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Security Policy Proposals through PC Security Solution Log Analysis (Prevention Leakage of Personal Information) (PC보안솔루션 로그분석을 통한 보안정책 제안 (개인정보유출 방지))

  • Chae, Hyun Tak;Lee, Sang-Jin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.24 no.5
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    • pp.961-968
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    • 2014
  • In order to prevent leakage of personal information by insiders a large number of companies install pc security solutions like DRM(Digital Right Management), DLP(Data Loss Prevention), Personal information filtering software steadily. However, despite these investments anomalies personal information occurred. To establish proper security policy before implementing pc security solutions, companies can prevent personal information leakage. Furthermore by analyzing the log from the solutions, companies verify the policies implemented effectively and modify security policies. In this paper, we define the required security solutions installed on PC to prevent disclosure of personal information in a variety of PC security solution, plan to integrate operations of the solutions in the blocking personal information leakage point of view and propose security policies through PC security solution log analysis.

An Insight Study on Keyword of IoT Utilizing Big Data Analysis (빅데이터 분석을 활용한 사물인터넷 키워드에 관한 조망)

  • Nam, Soo-Tai;Kim, Do-Goan;Jin, Chan-Yong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2017.10a
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    • pp.146-147
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    • 2017
  • Big data analysis is a technique for effectively analyzing unstructured data such as the Internet, social network services, web documents generated in the mobile environment, e-mail, and social data, as well as well formed structured data in a database. The most big data analysis techniques are data mining, machine learning, natural language processing, and pattern recognition, which were used in existing statistics and computer science. Global research institutes have identified analysis of big data as the most noteworthy new technology since 2011. Therefore, companies in most industries are making efforts to create new value through the application of big data. In this study, we analyzed using the Social Matrics which a big data analysis tool of Daum communications. We analyzed public perceptions of "Internet of things" keyword, one month as of october 8, 2017. The results of the big data analysis are as follows. First, the 1st related search keyword of the keyword of the "Internet of things" has been found to be technology (995). This study suggests theoretical implications based on the results.

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A Comparative Study on Clustering Methods for Grouping Related Tags (연관 태그의 군집화를 위한 클러스터링 기법 비교 연구)

  • Han, Seung-Hee
    • Journal of the Korean Society for Library and Information Science
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    • v.43 no.3
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    • pp.399-416
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    • 2009
  • In this study, clustering methods with related tags were discussed for improving search and exploration in the tag space. The experiments were performed on 10 Delicious tags and the strongly-related tags extracted by each 300 documents, and hierarchical and non-hierarchical clustering methods were carried out based on the tag co-occurrences. To evaluate the experimental results, cluster relevance was measured. Results showed that Ward's method with cosine coefficient, which shows good performance to term clustering, was best performed with consistent clustering tendency. Furthermore, it was analyzed that cluster membership among related tags is based on users' tagging purposes or interest and can disambiguate word sense. Therefore, tag clusters would be helpful for improving search and exploration in the tag space.

A Study on Automatic Text Categorization of Web-Based Query Using Synonymy List (유사어 사전을 이용한 웹기반 질의문의 자동 범주화에 관한 연구)

  • Nam, Young-Joon;Kim, Gyu-Hwan
    • Journal of Information Management
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    • v.35 no.4
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    • pp.81-105
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    • 2004
  • In this study, the way of the automatic text categorization on web-based query was implemented. X2 methods based on the Supported Vector Machine were used to test the efficiency of text categorization on queries. This test is carried out by the model using the Synonymy List. 713 synonyms were extracted manually from the tested documents. As the result of this test, the precision ratio and the recall ratio were decreased by -0.01% and by 8.53%, respectively whether the synonyms were assigned or not. It also shows that the Value of F1 Measure was increased by 4.58%. The standard deviation between the recall and precision ratio was improve by 18.39%.

Design And Implementation of WebDAV Virtual Storage System based on Android (안드로이드 기반의 WebDAV 가상 스토리지 시스템의 설계 및 구현)

  • Kim, Sang-Geon;Byun, Sung-Jun;Lim, Hyo-Taek
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2010.10a
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    • pp.669-671
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    • 2010
  • IStorage is a technology, which can use resources of server PC by using Android Phone supporting wireless internet access. IStorage utilizes resources of server PC through WebDAV protocol. And with GUI interface, Users upload their resources to the server PC and They can perform various kinds of works like Opening, Searching, Deleting and Downloading files. Since it is possible for them to use resources of server PC as if they are originally stored in their mobile devices, there is no limit on using the functions such as watching movies, listening musics and opening document files in real time. We expect this study can to overcome the limitation of storage space and also be a useful technology in the smart phone market.

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A Study of Product Trade Service using Mobile Agent (모바일 에이전트를 이용한 상품거래서비스에 관한 연구)

  • 안성욱;오기욱
    • Journal of the Korea Society of Computer and Information
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    • v.6 no.3
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    • pp.1-10
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    • 2001
  • Recently, way of Electronic Commerce is changing with increment of Internet users. In the previous way of commerce, users used to search for information by themselves. However, for user's convience, it can be done for users from one site. Mobile in order to provide users with such service. By the mobile agent-based Electronic Commerce system, users can get information from one site, and service companies can provide various and useful information to users. This is very important for construction of reliable Electronic Commerce environment, However, in generally used mobile agent-based platforms, the user should know URL information. and it is based on search engines. And as user's requirement levels become higher, they want to be provided with integrated and summarized service. In this paper, we implement product-trading system by applying mobile agent concept in order to satisfy user's requirement of getting required information from one site with minimal mouse click. For implementing the product trading system, E-speak, which is a platform for E-Service, is used And contents are saved as XML documents and data are shared based on these documents.

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The Study on the patient safety culture convergence research topics through text mining and CONCOR analysis (텍스트마이닝 및 CONCOR 분석을 활용한 환자안전문화 융복합 연구주제 분석)

  • Baek, Su Mi;Moon, Inn Oh
    • Journal of Digital Convergence
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    • v.19 no.12
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    • pp.359-367
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    • 2021
  • The purpose of this study is to analyze domestic patient safety culture research topics using text mining and CONCOR analysis. The research method was conducted in the stages of data collection, data preprocessing, text mining and social network analysis, and CONCOR analysis. A total of 136 articles were analyzed excluding papers that were not published. Data analysis was performed using Textom and UCINET programs. As a result of this study, TF (frequency) of patient safety culture-related studies showed that patient safety was the highest, and TF-IDF (importance in documents) was highest in nursing. As a result of the CONCOR analysis, a total of seven clusters were derived: knowledge and attitude, communication, medical service, team, work environment, structure, organization and management that constitute the patient safety culture. In the future, it is necessary to conduct research on the relationship between the establishment of a patient safety culture and patient outcomes.

A Study on Research Paper Classification Using Keyword Clustering (키워드 군집화를 이용한 연구 논문 분류에 관한 연구)

  • Lee, Yun-Soo;Pheaktra, They;Lee, JongHyuk;Gil, Joon-Min
    • KIPS Transactions on Software and Data Engineering
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    • v.7 no.12
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    • pp.477-484
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    • 2018
  • Due to the advancement of computer and information technologies, numerous papers have been published. As new research fields continue to be created, users have a lot of trouble finding and categorizing their interesting papers. In order to alleviate users' this difficulty, this paper presents a method of grouping similar papers and clustering them. The presented method extracts primary keywords from the abstracts of each paper by using TF-IDF. Based on TF-IDF values extracted using K-means clustering algorithm, our method clusters papers to the ones that have similar contents. To demonstrate the practicality of the proposed method, we use paper data in FGCS journal as actual data. Based on these data, we derive the number of clusters using Elbow scheme and show clustering performance using Silhouette scheme.

Digital Literacy of Middle School Students for Informatics Education (정보 교육을 위한 중학생의 디지털 리터러시 수준 분석)

  • Choi, Jeongwon
    • Journal of Convergence for Information Technology
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    • v.12 no.1
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    • pp.83-90
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    • 2022
  • In order for effective informatics education it is premisd that students have digital literacy. But the absence of informatics education for about 10 years has make students have low digital literacy, and as a result, there are many voices in the school field that it is difficult to have a smooth class. Therefore in this study, the elements of digital literacy required to efficiently operate the 2015 middle school informatics curriculum and digital literacy of middle school students was analyzed. As a result, the students showed biased use of the computing devices and software the frequently use. They were inexperienced in using hardware necessary for learning, understanding basic terms for online collaboration, understanding operating systems, information searching, and producing documents. This study is meaningful in that it provides basic data that serves as a guideline for the direction of digital literacy education for effective informatics education.

Topic Analysis of the "Right to be Forgotten" Using Text Mining (텍스트마이닝을 활용한 "잊힐 권리"의 토픽 분석)

  • Lee, So-Hyun;Koo, Bon-Jin
    • Journal of the Korean Society for information Management
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    • v.39 no.2
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    • pp.275-298
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    • 2022
  • This study examined the issues and characteristics that appeared in news and journal articles related to the 'right to be forgotten' using text mining analysis. Data for analysis were collected from 2010 to 2020 with the keyword 'right to be forgotten'. Keyword analysis and topic modeling analysis were performed on the collected data. As a result, in the last 10 years the issues about 'right to be forgotten' are not much different in news and journal articles and the approaches also are similar. However, it confirmed common issues and the partial difference between news and journal articles through comparison. Therefore in Archives and Records Management Studies, it is necessary to discuss derived in this study. In particular common issues are considered first but if there are differences in issues, it is needed to discuss them in various ways. This study is meaningful to understand the meaning and to draw issues that may arise in the future of the 'right to be forgotten'. The results of this study will contribute to be variously discussed on the 'right to be forgotten' in Archives and Records Management Studies.