• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.2
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• pp.76-86
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• 2016

SQL Injection attacks are the most widely used and also they are considered one of the oldest traditional hacking techniques. SQL Injection attacks are getting quite complicated and they perform a high portion among web hacking. The big data environments in the future will be widely used resulting in many devices and sensors will be connected to the internet and the amount of data that flows among devices will be highly increased. The scale of damage caused by SQL Injection attacks would be even greater in the future. Besides, creating security solutions against SQL Injection attacks are high costs and time-consuming. In order to prevent SQL Injection attacks, we have to operate quickly and accurately according to this data analysis techniques. We utilized data analytics and machine learning techniques to defend against SQL Injection attacks and analyzed the execution plan of the SQL command input if there are abnormal patterns through checking the web log files. Herein, we propose a way to distinguish between normal and abnormal SQL commands. We have analyzed the value entered by the user in real time using the automated SQL Injection attacks tools. We have proved that it is possible to ensure an effective defense through analyzing the execution plan of the SQL command.

• 한국체육학회지인문사회과학편
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• v.56 no.2
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• pp.303-320
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• 2017

This paper seeks to better understand the focal issues and persons related to Rio Olympic soccer games through social data science and analytics. This study collected its data from online news articles and comments specific to KOR during the Olympic football games. In order to investigate the public interests for each game and target persons, this study performed the co-occurrence words analysis. Then after, the study applied the NodeXL software to perform its visualization of the results. Through this application and process, the study found several major issues during the Rio Olympic men's football game including the following: the match between KOR and PIJ, KOR player Heungmin Son, commentator Young-Pyo Lee, sportscaster Woo-Jong Jo. The study also showed the general public opinion expressed positive words towards the South Korean national football team during the Rio Olympics, though there existed negative words as well. Furthermore the study revealed positive attitude towards the commentators and casters. In conclusion, the way to increase the public's interest in big sporting events can be achieved by providing the following: contents that include various professional sports analysis, a capable domain expert with thorough preparation, a commentator and/or caster with artistic sense as well as well-spoken, explanatory power and so on. Multidisciplinary research combined with sports science, social science, information technology and media can contribute to a wide range of theoretical studies and practical developments within the sports industry.

• Journal of Convergence for Information Technology
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• v.10 no.9
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• pp.8-14
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• 2020

The objective of this research is to investigate how implementation of smart factory systems(SFS) effects management accounting(MA). The results based on data collected from 108 Korea small and medium enterprises(SME) confirmed that SFS implementation caused significant MA changes. Estimated regression models revealed that the most important SFS characteristic were the analytical capabilities since it positively influenced MA changes in four dimensions: internal reporting, budgeting, application of modern accounting techniques and MA employee's job. In the segment of budgeting, the quality of implementation of specialized bedgeting software had significant and positive influence. The only negative correlation founded was the one between the uncertainty of business environment and adoption of modern accounting techniques. Results from this study provide that SME should put special focus on implementation of business analytics modules in order to achieve comprehensive benefits in MA prctices.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.695-704
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• 2020

Recently, There has been an increasing of utilization IT, and studies have been conducted on predicting learning results. In this study, Learning activity data were collected that could affect learning outcomes by using learning analysis. The survey was conducted at a university in South Chung-Cheong Province from October to December 2018, with 1,062 students taking part in the survey. First, A Hierarchical regression analysis was conducted by organizing a model of individual, academic, and behavioral factors for learning results to ensure the validity of predictors in machine learning. The model of hierarchical regression was significant, and the explanatory power (R²) was shown to increase step by step, so the variables injected were appropriate. In addition, The linear regression analysis method of machine learning was used to determine how predictable learning outcomes are, and its error rate was collected at about 8.4%.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.207-218
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• 2020

Recently, due to the increase of online reviews and the development of analysis technology, the interest and demand for online review analysis continues to increase. However, previous studies have not considered the emotions contained in each vocabulary may differ from one reviewer to another. Therefore, this study first classifies the customer group according to the customer's grade, and presents the result of analyzing the difference by performing review analysis for each customer group. We found that the price factor had a significant influence on the evaluation of products for customers with high ratings. On the contrary, in the case of low-grade customers, the degree of correspondence between the contents introduced in the mall and the actual product significantly influenced the evaluation of the product. We expect that the proposed methodology can be effectively used to establish differentiated marketing strategies by identifying factors that affect product evaluation by customer group.

• Management & Information Systems Review
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• v.36 no.1
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• pp.273-290
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• 2017

Internet of Things (IoT) is considered to be the next wave of Information Technology transformation after the Internet has changed the process of doing business. Since the domain of IoT ranging from the sensor technology to service to the users is wide, the structure of the research domain is not delineated clearly. To do that we suggest to use the Technology Stack Model proposed by Porter et al.(2014) to measure the maturity level of IoT in organizations. Based on the Stack Model, for the general understandings of IoT, we do keyword analyses on the academic papers whose major research issue is IoT. It is found that the current status of IoT application from the perspectives of cloud and big data analytics is not active, meaning that the real value of IoT has not been realized. We also examine the cases which deal with the part of cloud process which is crucial for value accrual. Based on these findings, we suggest the future direction of IoT research. We also propose that IT is to value chain what IoT is to the Stack Model to derive value in organizations.

• Journal of Contemporary Eastern Asia
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• v.13 no.1
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• pp.5-18
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• 2014

This exploratory study investigates the use of a computational knowledge engine (WolframAlpha) and social networking sites (Gmail, Yahoo and Facebook) by 200 students at De La Salle-College of Saint Benilde, their "friends" and their "friends of friends" during the 2009 through 2013 school years, and how this appears to have added value in knowledge generation. The primary aim is to identify what enhances productiveness in knowledge generation in Philippine Tertiary Education. The phenomenological approach is used, therefore there are no specific research questions or hypotheses proposed in this paper. Considering that knowledge generation is a complex phenomenon, a stochastic modelling approach is also used for the investigation that was developed specifically to study un-deterministic complex systems. A list of salient features for knowledge generation is presented as a result. In addition to these features, various problem types are identified from literature. These are then integrated to provide a proposed framework of inclusive (friendly) and innovative social networks, for knowledge generation in Philippine tertiary education. Such a framework is necessarily multidisciplinary and useful for problem-solving in a globalized and pluralist reality. The implementation of this framework is illustrated in the three parts of the study: Part 1: Online lessons, discussions, and examinations in General Psychology, Introduction to Sociology, and Life and Works of Jose Rizal, for the author's students in De La Salle-College of Saint Benilde; Part 2: Facebook Report analytics of students and teachers, their friends and their friends of friends via WolframAlpha; and Part 3: Social Network Analysis of the people and groups influencing the courses' scope-and-sequence in the new General Education Curriculum for Tertiary Schools and Institutions in the Philippines.

• Journal of Korea Game Society
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• v.18 no.2
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• pp.27-36
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• 2018

In this paper, we propose a win-win network operating platform for mobile games. The characteristics of the service structure suggested is to form a marketing network that can influence the mobile game market by linking with the mobile game industry, and the excellent game content of the game developer in the industrial complex may not disappear. We also would like to propose a network operating platform that would help it enter the market area steadily. The proposed platform technology is used to distribute rapidly through a win-win network between game companies and publishers. When new games are commercialized, they can support continuous target marketing through various data indicators and analytics by the developed platform. In particular, G-Cross marketing strategy is considered to be a low-cost, high-efficiency marketing method in that it can provide users with information about new games by utilizing the given game infrastructure and utilize the user group possessed by each game company.

• The Journal of Society for e-Business Studies
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• v.16 no.3
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• pp.249-261
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• 2011

The rapid growth of e-business market makes new online companies to start and existing offline companies to join in this area. As the number of players of this market grows rapidly, the competition among them is very intense. Many companies invest huge resources to online marketing including search advertisement, email advertisement and banner advertisement. Because these traditional online marketing activities mainly focus on how to invite visitors to their web sites, ROI of these marketing activities are getting lower. Many companies are looking for a new marketing method to escape this situation. In this paper, we propose ROMS (Realtime Online Marketing System) which supports tools to improve conversion ratio of e-commerce sites, ROMS gathers behavioral data of visitors and analyzes it in realtime. ROMS supports live chats, visitor profiling, context analysis, event detection, and live marketing. With ROMS, personalized offers based on visitors' realtime context can be made for each visitor.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.3
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• pp.1155-1162
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• 2014

Background: Despite mixed survival data, the utilization of contralateral prophylactic mastectomy (CPM) for the prevention of a contralateral breast cancer (CBC) has increased significantly over the last 15 years, especially among women less than 40. We set out to look at our own experience with CPM, focusing on outcomes in women less than 40, the sub-population with the highest cumulative lifetime risk of developing CBC. With an extended follow-up, we hoped to demonstrate differences in the long-term disease free survival (DFS) and overall survival (OS) among groups who underwent the procedure (CPM) versus those that did not (NCPM). Materials and Methods: We performed a retrospective review of all breast cancer patients less than age 40 diagnosed at Mount Sinai Medical Center between January 1, 1980 and December 31, 2010 (n=481). Among these patients, 42 were identified as having undergone CPM, while 195 were confirmed as being CPM-free during the observation period. A univariate and multivariate analyses were performed. Results: The CPM group had a significantly higher percentage of patients who were diagnosed between 2000 and 2010 (95.2% vs 40%, p=0.0001). The CPM group had significantly smaller tumors (0-2cm.: 41.7% vs 24.8%, p=0.04). Among the entire group of patients, the overall five- and 10-year DFS were 81.3% and 73.3%, respectively. CPM was significantly associated [HR 2.35 (1.02, 5.41); p=0.046] with 10-year OS, although a similar effect was not observed for five-year OS. Conclusions: We found that CPM has increased dramatically over the last 15 years, especially among white women with locally advanced disease. In patients less than 40, who are thought to be at greatest cumulative risk of secondary breast cancer, CPM provided an OS advantage, regardless of genetics, tumor or patient characteristics, and which was only seen after 10 years of follow-up.