Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Tsai, Min-Jen | en_US |
dc.contributor.author | Liu, Jung | en_US |
dc.date.accessioned | 2014-12-08T15:35:45Z | - |
dc.date.available | 2014-12-08T15:35:45Z | - |
dc.date.issued | 2013 | en_US |
dc.identifier.isbn | 978-1-4673-5762-3; 978-1-4673-5760-9 | en_US |
dc.identifier.issn | 0271-4302 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/24147 | - |
dc.description.abstract | Recently, digital forensics, which involves the collection and analysis of the origin digital device, has become an important issue. Digital content can play a crucial role in identifying the source device, such as serve as evidence in court. To achieve this goal, we use different texture feature extraction methods such as gray-level co-occurrence matrix (GLCM) and discrete wavelet transform (DWT), to analyze the Chinese printed source in order to find the source of printers. Furthermore, we also explore the optimum feature subset by using feature selection techniques and using support vector machine (SVM) to identify the source model of the documents. The average experimental results attain a 98.64% identification rate which is significantly superior to the existing known method by 1.2%. This higher testing performance demonstrates that the proposed identification method is very useful for source laser printer identification. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Digital forensics | en_US |
dc.subject | Graylevel co-occurrence Matrix (GLCM) | en_US |
dc.subject | Discrete Wavelet Transform (DWT) | en_US |
dc.subject | Support Vector Machines (SVM) | en_US |
dc.title | Digital Forensics for Printed Source Identification | en_US |
dc.type | Proceedings Paper | en_US |
dc.identifier.journal | 2013 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS) | en_US |
dc.citation.spage | 2347 | en_US |
dc.citation.epage | 2350 | en_US |
dc.contributor.department | 資訊管理與財務金融系 註:原資管所+財金所 | zh_TW |
dc.contributor.department | Department of Information Management and Finance | en_US |
dc.identifier.wosnumber | WOS:000332006802141 | - |
Appears in Collections: | Conferences Paper |