This paper proposes a color image encryption algorithm based on a cloud model Fibonacci chaotic system, as well as a matrix convolution operation that can protect image content effectively and safely. The algorithm combines the cloud model with the generalized Fibonacci, creating a new complex chaotic system that realizes the dynamic random variation of chaotic sequences. The chaotic sequence is used to scramble the pixel coordinates of the mosaic images of the R, G, and B components of the color image. Then, the chaotic sequence value is used as a matrix convolution cloud algorithm that alternately updates the input value of the matrix convolution operation and the pixel value to obtain the permutation transformation of the original pixel value. Finally, the pixel values of the replacement and cloud model Fibonacci chaotic sequence and the pixel values of the front (rear) adjacent pixel points are subjected to a two-way exclusive XOR operation. Realizing the change of the arbitrary pixel value causes a chain transformation of the pixel values of all of the pixel points, and sequentially generates an encrypted image. Experiments show that the histogram of the encrypted image is smoother and adjacent pixels of the image have low correlation. In addition, this algorithm can resist attack experiments such as differential attack, select plaintext attack and noise attack and provides high encryption security, high anti-interference, and strong robustness. The dynamic chaotic system is used to realize the color image encryption of the dynamic key, and the encryption algorithm has higher security and the validity of the algorithm.

Aiming at the problem that the existing bit scrambling encryption algorithm is not sensitive to the bit scrambling between 8 bits of one pixel, and the anti-noise and anti-selective plaintext attack ability is weak, a 3D cyclic shift bit scrambling image encryption algorithm is proposed in this paper. Discarding the scrambling mode of 8 bits of one pixel and the bits of all pixels, the pixel values are converted into binary arrays and then converted into 3D matrices in this paper. And the higher bit-planes and the lower bit-planes, which contain the plaintext information of different weights, are scrambled by cyclic shifting respectively. Therefore the sensitivity of the bit scrambling, the anti-noise attack ability of the algorithm and the randomness of intermediate ciphertext are improved. Moreover the randomness and the anti-noise ability can be adjusted by changing the number of higher bit-planes according to different encryption requirements. A new type of Logistic-Fibonacci (L-F) cascade chaos is constructed to generate random sequences, which solves the problem of blank windows in the uneven distribution of Logistic chaos. The initial value and the control parameters are increased, the sequence randomness is improved, and the fastness of low-dimensional chaos is preserved. By strongly correlating the key with SHA-256 of the plaintext, the key stream can change adaptively with the plaintext, which greatly improves the sensitivity of the plaintext and the ability of resisting the selective plaintext and ciphertext attack. The experiments show that the algorithm can encrypt all kinds of images with high efficiency, and can resist common attacks. It is a secure and reliable image encryption algorithm. INDEX TERMS Image encryption, L-F cascade chaos, 3D bit scrambling, SHA-256.

This study aims to solve time-space uncertainties due to the narrow network channel bandwidth and long transmission delay of an underwater acoustic sensor network when a node is using a channel. This study proposes a MAC protocol (BSPMDP-MAC) for an underwater acoustic sensor network based on the belief state space. This protocol can averagely divide the time axis of a sensor's receiving nodes into n slots. The action state information of a sensor's transmission node was divided by the grades of link quality and the residual energy of each node. The receiving nodes would obtain the decision strategy sequence of the usage rights of the competitive channels of the sensor's transmission nodes according to the joint probability distributions of historical observations and action information of channel occupancy. The transmission nodes will transmit data packets to the receiving nodes in turns in allocated slots, according to the decision strategy sequence, and the receiving nodes will predict the channel occupancy and perceive the belief states and access actions in the next cycle, according to the present belief states and actions. These experimental simulation results show that this protocol can reduce the collision rate of data packets, improve the network throughput and transmission success rate of data packets, and reduce the energy overhead of the network.

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