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http://dx.doi.org/10.3837/tiis.2020.12.015

Automated Detection Technique for Suspected Copyright Infringement Sites  

Jeong, Hae Seon (ISAA Lab., Department of AI Convergence Network, Ajou University)
Kwak, Jin (Department of AI Convergence Network, Department of Cyber Security Ajou University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.14, no.12, 2020 , pp. 4889-4908 More about this Journal
Abstract
With the advances in Information Technology (IT), users can download or stream copyrighted works, such as videos, music, and webtoons, at their convenience. Thus, the frequency of use of copyrighted works has increased. Consequently, the number of unauthorized copies and sharing of copyrighted works has also increased. Monitoring is being conducted on sites suspected of conducting copyright infringement activities to reduce copyright holders' damage due to unauthorized sharing of copyrighted works. However, suspected copyright infringement sites respond by changing their domains or blocking access requests. Although research has been conducted for improving the effectiveness of suspected copyright infringement site detection by defining suspected copyright infringement sites' response techniques as a lifecycle step, there is a paucity of studies on automation techniques for lifecycle detection. This has reduced the accuracy of lifecycle step detection on suspected copyright infringement sites, which change domains and lifecycle steps in a short period of time. Thus, in this paper, an automated detection technique for suspected copyright infringement sites is proposed for efficient detection and response to suspected copyright infringement sites. Using our proposed technique, the response to each lifecycle step can be effectively conducted by automatically detecting the lifecycle step.
Keywords
Automated Analysis; Copyright Detection; Copyright Infringement; Monitoring; Piracy Site;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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