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Secure non-embedded steganography method based on generative adversarial network

A safe and steganographic technology, applied in the field of information security, can solve the problems of dissatisfaction, low embedding capacity, low recovery accuracy, etc., and achieve the effect of ensuring security

Active Publication Date: 2021-01-19
HEFEI UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing embedding-free steganography algorithms, especially those based on GAN, have some problems, including small embedding capacity, low recovery accuracy, and difficulty in resisting known generation model attacks, known extraction model attacks and training Common security threats such as extraction model attacks do not satisfy the Kerckhoffs criterion in modern cryptography

Method used

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  • Secure non-embedded steganography method based on generative adversarial network
  • Secure non-embedded steganography method based on generative adversarial network
  • Secure non-embedded steganography method based on generative adversarial network

Examples

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Embodiment Construction

[0057] In this example, see figure 1 , a secure embedding-free steganography method based on generative adversarial networks, is applied in a network environment composed of a sender, a receiver, a discriminator and a third party, and proceeds as follows:

[0058] Step 1. Use the openssl tool to generate a key pair, including: generate the key en_key and extract the key de_key;

[0059] Step 2. The third party distributes the generated key en_key to the generator, and distributes the extraction key de_key to the extractor;

[0060] Step 3. Train a GAN-based secure embedding-free steganographic model:

[0061] Step 3.1, obtain a real image set and use it as a pre-training data set w;

[0062] In a specific embodiment, the image data set FFHQ is used as the pre-training data set. The dataset contains 70,000 128×128×3 high-definition face images, and these photos have strong diversity, including age, accessories (glasses, hats), etc.

[0063] Step 3.2, let the safe embedding-...

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Abstract

The invention discloses a secure non-embedded steganography method based on a generative adversarial network. The method comprises the following steps: 1, training a steganography model based on the generative adversarial network; 2, carrying out encryption steganography on secret information; 3, encrypting and extracting the secret information. According to the method, common security threats such as known generation model attacks, known extraction model attacks, training extraction model attacks and the like can be solved, so the security requirements of information steganography and extraction in the communication transmission process can be met.

Description

technical field [0001] The invention belongs to the technical field of information security, in particular to a secure non-embedding steganography method based on generative adversarial networks. Background technique [0002] Information hiding is a technology used for secret communication. Through information hiding algorithm, secret information can be transmitted without being noticed by a third party. Steganography is an important way to hide information. It mainly achieves the goal by embedding and modifying the carrier medium, while keeping the distortion of the carrier quality due to the modification within a certain range, and will not arouse the vigilance of the third party. Early spatial digital image steganography algorithms mainly used the insensitivity of human vision to small changes in the image, and replaced the least significant bit of image pixels with secret information. The security of adaptive steganography is challenged by powerful deep learning-based s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L29/06H04L9/08G06T1/00G06N3/04G06N3/08
CPCH04L63/0442H04L9/0825H04L9/0861G06T1/0021G06N3/08G06T2201/005G06N3/045
Inventor 胡东辉张雨蒋文杰严淞
Owner HEFEI UNIV OF TECH
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