TY - GEN
T1 - Coverless image steganography framework using distance local binary pattern and convolutional neural network
AU - Sandoval-Bravo, Luis A.
AU - Ponomaryov, Volodymyr I.
AU - Reyes-Reyes, Rogelio
AU - Cruz-Ramos, Clara
N1 - Publisher Copyright:
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
PY - 2020
Y1 - 2020
N2 - Steganography in digital images commonly uses a carrier image and embeds secret data into to create the stego-image by spatial or frequency domain methods, which directly modifies the bits of the carrier image, altering the intensity of the pixels and leaving traces of modification caused by the embedding of data in the carrier image, which makes successful steganalysis possible. This paper proposes a digital image steganography framework without embedding data directly into the images that extracts the secret-data from the convolutional neural network trained with the distance local binary pattern images from an indexed image database. Experimental results demonstrate that the proposed framework is resistant to common steganalysis tools, intentional and unintentional image attacks such as luminance and contrast changes, rescaling, noise addition and compression.
AB - Steganography in digital images commonly uses a carrier image and embeds secret data into to create the stego-image by spatial or frequency domain methods, which directly modifies the bits of the carrier image, altering the intensity of the pixels and leaving traces of modification caused by the embedding of data in the carrier image, which makes successful steganalysis possible. This paper proposes a digital image steganography framework without embedding data directly into the images that extracts the secret-data from the convolutional neural network trained with the distance local binary pattern images from an indexed image database. Experimental results demonstrate that the proposed framework is resistant to common steganalysis tools, intentional and unintentional image attacks such as luminance and contrast changes, rescaling, noise addition and compression.
KW - Convolutional neural network
KW - Coverless Steganography
KW - Digital images
KW - Steganalysis
KW - Steganography without data embedding
KW - distance local binary pattern
UR - http://www.scopus.com/inward/record.url?scp=85085731718&partnerID=8YFLogxK
U2 - 10.1117/12.2556310
DO - 10.1117/12.2556310
M3 - Contribución a la conferencia
AN - SCOPUS:85085731718
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Real-Time Image Processing and Deep Learning 2020
A2 - Kehtarnavaz, Nasser
A2 - Carlsohn, Matthias F.
PB - SPIE
T2 - Real-Time Image Processing and Deep Learning 2020
Y2 - 27 April 2020 through 8 May 2020
ER -