High-order airspace hiding method for resisting sample pair analysis

Abstract

The invention relates to a high-order airspace hiding method for resisting sample pair analysis. The information hiding technology is a new research topic in the information security field in recent years. The technology is to hide secret information in other carriers to go beyond the awareness of people so as to ensure the security of secret information. The high-order airspace hiding method for resistable sample pair analysis comprises the following steps: finding a pixel point capable of performing high-order hiding in a carrier gray level image with a size of N1xN2, converting the to-be-hidden secret image with a size of M1xM2 into binary information stream, determining on which position of the carrier image the binary information stream is hidden through Logistic chaos mapping, the Logistic chaos mapping formula being Z(n+1)=4Zn(1-Zn), wherein Zn belonging to (0,1); if the secret information is identical to the bit information, substitution is not performed, and otherwise, substitution is performed, then necessary compensation algorithm is performed to control the variation range of the pixel points within four pixels, then repeating the process till all information is hidden. The invention is used for information hiding technology.

Description

Technical field: [0001] The invention relates to a method for concealing high-level space, in particular to a method for hiding high-level space that is resistant to sample pair analysis. Background technique: [0002] Information hiding technology is a new research direction in the field of information security in recent years. This technology hides secret information in other carriers so that people can't detect it, thus ensuring the security of secret information. In the image hiding algorithm, according to the classification of embedded domain, it can be divided into spatial domain and transform domain hiding. In the image information hiding technology based on the space domain, the least significant bit (LSB) algorithm has a large hiding capacity and is easy to implement, but the hiding position is unreliable and the robustness is poor, so that many analysis methods for LSB hiding have appeared in recent years. , such as classic SPA (sample pair analysis) and RS analys...

AI Technical Summary

Problems solved by technology

In the image information hiding technology based on the space domain, the least significant bit (LSB) algorithm has a large hiding capacity and is easy to implement, but the hiding position is unreliable and the robustness is poor, so that many analysis methods for LSB hiding have appeared in recent years. , such as classic SPA (sample pair analysis) and RS analysis methods

Then people proposed the HB algorithm based on the most significant bit of the image. Compared with the LSB algorithm, its robustness has been greatly improved, but the hidden amount can only reach 30% of the carrier image; in 2005, Zhu Congxu proposed that each watermark bit It is randomly embedded into a middle bit of the pixel, and the optimization strategy of minimizing the amount of pixel change is adopted, so that the robustness has been greatly improved, but even the optimized pixel value still has a large difference from the original image. Changes will have a certain impact on the vision

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