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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | StegoFace an End to End Deep convolutional Printed ID Facial Image Steganography to prevent Photograph Substitution Attack |
| Authors Name: | Sathish Kumar S , Arun Kumar C , Santhanaraj M , Tamilarasan M |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_181329
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| Published Paper Id: | IJNRD2205177 |
| Published In: | Volume 7 Issue 5, May-2022 |
| DOI: | |
| Abstract: | : IDs and MRTDs (Identification and Machine-Readable Travel Documents) are used to identify and authenticate identities in several scenarios such as crossing national borders, in civil applications, sales and purchasing portals, or admission to transaction processing systems. These documents have several security features which mitigate and combat document forgery. As these security systems are difficult to circumvent, criminal attacks on ID verification systems are now focusing on fraudulently obtaining genuine documents and the manipulation of the facial portraits. To reduce risks related to this fraud problem, it is necessary those governments and manufacturer of IDs and MRTDs continuously develop and improve security measures. With this in mind, we introduce the first efficient steganography method - StegoFace - which is optimized for facial images printed in common IDs and MRTDs. StegoFace is an end-to-end facial image steganography model that is formed by n Deep Convolutional Auto Encoder, that can conceal a secret message in a face portrait and, hence, producing the stego facial image, and a Deep Convolutional Auto Decoder, which is able to read a message from the stego facial image, even if it is previously printed and then captured by a digital camera. Facial images encoded with our StegoeFace approach outperform the StegaStamp generated images in terms of their perception quality. Peak Signal-to-Noise Ratio, hiding capacity and imperceptibility results on the test set are used to measure the performance |
| Keywords: | Face detection,steganography, component analysis. |
| Cite Article: | "StegoFace an End to End Deep convolutional Printed ID Facial Image Steganography to prevent Photograph Substitution Attack", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.7, Issue 5, page no.1318-1326, May-2022, Available :http://www.ijnrd.org/papers/IJNRD2205177.pdf |
| Downloads: | 000118756 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2205177 Registration ID: 181329 Published In: Volume 7 Issue 5, May-2022 DOI (Digital Object Identifier): Page No: 1318-1326 Country: tirupathur, tamil nadu, India Research Area: Information Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2205177 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2205177 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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