• Journal of the Korea Society of Computer and Information
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• v.14 no.5
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• pp.65-75
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• 2009

The development of IT technology, Internet popularity is increasing geometrically. However, as its side effect, the intrusion behaviors such as information leakage for key system and infringement of computation network etc are also increasing fast. The attack traffic detection method which is suggested in this study utilizes the Snort, traditional NIDS, filters the packet with false positive among the detected attack traffics using Nmap information. Then, it performs the secondary filtering using nessus vulnerability information and finally performs correlation analysis considering appropriateness of management system, severity of signature and security hole so that it could reduce false positive alarm message as well as minimize the errors from false positive and as a result, it raised the overall attack detection results.

• Journal of the Korean Institute of Landscape Architecture
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• v.36 no.4
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• pp.100-110
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• 2008

The purposes of the study were to analyze the effects of determinants and persuasive messages on the willingness-to-pay cultural & heritage assets' admission fees. Recently visitors have responded to a nationwide boycott of the fees within national parks due to feelings of disapproval and resentment. Data were collected through onsite surveys of 302 visitors in the Mt. Gyeryong National Park. Regression analysis and two-way ANOVA were employed to obtain the results. The results indicate that credit card payment was the most prominent predictor of willingness-to-pay at the .05 level. The second highest coefficient was obtained in the condition levying of admission fees and parking fees at the same time, providing temple interpretive services, followed by free days for everyone on special days each month. In addition, the most persuasive message was the descriptive content, which stated that fees were profoundly committed to the protection of the cultural heritage for future generations. As a result, it is effective to continually persuade visitors to use posters or reminders that stress the preservation of cultural assets at the entrance gate.

• Journal of KIISE:Databases
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• v.37 no.5
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• pp.258-266
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• 2010

In this paper, we introduce a novel method to predict next update of blogs. The number of RSS feeds registered on meta-blogs is on the order of several million. Checking for updates is very time consuming and imposes a heavy burden on network resources. Since blog search engine has limited resources, there is a fix number of blogs that it can visit on a day. Nevertheless we need to maximize chances of getting new data, and the proposed method which predicts update probability on blogs could bring better chances for it. Also this work is important to avoid distributed denial-of-service attack for the owners of blogs. Furthermore, for the internet as whole this work is important, too, because our approach could minimize traffic. In this study, we assumed that there is a specific pattern to when a blogger is actively posting, in terms of days of the week and, more specifically, hours of the day. We analyzed 15,119 blogs to determine a blogger's posting preference. This paper proposes a method to predict the update probability based on a blogger's posting history and preferred days of the week. We applied proposed method to 12,115 blogs to check the precision of our predictions. The evaluation shows that the model has a precision of 0.5 for over 93.06% of the blogs examined.