Deep-learning-model-based steganography image detection method and system

Abstract

The invention discloses a deep-learning-model-based steganography image detection method and system. The method comprises the following steps that: an initial deep learning model for fitting and analyzing a digital image steganography rich model feature is preset; a supervised pre training algorithm is selected to carry out pre training on the initial deep learning model to obtain a pre-training deep learning model; the pre-training deep learning model and a deep classification network are integrated to generate an integrated deep learning model, the integrated deep learning model is trained according to a training data set obtained in advance and thus a final deep learning model is generated, a steganography image is detected based on the final deep learning model, and a detection result is outputted. Therefore, a steganography image and a carrier image can be distinguished accurately. Moreover, the data calculation dimension is low; the computing load is low; and the steganography image detection speed increases.

Description

technical field [0001] The invention relates to the technical field of digital image steganography, in particular to a steganographic image detection method and system based on a deep learning model. Background technique [0002] Information hiding is a new technology of information security that emerged in the 1990s, and has become a hotspot in the research of information security technology. In the traditional communication field, in order to ensure that the information transmitted can not be eavesdropped or destroyed, passwords are often used to protect the information, that is, to prevent eavesdroppers from seeing or understanding, but the disadvantage of this technology is to tell eavesdroppers that this is secret information, especially With the development of computer technology, the security of passwords has been greatly challenged. And digital steganography is to hide the secret information that needs to be transmitted in an ordinary non-secret message, and then tr...

AI Technical Summary

Problems solved by technology

The features of steganalysis algorithms in the prior art have high dimensionality, which greatly increases the time for feature extraction and feature classification, which is not conducive to practical applications, and increases the time cost of image steganalysis technology

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