Reversible data hiding in encrypted images with additive and multiplicative public-key homomorphism

Chen, Bing; Wu, Xiaotian; Lu, Wei; Ren, Honglin

doi:10.1016/j.sigpro.2019.05.036

Cited by 21 publications

(11 citation statements)

References 27 publications

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“…In addition, an LDH-CT scheme is developed in [34] for the learning with errors (LWE)-based public-key cryptography [9]. In [35], two preprocessing-free schemes using additive and multiplicative homomorphism were proposed for BGN [5] and ELGamal [6] public-key encryptions, respectively.…”

Section: A Rdh Methods For Homomorphic Encrypted Imagesmentioning

confidence: 99%

“…As shown in Fig. 1(a), the data hidden with the schemes in [30], [33], [34], [35], [38] can be directly extracted from the ciphertext given the extraction rule. Thereby, the to-be-hidden data need to be protected by adopting symmetric encryption schemes before being embedded with this kind of LDH-CT methods.…”

Section: A Rdh Methods For Homomorphic Encrypted Imagesmentioning

confidence: 99%

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Lossless Data Hiding in NTRU Cryptosystem by Polynomial Encoding and Modulation

Wu,

Cheung,

Tian

et al. 2024

IEEE Trans.Inform.Forensic Secur.

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Lossless data hiding in ciphertexts (LDH-CT) is to perform data embedding without changing their plaintexts, which can be used to transmit extra data in the applications of homomorphic encryption at little cost. In this paper, two LDH-CT algorithms named Polynomial Encoding (PE) and Polynomial Modulation (PM) are proposed for the "N-th Degree Truncated Polynomial Ring Unit" (NTRU) scheme, respectively. In the PE algorithm, a polynomial is encoded according to a string of bit values and further used to encrypt a plain-text polynomial. After decrypting the ciphertext, the encoded polynomial can be retrieved so that dozens of bit values can be extracted from it. Moreover, the PE algorithm can be combined with a polynomial partitioning strategy to achieve data extraction before decryption as well. In applying the PM algorithm, no parameter setting of an NTRU cryptosystem is changed while a cipher-text polynomial is generated by selectively sampling a polynomial to match the to-be-hidden value. Furthermore, the data hidden with the PM algorithm can be pre-chosen to be extracted without decryption or after decryption, and in each case up to 10 bit values can be hidden into one cipher-text polynomial. The proposed algorithms and schemes are implemented and compared with several schemes developed for NTRU, BGN, LWE and Paillier encryption. Experimental results and performance evaluations demonstrate the efficacy and superiority of the proposed algorithms and schemes.

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Section: A Rdh Methods For Homomorphic Encrypted Imagesmentioning

confidence: 99%

Section: A Rdh Methods For Homomorphic Encrypted Imagesmentioning

confidence: 99%

Lossless Data Hiding in NTRU Cryptosystem by Polynomial Encoding and Modulation

Wu,

Cheung,

Tian

et al. 2024

IEEE Trans.Inform.Forensic Secur.

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“…Since homomorphic encryption can directly process data in the encryption domain and there is no need to decrypt the cipher-texts before operating them, the Paillier cryptosystem is more practical [27,28]. For example, Chen et al encrypted an image through the Paillier cryptosystem and used the additive homomorphism of the Paillier encryption system to embed the secret data [29].…”

Section: Related Workmentioning

confidence: 99%

A Novel Reversible Data Hiding Method for 3D Model in Homomorphic Encryption Domain

Luo

Zhang

et al. 2021

Symmetry

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Reversible data hiding in the encrypted domain (RDH-ED) is a technique that protects the privacy of multimedia in the cloud service. In order to manage three-dimensional (3D) models, a novel RDH-ED based on prediction error expansion (PEE) is proposed. First, the homomorphic Paillier cryptosystem is utilized to encrypt the 3D model for transmission to the cloud. In the data hiding, a greedy algorithm is employed to classify vertices of 3D models into reference and embedded sets in order to increase the embedding capacity. The prediction value of the embedded vertex is computed by using the reference vertex, and then the module length of the prediction error is expanded to embed data. In the receiving side, the data extraction is symmetric to the data embedding, and the range of the module length is compared to extract the secret data. Meanwhile, the original 3D model can be recovered with the help of the reference vertex. The experimental results show that the proposed method can achieve greater embedding capacity compared with the existing RDH-ED methods.

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“…The use of RRBE and VRAE frameworks is prevalent in many literature studies 6 , 11 – 13 , 16 – 29 RRBE makes use of spatial correlation existing between pixels of the cover image and reserve room. The room reserved for secret data hiding is adopted by self-embedding strategy 11 .…”

Section: Introductionmentioning

confidence: 99%

Secure most significant bit plane compression based reversible data hiding in encrypted image technique using Huffman Ciphersystem

Singh,

Patel,

Vaish

2024

J. Electron. Imag.

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In this work, a secure encryption technique for implementing reversible data hiding, named the Huffman Ciphersystem, is developed. First, a cover image is decomposed into two sub-images. The first sub-image consists of four most significant bits (MSBs), and the second sub-image consists of four least significant bits. The difference of adjacent MSB values for the first sub-image is calculated using inverse S scan order because it gives a confined and small range of difference values. It helps to attain an efficient lossless compression, enhancing our proposed work's embedding capacity (EC). On the other hand, security is imparted by our proposed Huffman Ciphersystem by same level node exchange strategy followed by encryption of the dictionary via scrambling. The proposed scheme achieves a peak signal-to-noise ratio value of infinite for all the tested standard grayscale images at the recovery time. Experimental results demonstrate the proposed work's superiority in EC and security of the encrypted images.

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Reversible data hiding in encrypted images with additive and multiplicative public-key homomorphism

Cited by 21 publications

References 27 publications

Lossless Data Hiding in NTRU Cryptosystem by Polynomial Encoding and Modulation

Lossless Data Hiding in NTRU Cryptosystem by Polynomial Encoding and Modulation

A Novel Reversible Data Hiding Method for 3D Model in Homomorphic Encryption Domain

Secure most significant bit plane compression based reversible data hiding in encrypted image technique using Huffman Ciphersystem

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