Abstract
With the rapid development of communication technology, digital technology has been widely used in all walks of life. Nevertheless, with the wide dissemination of digital information, there are many security problems. Aiming at preventing privacy disclosure and ensuring the safe storage and sharing of image and video data in the cloud platform, the present work proposes an encryption algorithm against neural cryptography based on deep learning. Primarily, the image saliency detection algorithm is used to identify the significant target of the video image. According to the significant target, the important region and nonimportant region are divided adaptively, and the encrypted two regions are reorganized to obtain the final encrypted image. Then, after demonstrating how attackers conduct attacks to the network under the ciphertext attack mode, an improved encryption algorithm based on selective ciphertext attack is proposed to improve the existing encryption algorithm of the neural network. Besides, a secure encryption algorithm is obtained through detailed analysis and comparison of the security ability of the algorithm. The experimental results show that Bob's decryption error rate will decrease over time. The average classification error rate of Eve increases over time, but when Bob and Alice learn a secure encryption network structure, Eve's classification accuracy is not superior to random prediction. Chosen ciphertext attack-advantageous neural cryptography (CCA-ANC) has an encryption time of 14s and an average speed of 69mb/s, which has obvious advantages over other encryption algorithms. The self-learning secure encryption algorithm proposed here significantly improves the security of the password and ensures data security in the video image.
Highlights
With the rapid development of communication technology, digital technology has been widely used in all walks of life
The image saliency detection algorithm is used to identify the significant target of the video image
According to the significant target, the important region and nonimportant region are divided adaptively, and the encrypted two regions are reorganized to obtain the final encrypted image. en, after demonstrating how attackers conduct attacks to the network under the ciphertext attack mode, an improved encryption algorithm based on selective ciphertext attack is proposed to improve the existing encryption algorithm of the neural network
Summary
Image Encryption. e purpose of image encryption is to disrupt the semantic information of the image so that the attacker cannot obtain valid information after intercepting the ciphertext image. e legitimate receiver can still restore the original image through the agreed key and public encryption and decryption algorithm. A sine function is innovatively introduced in exploring image encryption to propose a new one-dimensional chaotic system image encryption scheme. It makes the chaotic phenomenon of the chaotic system more prominent and enhances the image encryption effect. A high-order chaotic system is introduced into the image encryption scheme to ensure the security of encrypted data. Because fixed encoding rules cannot be applied to the encryption system as an independent technology, a scheme combining a high-dimensional chaotic system with DNA encoding is proposed to enhance the encryption strength and the security of the encrypted image. E choice of the encryption algorithm is to encrypt some essential syntax elements after video entropy coding so that the video is seriously distorted to achieve the effect of video encryption. E video with encrypted video syntax elements will be severely distorted after decoding so that the reconstructed video cannot obtain any useful information, and the user who holds the key can obtain the original video
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