Encrypting the compressed image by chaotic map and arithmetic coding

As a primary method, image encryption is widely used to protect the security of image information. In recent years, image encryption pays attention to the combination with DNA computing. In this work, we propose a novel method to correct errors in image encryption, which results from the uncertainty of DNA computing. DNA coding is the key step for DNA computing that could decrease the similarity of DNA sequences in DNA computing as well as correct errors from the process of image encryption and decryption. The experimental results show our method could be used to correct errors in image encryption based on DNA coding.

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“…The NPCR and UACI are defined as follows [ 39 , 40 , 41 ]:

where

and

denotes two different cipher images. These cipher images only have one pixel difference.…”

Section: Experiments and Simulationmentioning

confidence: 99%

Correcting Errors in Image Encryption Based on DNA Coding

et al. 2018

Self Cite

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“…x n+ (2) In the prediction stage, the even signal is used to estimate the odd signal via multiplication by a forecasting parameter P. The difference between the odd and predicted signals is the high-frequency coefficients, as expressed in Equation 3.…”

Section: Spiht-based Image Compressionmentioning

confidence: 99%

“…In the current era, with the availability of inexpensive capturing devices with high resolution, the rapid growth of image transmission over public networks has raised substantial concern in the fields of secure transmission and the compression of images [1,2].…”

Section: Introductionmentioning

confidence: 99%

“…However, this method is not suitable for image data because image compression capability is compromised. The second method is based on a compression algorithm and encryption is an additional capability that is realized via entropy coding techniques [1,2]. However, this method is based on a compression algorithm and encryption is embedded as an additional functionality.…”

Section: Introductionmentioning

confidence: 99%

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Joint Image Compression and Encryption Using IWT with SPIHT, Kd-Tree and Chaotic Maps

Nasrullah¹,

Sang

Akbar

et al. 2018

Applied Sciences

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Confidentiality and efficient bandwidth utilization require a combination of compression and encryption of digital images. In this paper, a new method for joint image compression and encryption based on set partitioning in hierarchical trees (SPIHT) with optimized Kd-tree and multiple chaotic maps was proposed. First, the lossless compression and encryption of the original images were performed based on integer wavelet transform (IWT) with SPIHT. Wavelet coefficients undergo diffusions and permutations before encoded through SPIHT. Second, maximum confusion, diffusion and compression of the SPIHT output were performed via the modified Kd-tree, wavelet tree and Huffman coding. Finally, the compressed output was further encrypted with varying parameter logistic maps and modified quadratic chaotic maps. The performance of the proposed technique was evaluated through compression ratio (CR) and peak-signal-to-noise ratio (PSNR), key space and histogram analyses. Moreover, this scheme passes several security tests, such as sensitivity, entropy and differential analysis tests. According to the theoretical analysis and experimental results, the proposed method is more secure and decreases the redundant information of the image more than the existing techniques for hybrid compression and encryption.

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“…Only one logistic map can be employed to generate the order that is used to permute watermarking. However, it will generate the security flaw [33,34]. So we employ two logistic maps to structure the architecture in this work.…”

Section: Embedding Watermarkingmentioning

confidence: 99%