Coverless image steganography based on DenseNet feature mapping

Qiang Liu,Yao Qiu,Jiaohua Qin,Yun Tan,Xuyu Xiang

doi:10.1186/s13640-020-00521-7

Abstract

Since the concept of coverless information hiding was proposed, it has been greatly developed due to its effectiveness of resisting the steganographic tools. Most existing coverless image steganography (CIS) methods achieve excellent robustness under non-geometric attacks. However, they do not perform well under some geometric attacks. Towards this goal, a CIS algorithm based on DenseNet feature mapping is proposed. Deep learning is introduced to extract high-dimensional CNN features which are mapped into hash sequences. For the sender, a binary tree hash index is built to accelerate index speed of searching hidden information and DenseNet hash sequence, and then, all matched images are sent. For the receiver, the secret information can be recovered successfully by calculating the DenseNet hash sequence of the cover image. During the whole steganography process, the cover images remain unchanged. Experimental results and analysis show that the proposed scheme has better robust compared with the state-of-the-art methods under geometric attacks.

Highlights

Information hiding is the most common way to protect secret information
Based on the above analysis, this paper proposed a coverless image steganography (CIS) algorithm based on DenseNet feature mapping, which aims to improve the robustness of secret information under geometric attacks
We summarize the main contributions of this work as follows: 1. We propose a novel hash mapping rules based on Convolutional neural networks (CNN) feature, and it improves the robustness against geometric attacks

Summary

Introduction

Information hiding is the most common way to protect secret information. Information encryption is the earliest means of protecting secret information, and it is using computer encryption to change the digital structure of load information in digital communication. Researchers began to use image steganography to realize the secret transmission of important information, and it is mainly embedding the secret information into the carrier. It keeps the maximum visual similarity between the carrier and the original object, so as to avoid the abnormalities during transmission process. How to hide information effectively without modifying the carrier is a breakthrough and challenging point

Methods

Results

Conclusion