Abstract
A new image cryptosystem based on neuron-like scheme is proposed in this paper. As a non-linear component of image cryptosystem, neuron-like learning algorithm can realize a kind of memorable diffusion algorithm, thus realizing the plaintext-related image encryption algorithm. Through the feedback operation, the inputs and weights of the neuron are regulated by the information of the image, and then they are used to diffuse the image information. According to the needs of application scenarios, the number of inputs of the neuron can be adjusted so that the image cryptosystem can be applied to different security requirements. The simulation results show that the proposed image encryption system is extremely sensitive to the secret keys, the equivalent keys and the plain images, and also possesses the high security and adaptive characteristics. The image cryptosystem can be applied to the actual applications of image information security.
Highlights
Information security issue has a long history
Image encryption requires a large number of pseudo-random numbers due to the huge volume of the image [3], [4]
Cryptographers have found that chaotic systems can be used to generate pseudo-random sequences with good statistical properties, which is more convenient and effective than using traditional non-linear shift registers to produce pseudo-random numbers [8], [9]
Summary
Information security issue has a long history. Until 1949 did Shannon raise it to an academic altitude of the same importance as communication [1]. It can be seen that these image cryptosystems [24]–[31] are insecure, not because they used the chaotic systems with simple dynamic equations, nor because the statistical characteristics of chaotic pseudo-random sequences used are not good, but because their confusion or diffusion schemes are not well designed, which makes their equivalent keys directly involved in image encryption insensitive to plain images. These image cryptosystems are separately cracked by [32]–[41], and the main decoding algorithms are the chosen/known plaintext methods. Equation (6) plays a vital role in the feedback and diffusion of image information used to achieve the effect of image encryption
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