Reversible data hiding based on RSBEMD coding and adaptive multi-segment left and right histogram shifting

Peng, Fei; Zhao, Yu; Zhang, Xiang; Long, Min; Pan, Weiqiang

doi:10.1016/j.image.2019.115715

Cited by 23 publications

(24 citation statements)

References 30 publications

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“…However, there is a trade-off problem between the EC and the quality of the stego-images. Most common RDH methods essentially are classified into four types, i.e., (1) difference expansion-based (DE-based) techniques [6][7][8][9][10], (2) prediction error expansion-based (PEE-based) techniques [11][12][13][14][15], (3) HS-based techniques [16][17][18][19][20], and (4) other techniques [21][22][23][24][25].…”

Section: Related Workmentioning

confidence: 99%

“…To demonstrate the definition of proposed state mapping better, Table 2 gives an example of a specific case. Here, the pos is set to 4, and the initial sequence [20,20,20,21]. First, we rotate the initial sequence, i.e., 0, 1, 2, and 3 times separately, to generate four states, i.e., Θ 1 , Θ 2 , Θ 3 and Θ 4 .…”

Section: Definition Of State Mappingmentioning

confidence: 99%

“…In Figure 2(a), the image block is [40, 41; 41, 40], and the to-be-embedded payload bits are "01." First, we can obtain the initial sequence [20,20,20,21] (see Figure 1). Since the decimal value of payload bits is dv � 1, so this sequence is rotated left 1 time.…”

Section: Payload Embeddingmentioning

confidence: 99%

“…Usually, the cryptography-based information security technique [1,2] is considered to be an effective solution for this concern, but the encrypted information can easily attract the attention of attackers. us, the researchers in this area have focused their attention on irreversible data hiding [3][4][5] and reversible data hiding (RDH) [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25] in medical images, which are techniques that can provide security and avoid attracting the attention of attackers.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Privacy-Preserving Reversible Data Hiding for Medical Images Employing Local Rotation

Lin

Chang

2021

Journal of Healthcare Engineering

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As digitalization becomes more common, patients’ concerns about the leakage of private information, such as electronic medical record, are increasing, and those concerns motivated this case study of secure covert communication. Therefore, in this paper, a novel reversible data hiding method based on pixel rotation is proposed for medical images. Using pixel rotation, a state mapping model is constructed to represent the payload. More specifically, many intermediate states are derived from an image block, and each of them is used to form a one-to-one mapping relationship with a specific sequence of payload bits. In addition, to ensure the visual quality of stego-medical-images, the payload bits are only concealed in the regular blocks and the other blocks are unchanged. Moreover, the smoother regular image block will be priority to be used to embed the payload to enhance the visual quality of stego-medical-image. The experimental results showed that the stego-medical-images generated by the proposed reversible data hiding method have better visual quality with an average PSNR of 47.0307 dB, which is higher than that provided by some state-of-the-art methods.

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Section: Related Workmentioning

confidence: 99%

Section: Definition Of State Mappingmentioning

confidence: 99%

Section: Payload Embeddingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Privacy-Preserving Reversible Data Hiding for Medical Images Employing Local Rotation

Lin

Chang

2021

Journal of Healthcare Engineering

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“…In fact, audio has unique characteristics to explore further. The algorithms being applied can be extensions and variations of either imageor video-based methods, such as Echo Data Hiding (EDH) [19] and Histogram Shifting (HS) [20,21] which is then extended in [22] by applying a statistical histogram. Other examples are Prediction Error Expansion (PEE) [23], Noncausal Prediction (NP) [24], and Difference Expansion (DE) along with its variations, such as Reduced Difference Fig.…”

mentioning

confidence: 99%

Reversible data hiding with segmented secrets and smoothed samples in various audio genres

Ahmad

Samudra

2020

J Big Data

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In this age, information technology has grown significantly. Computer networks, which connect a device to others, have made it easier for people to transfer data than before. Moreover, smart devices have the capability of supporting this data transmission, including those in the cloud that may contain massive data. However, the security factor can be a severe issue if sensitive big data, such as military and medical data, do not have enough protection. Furthermore, an attacker may be able to disclose such data. Some algorithms have been introduced to solve that problem, one of which is the data hiding method. Nevertheless, some factors are still challenging, concerning the capacity of the secret data and the quality of the generated data, which are represented by bit and Peak Signal-to-Noise Ratio (PSNR), respectively. Besides, some techniques are not reversible, which means that they cannot reconstruct the carrier (cover). In this research, we investigate those problems by taking audio as the carrier. It is done by sampling the audio file before being interpolated to present spaces for accommodating the secret. Meanwhile, the secret is segmented before the embedding. Later, the embedded audio is smoothed according to the required level. The experimental result is obtained by using a public data set containing various audio genres and instruments, and 11 secret sizes, from 1 to 100 kb. It shows that the proposed method outperforms the others. This higher PSNR value means that the proposed method can generate more similar stego data; it also implies that at a certain quality level, the number of bits that can be hidden in the audio cover is higher than that of others.

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Reversible Data Hiding in Encrypted Image Based on MSB Inversion

Yang

Weng

Hung

et al. 2022

2021 International Conference on Security and Information Technologies With AI, Internet Computing and Big-Data Applications

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Reversible data hiding based on RSBEMD coding and adaptive multi-segment left and right histogram shifting

Cited by 23 publications

References 30 publications

Privacy-Preserving Reversible Data Hiding for Medical Images Employing Local Rotation

Privacy-Preserving Reversible Data Hiding for Medical Images Employing Local Rotation

Reversible data hiding with segmented secrets and smoothed samples in various audio genres

Reversible Data Hiding in Encrypted Image Based on MSB Inversion

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