• Journal of Information Technology Applications and Management
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• v.16 no.1
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• pp.21-36
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• 2009

As the World Wide Web (WWW) has become a major channel for information delivery, the data accumulated in the Internet increases at an incredible speed, and it derives the advances of information search technologies. It is the search engine that solves the problem of information overloading and helps people to identify relevant information. However, as search engines become a powerful tool for finding information, the opportunities of plagiarizing have increased significantly in e-Learning. In this paper, we developed an online plagiarism detection system for detecting plagiarized documents that incorporates the functions of search engines and acts in exactly the same way of plagiarizing. The plagiarism detection system uses morpheme analysis to improve the performance and sentence-based comparison to investigate document comes from multiple sources. As a result of applying this system in e-Learning, the performance of plagiarism detection was improved.

• Journal of Digital Contents Society
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• v.7 no.3
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• pp.199-205
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• 2006

Due to easy access to information in our digital society, there are many cases of illegal counterfeiting and usage of personal information. Producing information with investment and effort is important indeed, but managing and protecting information is becoming a furthermore important issue. This is to promote a new detecting theory and solution for cases of intellectual property violations and plagiarizing digital contents.

• Journal of the Korea Society of Computer and Information
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• v.10 no.3 s.35
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• pp.259-265
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• 2005

The purpose of this study is for designing a illegal query detection system using Winpcap library for unauthorized access by internal person. The illegal query detection can be possible detecting the data in out of access control or searching illegal data by plagiarizing other user ID. The system used in this paper collects packets and analyzes the data related to SQL phrase among them, and selects the user's basic information by comparing the dispatch of MAC address and user's hardware information constructed previously. If the extracted information and user's one are different, it is considered as an illegal query. It is expected that the results of this study can be applied to reducing the snaking off unprotected data, and also contributed to leaving the audit records using user's access log which can be applied to the pattern analysis.

• The Journal of Korean Association of Computer Education
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• v.13 no.6
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• pp.79-89
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• 2010

In this paper, we proposed a method to find out similar sentences from documents to detect plagiarized documents. The proposed model adapts LSA and N-gram techniques to detect every type of Korean plagiarized sentence type. To evaluate the performance of the model, we constructed experimental data using students' essays on the same theme. Students made their essay by intentionally plagiarizing some reference documents. The experimental results showed that our proposed model outperforms the conventional N-gram model, Vector model, LSA model in precision, recall, and F measures.