论文信息 - A Novel Grayscale Image Steganography via Generative Adversarial Network - 字舞流文

A Novel Grayscale Image Steganography via Generative Adversarial Network

Zhihua Gan | Yuhao Zhong | Zhihua Gan | Yuhao Zhong

[1] Yun Q. Shi,et al. Structural Design of Convolutional Neural Networks for Steganalysis , 2016, IEEE Signal Processing Letters.

[2] Jing Dong,et al. SSGAN: Secure Steganography Based on Generative Adversarial Networks , 2017, PCM.

[3] Mo Chen,et al. Deep Residual Network for Steganalysis of Digital Images , 2019, IEEE Transactions on Information Forensics and Security.

[4] Fucai Zhou,et al. Evolutionary-Based Image Encryption with DNA Coding and Chaotic Systems , 2020, WISA.

[5] Tomás Pevný,et al. Using High-Dimensional Image Models to Perform Highly Undetectable Steganography , 2010, Information Hiding.

[6] Jessica J. Fridrich,et al. Universal distortion function for steganography in an arbitrary domain , 2014, EURASIP Journal on Information Security.

[7] Bin Ma,et al. A Novel Grayscale Image Steganography Scheme Based on Chaos Encryption and Generative Adversarial Networks , 2020, IEEE Access.

[8] Jian Sun,et al. Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition , 2015, IEEE Trans. Pattern Anal. Mach. Intell..

[9] Bin Li,et al. Automatic Steganographic Distortion Learning Using a Generative Adversarial Network , 2017, IEEE Signal Processing Letters.

[10] Luc Van Gool,et al. The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.

[11] Jianyi Liu,et al. Invisible steganography via generative adversarial networks , 2018, Multimedia Tools and Applications.