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Image Compression and Encryption Combining Autoencoder and Chaotic Logistic Map
Iranian Journal of Science and Technology, Transactions A: Science ( IF 1.7 ) Pub Date : 2020-06-28 , DOI: 10.1007/s40995-020-00905-4
K. M. Ameen Suhail , Syam Sankar

The third-party misuse and manipulation of digital images are a threat to the security and privacy of human subjects. In this paper, we report a system which effectively compresses and encrypts images to achieve secure transmission of image data with minimal bandwidth. The proposed system utilizes autoencoder for compression and chaotic logistic map for encryption. Autoencoder is an unsupervised deep learning neural network algorithm which compresses the input vector into a vector of fewer dimensions, which forms the dense representation of input data. This capability of the autoencoder can be used for compressing images. The encryption procedure is applied to the compressed data. The sequences generated by the logistic map are used efficiently in shuffling and encrypting the compressed image form. The security analysis confirms that the system is secure enough for transmitting image data.

中文翻译:

自动编码器与混沌逻辑映射相结合的图像压缩与加密

第三方滥用和操纵数字图像对人类受试者的安全和隐私构成威胁。在本文中,我们报告了一种可以有效压缩和加密图像以最小带宽实现图像数据安全传输的系统。所提出的系统利用自动编码器进行压缩,利用混沌逻辑映射进行加密。自动编码器是一种无监督的深度学习神经网络算法,可将输入向量压缩为维数较少的向量,从而形成输入数据的密集表示。自动编码器的此功能可用于压缩图像。加密过程将应用于压缩数据。由逻辑图生成的序列可有效地用于改组和加密压缩图像形式。
更新日期:2020-06-28
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