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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Bin Xia Xingming Sun Jiaohua Qin |
| Copyright Year | 2009 |
| Abstract | In this paper, we propose a new method to detect least significant bit (LSB) matching steganography which is based on neighbourhood node degree histogram characteristic function (NDHCF). First we calculate the center of mass (COM) of the NDHCF then embed another random secret message to compute the alteration rate of the NDHCF COM. We select NDHCF COM and the alteration rate as features and use support vector machines as a classifier. Experimental results demonstrate that the proposed method is efficient to detect the LSB matching stegonagraphy on compressed or uncompressed images and has superior results compared with other recently proposed algorithms. |
| Starting Page | 79 |
| Ending Page | 82 |
| File Size | 287263 |
| Page Count | 4 |
| File Format | |
| ISBN | 9780769538433 |
| DOI | 10.1109/MINES.2009.51 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-11-18 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Gray-scale Information hiding LSB matching Histograms Steganography Image coding Image analysis Steganalysis Information security Feature extraction Computer networks Computer security Pixel Neighbourhood node degree histogram |
| Content Type | Text |
| Resource Type | Article |
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