• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.77-84
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• 2021

In this paper, we propose a system that uses image data and beacon data to classify authorized and unauthorized perosn who are allowed to enter a group facility. The image data collected through the IP camera uses YOLOv4 to extract a person object, and collects beacon signal data (UUID, RSSI) through an application to compose a fingerprinting-based radio map. Beacon extracts user location data after CNN-LSTM-based learning in order to improve location accuracy by supplementing signal instability. As a result of this paper, it showed an accuracy of 93.47%. In the future, it can be expected to fusion with the access authentication process such as QR code that has been used due to the COVID-19, track people who haven't through the authentication process.

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.142-146
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• 2007

Digital Rights Management (DRM) technology has been widely used for protecting the digital contents over the recent years. But the digital contents protected by DRM are vulnerable to various video memory capture programs when DRM packaged contents are decrypted on the consumers' multimedia devices. To make up for this kind of DRM security holes the Forensic Marking (FM) technology is being deployed into the content protection area. Most leading DRM companies as well as big electronics companies like Thomson and Philips already have commercial FM solutions. Forensic Marking technology uses the digital watermarking to insert the user information such as user id, content playing time and etc. into the decrypted and decoded content at the playback time on the consumer devices. When the content containing watermarked user information (Forensic Mark) is illegally captured and distributed over the Internet, the FM detection system takes out the inserted FM from the illegal contents and informs contents service providers of the illegal hacker's information. In this paper the requirements and test conditions are discussed for the commercial Forensic Marking systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.131-137
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• 2014

Although illegal reproduction of cartoon books are prevalent with rapid growth of webhard services and smartphone use, fingerprinting technology for product identification, as seen in music and videos, has not been developed yet. This leads to indiscriminate illegal reproduction of cartoon books, causing great amount of copyright damages from copyright infringement of the rightful owners. The copyright R&D project granted from the Korea Copyright Permission (Project Title: Identification and Copy Protection Technology of Bookscaned Text/Comic Books) has been carried out in order to develop technology to effectively identify illegal reproduction and distribution of scanned cartoon books. The developed technology will contribute to increase of royalty payments and robust ecosystem of cartoon book markets. The study is to propose an enhanced implementation model for identification of scanned cartoon books on the basis of hierarchical symmetric difference feature algorithms adopted from existing feature extraction algorithms for video.