Composite chaotic secondary scrambling image encryption algorithm

Abstract

The invention provides a composite chaotic secondary scrambling image encryption algorithm and belongs to the technical field of encryption. The algorithm is characterized by, to begin with, generating an initial value of Logistic mapping through Chebyshev mapping; then, forming a two-dimensional chaotic matrix through the Logistic mapping; and carrying out position and grayscale secondary scrambling on images needing encryption through the matrix. The algorithm utilizes Chebyshev mapping and Logistic mapping to alternately generate mixed chaotic sequences, thereby not only inheriting characteristics of the single Logistic mapping chaotic sequence, but also improving the phenomenon of stable window of the single chaotic sequence; in comparison, random performance of the sequence is higher;and in particular, the system is very sensitive to encryption keys, and subtle changes in the keys will directly lead to changes in the location and grayscale matrix, so that decryption fails, and the system has higher safety.

Description

technical field [0001] The invention relates to the technical field of encryption, in particular to a compound chaos secondary scrambling image encryption algorithm. Background technique [0002] With the rapid development of network technology and multimedia technology, multimedia data has gradually become an important source of information for people and an important part of people's lives. However, multimedia data is vulnerable to man-made attacks in the network environment, such as information leakage, data tampering and information theft. Therefore, information security has received more and more attention. This paper mainly discusses the digital image encryption technology related to digital image information security. [0003] Image encryption algorithms are currently mainly divided into three categories: image pixel position scrambling, grayscale conversion, and the combination of the two. Among them, position scrambling is to scramble the position of the original...

AI Technical Summary

Problems solved by technology

Among them, position scrambling is to scramble the position of the original data and rearrange the image pixels. Typical algorithms include Arnold transformation, pseudo Rubik's cube transformation and m-sequence transformation. These algorithms are simple, but the periodic calculation time is long and no matter the process What a complex transformation, the gray histogram of the image will not change, so it is easy to be deciphered by statistical analysis methods

Grayscale conversion is to change the pixel value of the original image by some method to make the image unrecognizable. At present, most algorithms are mainly concentrated in the chaotic system, and the typical ones are Logistic mapping, Chebyshev mapping and sinusoidal chaotic mapping, etc., but the single Discrete chaotic iterative systems have disadvantages such as small key space, slow speed, and weak security functions, and the effect of one-time encryption is not ideal, and it is often still possible to distinguish contours.

The composite discrete chaotic iterative system, because its dynamic behavior is related to the dynamic behavior of the composite sequence and each chaotic iterative subsystem, is more complex and has a large key space.