A 3D model encryption scheme based on a cascaded chaotic system

Audio information strongly correlates in adjacent times, and the data type of the audio is float, so the traditional encryption algorithms for the image are unsuitable for audio encryption. This paper proposes an audio encryption algorithm based on Chaos, named AEA-NCS. Most 1D maps have a control parameter, and the parameter space in the chaotic state is small. Therefore, a 2D-Logistic-nested-infinite-collapse (2D-LNIC) is proposed by combining an infinite collapse map (1D-ICM) and a logistic map. There are two control parameters in 2D-LNIC, and it exhibits good chaotic performance through the Lyapunov exponent and attractor phase diagram . In the audio encryption algorithm, 2D-LNIC generates the keystream, and the encryption algorithm is a process of scrambling and diffusion simultaneously. This structure increases the security of the algorithm. We evaluate AEA-NCS in ESC-50, and the evaluation results show that AEA-NCS exhibits good performance, significantly reducing the correlation of audio information in adjacent times. • A 2D-LNIC is proposed and its dynamic behavior is analyzed. • An audio encryption algorithm, named AEA-NCS is proposed based on 2D-LNIC. • Experimental analysis show that AEA-NCS exhibits good performance. 

AEA-NCS: An audio encryption algorithm based on a nested chaotic system

A multi-image encryption scheme based on the fractional-order hyperchaotic system is designed in this paper. The chaotic characteristics of this system are analyzed by the phase diagram, Lyapunov exponent and bifurcation diagram. According to the analyses results, an interesting image encryption algorithm is proposed. Multiple grayscale images are fused into a color image using different channels. Then, the color image is scrambled and diffused in order to obtain a more secure cipher image. The pixel confusion operation and diffusion operation are assisted by fractional hyperchaotic system. Experimental simulation and test results indicate that the devised multi-image encryption scheme can effectively encrypt multiple images, which increase the efficiency of image encryption and transmission, and have good security performance.

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A new image encryption scheme based on fractional-order hyperchaotic system and multiple image fusion

In this paper, a new improved Lorenz system (ImproLS) is designed with a better behavior due to a larger positive Lyapunov exponent. Then, an asymmetric image encryption scheme is presented based on blind signature and the ImproLS. First, the sender uses the public key from the receiver to produce the cipher keys in conjunction with the Rivest–Shamir–Adleman (RSA) algorithm. Then, a new mathematical model is established to convert both the plain keys and the cipher keys to generate the initial values for ImproLS. After doing preprocess to the secret plain image, its statistical characteristics is changed greatly. Then, by employing permutation and diffusion operations, the cipher image can be obtained and sent to the receiver and the signer. Second, the signer encrypts the digital signature image using Arnold transform in conjunction with the RSA algorithm, and applies the discrete wavelet transform (DWT) to the cipher image. The scrambled signature image is then embedded into the wavelet domain of cipher image blindly. Then, the cipher image containing signature is sent to the receiver for authentication. Third, the receiver uses the private key to check the signature and recover the cipher image. After comparing the decrypted images from both the sender and the signer, the receiver can judge the source of the secret plain image. Experimental results show that the information entropy is high and closer to the theoretical value. In addition, both unsigned and signed cipher images can effectively resist salt and pepper attack, and clipping attack. 

Image encryption scheme based on blind signature and an improved Lorenz system

Cryptographic system based on double parameters fractal sorting vector and new spatiotemporal chaotic system

An image encryption scheme based on multi-objective optimization and block compressed sensing

Combining improved genetic algorithm and matrix semi-tensor product (STP) in color image encryption

In this paper, an effective image encryption algorithm based on 3D Latin cube and memristive hyperchaotic system is proposed. The architecture of preprocessing, permutation and diffusion is utilized. The original image is updated for the first time by the preprocessing process to modify statistical distribution of image pixels, which includes random data embedding and alphabetic XOR operation (AXO). Subsequently, the resulting image is converted to a 3D bit matrix, permutation based on 3D Latin cube (P3DL) and diffusion based on 3D Latin cube (D3DL) are successively manipulated on it to obtain the final cipher image, such that each bit element of plain image may move to any position across the bit plane, and the general transformation of matrix dimensions from permutation to diffusion is also unnecessary. Additionally, the adoption of preprocessing operation makes the permutation easy to resist attacks against special images. Moreover, random data used in preprocessing and 3D Latin cubes utilized in P3DL and D3DL are controlled by a 4D memristive hyperchaotic system, its initial values are computed by information entropy of plain image, which makes the chosen-plaintext and known-plaintext attacks invulnerable. Simulation results and performance analyses verify the effectiveness and security of the proposed image encryption scheme.

Exploiting preprocessing-permutation–diffusion strategy for secure image cipher based on 3D Latin cube and memristive hyperchaotic system

Cloud-decryption-assisted image compression and encryption based on compressed sensing

With the development of telemedicine diagnosis technology, the collection, storage, and transmission of medical data has become a pivotal problem. To solve these problems, in terms of semi-tensor product compressed sensing (STP-CS) and hybrid cloud, a new medical data transmission framework is presented in this article, which can ensure the efficiency, confidentiality, and verifiability of data transmission. According to the edge detection, the authentication information is embedded into the insignificant area of the medical image to protect the authenticity of the data. STP-CS is utilized to measure and encrypt the medical image, which improves the efficiency of data transmission. In order to make the image data more secure, an adaptive cyclic shift diffusion algorithm based on chaotic sequence is used to effectively diffuse the measurement results. In addition, we also apply encoding for the quantized measurement value to be used as tamper proof authentication. The simulation results prove that the presented medical data transmission scheme can effectively improve the image reconstruction effect, transmission efficiency, and security.

Jiangyu Fu

Papers

An image encryption scheme based on multi-objective optimization and block compressed sensing

Combining improved genetic algorithm and matrix semi-tensor product (STP) in color image encryption

Exploiting preprocessing-permutation–diffusion strategy for secure image cipher based on 3D Latin cube and memristive hyperchaotic system

Cloud-decryption-assisted image compression and encryption based on compressed sensing

Exploiting Semi-Tensor Product Compressed Sensing and Hybrid Cloud for Secure Medical Image Transmission