Reversible data hiding in encrypted image with local-correlation-based classification and adaptive encoding strategy

Zou, Han; Chen, Guohua

doi:10.1016/j.sigpro.2022.108847

Cited by 10 publications

(5 citation statements)

References 28 publications

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“…The correlation coefficient is another classical parameter to measure encryption quality [37,38], where a correlation close to zero indicates secure encryption. Its procedure follows the next steps.…”

Section: Correlation Coefficientmentioning

confidence: 99%

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A Dynamic Hybrid Cryptosystem Using Chaos and Diffie–Hellman Protocol: An Image Encryption Application

2023

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Images with sensitive content require encryption for storage and transmission. Symmetric schemes can cipher them, while an asymmetric cryptosystem can distribute the secret key safely. For this reason, we propose a dynamic hybrid cryptosystem, which ciphers images and transfers its private keys. It has a symmetric algorithm that applies the Lorenz equations for generating different boxes and permutations in every encryption process and round. Since the secret key concatenates two private numbers, an asymmetric algorithm is included for its key distribution. The proposal uses the Diffie–Hellman protocol with ElGamal for obtaining a seed and building 128 strings. Then, the SHA-512 is applied in each of them a number of times associated with the secret key value in its blockchain representation. The resultant strings are concatenated to conform to the public key. Finally, the tests indicate that the cryptosystem resists differential, linear, algebraic, and brute-force attacks. Its cipher quality is high according to the entropy, correlation, DFT, NPCR, UACI, AC, texture analysis, and goodness of fit test. Additionally, occlusion, additive, multiplicative, and the proposed χ2 noise attacks are simulated on encrypted images. Finally, the sharpness loss is measured with the Similarity Parameter and improved with a filter 5 × 5.

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Section: Correlation Coefficientmentioning

confidence: 99%

“…The constants D i , shown in Equation (37), are unique according to Euclid's division algorithm [47] and satisfy Equation (38).…”

Section: Algorithm For the Generation Of Permutationsmentioning

confidence: 99%

A Dynamic Hybrid Cryptosystem Using Chaos and Diffie–Hellman Protocol: An Image Encryption Application

2023

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“…This is because secret data can only be embedded if there is a certain amount of redundancy space in the carrier, whereas encryption increases the information entropy of the image and leads to a reduction in redundancy space. Despite this, VRAE-based RDHEI research has been widely favored by a range of related work [7][8][9][10][11][12][13][14][15][16][17][18][19]. In [7], the original image was encrypted using a pseudo-random stream cipher, and the secret data were embedded by flipping the three least significant bits (LSBs) of all pixels in a block.…”

Section: Introductionmentioning

confidence: 99%

“…By retaining the auxiliary information and coded information, the carrier image can be recovered losslessly after information extraction. Zhou and Chen [16] proposed a novel VRAE-based algorithm that combines block classification and multilayer processing to fully explore the redundant space.…”

Section: Introductionmentioning

confidence: 99%

Reversible data hiding in encrypted images with multi-prediction and adaptive Huffman encoding

Ren

Yue

2023

Preprint

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With the rapid development of network technology and the massive accumulation of user data, huge amounts of data are being rapidly generated and shared on the network, while the problems of unauthorized data access and misuse continue to emerge. Reversible data hiding in encrypted images (RDHEI) is a privacy-preserving method that embeds protected data into encrypted content and accurately extracts the embedded data without affecting the original content. However, the amount of embedded protected information has always been one of the major constraints on the performance and application of RDHEI. Currently, the main approaches to improve the net embedding capacity of RDHEI are to increase the total embedding capacity or to reduce the length of the auxiliary information to be embedded. In this paper, we propose a novel RDHEI scheme based on multi-prediction and adaptive Huffman encoding. To increase the total embedding capacity, we use the MED + GAP predictor to generate the label map data of non-reference pixels before image encryption. Then, an adaptive Huffman coding is designed to compress the generated labels to reduce the embedding length of the auxiliary information used for extraction and recovery. Experimental results show that with MED + GAP predictor and adaptive Huffman coding, the proposed method achieves a higher embedding capacity than other recent methods while ensuring security and reversibility.

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“…

carrier and reduces available redundancy space. However, VRAE-based RDHEI research has gained significant attention from various related studies [7][8][9][10][11][12][13][14][15][16][17][18][19] . In 7 , the original image was encrypted using a pseudorandom stream cipher, and one bit of the secret data was embedded by flipping the three least significant bits (LSBs) of all the pixels in a selected block.

…”

mentioning

confidence: 99%

Reversible data hiding in encrypted images with multi-prediction and adaptive huffman encoding

Ren,

Bai,

Chen

et al. 2023

Sci Rep

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With the rapid development of multimedia technology and the massive accumulation of user data, a huge amount of data is rapidly generated and shared over the network, while the problems of inappropriate data access and abuse persist. Reversible data hiding in encrypted images (RDHEI) is a privacy-preserving method that embeds protected data in an encrypted domain and accurately extracts the embedded data without affecting the original content. However, the amount of embedded data has been one of the major limitations in the performance and application of RDHEI. Currently, the main approaches to improve the capacity of RDHEI are either to increase the overall capacity or to reduce the length of the auxiliary information. In this paper, we propose a novel RDHEI scheme based on multi-prediction and adaptive Huffman encoding. To increase the overall capacity, we propose a multi-prediction, called MED+GAP predictor, to generate the label map data of non-reference pixels prior to image encryption. Then, an adaptive Huffman coding is designed to compress the generated labels in order to reduce the embedding length of the auxiliary information used for the extraction and recovery. Experiments show that the proposed method with MED+GAP predictor and adaptive Huffman coding improves 0.052 bpp, 0.023 bpp, and 0.047 bpp on average over the other state-of-the-art methods on the BOSSBase, BOWS-2, and UCID datasets, respectively, while maintaining security and reversibility.

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Reversible data hiding in encrypted image with local-correlation-based classification and adaptive encoding strategy

Cited by 10 publications

References 28 publications

A Dynamic Hybrid Cryptosystem Using Chaos and Diffie–Hellman Protocol: An Image Encryption Application

A Dynamic Hybrid Cryptosystem Using Chaos and Diffie–Hellman Protocol: An Image Encryption Application

Reversible data hiding in encrypted images with multi-prediction and adaptive Huffman encoding

Reversible data hiding in encrypted images with multi-prediction and adaptive huffman encoding

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