arXiv Open Access 2018

StegNet: Mega Image Steganography Capacity with Deep Convolutional Network

Pin Wu Yang Yang Xiaoqiang Li

Lihat Sumber

Abstrak

Traditional image steganography often leans interests towards safely embedding hidden information into cover images with payload capacity almost neglected. This paper combines recent deep convolutional neural network methods with image-into-image steganography. It successfully hides the same size images with a decoding rate of 98.2% or bpp (bits per pixel) of 23.57 by changing only 0.76% of the cover image on average. Our method directly learns end-to-end mappings between the cover image and the embedded image and between the hidden image and the decoded image. We~further show that our embedded image, while with mega payload capacity, is still robust to statistical analysis.

Topik & Kata Kunci

cs.MM

Penulis (3)

Pin Wu

Yang Yang

Xiaoqiang Li

Format Sitasi

APA MLA BibTeX

Wu, P., Yang, Y., Li, X. (2018). StegNet: Mega Image Steganography Capacity with Deep Convolutional Network. https://arxiv.org/abs/1806.06357

Akses Cepat

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Informasi Jurnal

Tahun Terbit: 2018
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓