• Journal of the Korean Society for Library and Information Science
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• v.55 no.1
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• pp.493-519
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• 2021

The purpose of this study is to propose a plan to implement the comprehensive linking system centered on identifiers in order to provide seamless academic information services to researchers. To achieve this goal, interviews were conducted with 17 researchers from five centers and one secretariat belonging to KISTI. The contents of the interview are about the establishment and management status of the identifier of the academic information service DB. As a result of the interview, it was found that the identification rate for identifiers such as KOI was high in the case of domestic articles DB, but the identification rate for global identifiers such as ORCID was low in the case of foreign articles DB except for DOI. To solve this problem, this study proposes the council for joint use of a comprehensive linking system to build the comprehensive linking system model centered on identifiers. The joint use council will be organized around domestic academic information distribution institutions, and the council is expected to discover and implement new services through ID linkage by collecting foreign identifiers.

• 산림경영
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• s.132
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• pp.32-33
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• 1998

• TTA Journal
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• s.84
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• pp.111-122
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• 2002

• TTA Journal
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• s.98
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• pp.148-156
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• 2005

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.33-40
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• 2021

Automatic Speech Recognition(ASR) is a technology that analyzes human speech sound into speech signals and then automatically converts them into character strings that can be understandable by human. Speech recognition technology has evolved from the basic level of recognizing a single word to the advanced level of recognizing sentences consisting of multiple words. In real-time voice conversation, the high recognition rate improves the convenience of natural information delivery and expands the scope of voice-based applications. On the other hand, with the active application of speech recognition technology, concerns about related cyber attacks and threats are also increasing. According to the existing studies, researches on the technology development itself, such as the design of the Automatic Speaker Verification(ASV) technique and improvement of accuracy, are being actively conducted. However, there are not many analysis studies of attacks and threats in depth and variety. In this study, we propose a cyber attack model that bypasses voice authentication by simply manipulating voice frequency and voice speed for AI voice recognition service equipped with automated identification technology and analyze cyber threats by conducting extensive experiments on the automated identification system of commercial smartphones. Through this, we intend to inform the seriousness of the related cyber threats and raise interests in research on effective countermeasures.

• The Monthly Technology and Standards
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• s.88
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• pp.44-44
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• 2009

• Journal of Information Management
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• v.16 no.2
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• pp.67-75
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• 1983

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.711-713
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• 2013

Various human resource information of the world can be found according to spread of social network such as facebook and twitter. There are an amounts of researcher information on the science and technology area but it is difficult to find a suitable researcher for research or business such as research partner, because researcher information is not systematically arranged. To solver this problem, we are constructing authority data system for science and technology based on authority information of overseas academic papers. In this paper, in order to construct the authority data, we extracts author identification elements from millions of overseas academic papers, which are published from 1994 to 2012. There are more than 50 author identification elements such as author name, affiliation, paper title, publisher, year, keywords, co-author, co-author's affiliation in Korean, English, Chinese, and Japanese. We construct the element database by extracting and storing an author identification information based on the elements from overseas academic papers. Future works includes that the authority database for overseas academic papers is constructed by storing an academic activities of researchers after author clustering with these extracted elements. The authority data is used to improve the researcher information utilization and activate community to find a suitable research partner or a business examiner.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.553-561
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• 2019

In this study, the method of quality measurement for the statistical usefulness of de-identified data was examined in terms of prediction accuracy by statistical modeling. In the era of the 4th industrial revolution, effective use of big data is essential to innovation through information and communication technology, but personal information issues are constrained to actively utilize big data. In order to solve this problem, de-identification guidelines have been established and the possibility of actual re-identification of personal information has become very low due to the utilization of various de-identification methods. On the other hand, strong de-identification can have side effects that degrade the usefulness of the data. We have studied the quality of statistical usefulness of the de-identified data by KLT model which is a representative de-identification method, A case study was conducted to see how statistical accuracy of prediction is degraded by de-identification. We also proposed a new measure of data usefulness of the de-identified data by quantifying how much data is added to the de-identified data to restore the accuracy of the predictive model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.5
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• pp.2402-2409
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• 2011

The voice has distinguishable acoustic properties of speaker as well as transmitting information. The speaker recognition is the method to figures out who speaks the words through acoustic differences between speakers. The speaker recognition is roughly divided two kinds of categories: speaker verification and identification. The speaker verification is the method which verifies speaker himself based on only one's voice. Otherwise, the speaker identification is the method to find speaker by searching most similar model in the database previously consisted of multiple subordinate sentences. This paper composes feature vector from extracting MFCC coefficients and uses the dynamic time warping algorithm to compare the similarity between features. In order to describe common characteristic based on phonological features of spoken words, two subordinate sentences for each speaker are used as the training data. Thus, it is possible to identify the speaker who didn't say the same word which is previously stored in the database.