKRIBC) technique is introduced to analyze the heterogeneous health data in the cloud to predict the health risks and send alerts. The infomax boost ensemble technique improves the prediction accuracy by finding the maximum mutual information, thereby minimizing the mean square error. The performance evaluation of the proposed RT-TKRIBC technique is realized through extensive simulations in the cloud environment, which provides better prediction accuracy and less prediction time than those provided by the state-of-the-art methods.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.12
• /
• pp.2305-2309
• /
• 2016

Cloud Computing Service should support efficiency and stability. United States of America, for example, provides FedRAMP (Federal Risk and Authorization Management Program) accreditation to certify cloud computing service and hence growth of computing service industry is giving benefits of cost reduction and efficiency to companies. However, the use of computing service brings more risk than ever. Because cloud computing holds all the data of multiple companies, problems such as hacking bring out control loss of service and as a result total data of companies can be lost. Unfortunately, cloud computing certification programs do not have any good solutions for this data loss and companies may lose all the important data without any proper data backup. This paper studies such problems in terms of backup problem and provides Data Availability Zone solution for recovery and safe saving of data so that computing service can offer better efficiency and stability.

• Informatization Policy
• /
• v.21 no.2
• /
• pp.49-66
• /
• 2014

In the last few years, cloud computing has grown from being a promising business concept to one of the fast growing segments of the IT industry. However, as more and more information on individuals and companies are placed in the cloud, concerns on just how safe the computing environment is have gradually increased. In this study, it will be explored if key characteristics of cloud computing services would affect the behavioral intention to use public cloud computing services. A conceptual model is developed and seven research hypotheses are proposed for empirical testing. The proposed model is examined through structural equation analysis. The results show that perceived risk has statistically significant effect on the privacy concern of users and the privacy concern has a negative influence on the trust. Finally, the trust has a positive effect on the attitude and the attitude has statistically significant effect on use intention. Implications of these findings are discussed for both researchers and practitioners and future research issues are raised as well.