Reversible data hiding in encrypted images by active block exchange and room reservation

Chang

2021

Entropy

With the development of cloud storage and privacy protection, reversible data hiding in encrypted images (RDHEI) plays the dual role of privacy protection and secret information transmission. RDHEI has a good application prospect and practical value. The current RDHEI algorithms still have room for improvement in terms of hiding capacity, security and separability. Based on (7, 4) Hamming Code and our proposed prediction/ detection functions, this paper proposes a Hamming Code and UnitSmooth detection based RDHEI scheme, called HUD-RDHEI scheme for short. To prove our performance, two database sets—BOWS-2 and BOSSBase—have been used in the experiments, and peak signal to noise ratio (PSNR) and pure embedding rate (ER) are served as criteria to evaluate the performance on image quality and hiding capacity. Experimental results confirm that the average pure ER with our proposed scheme is up to 2.556 bpp and 2.530 bpp under BOSSBase and BOWS-2, respectively. At the same time, security and separability is guaranteed. Moreover, there are no incorrect extracted bits during data extraction phase and the visual quality of directly decrypted image is exactly the same as the cover image.

Section: Preliminariesmentioning

confidence: 99%

Reversible Data Hiding in Encrypted Image Based on (7, 4) Hamming Code and UnitSmooth Detection

Chang

2021

Entropy

“…In this work, original image is divided into coarse area and smooth area, the traditional RDH method [3] is exploited to embed several least significant bit (LSB) planes of the coarse area into the smooth area, and the vacated LSB planes are used for data embedding. Motivated by [16], Mathew and Wilscy [17] presented an IET Image Process. 2021;1-13.…”

Section: Introductionmentioning

confidence: 99%

Reversible data hiding for encrypted image based on adaptive prediction error coding

Tang

Pang

et al. 2021

IET Image Processing

Reversible data hiding (RDH) is a useful technique of data security. Embedding capacity is one of the most important performance of RDH for encrypted image. Many existing RDH algorithms for encrypted image do not reach desirable embedding capacity yet. To address this problem, a new RDH algorithm is proposed for encrypted image based on adaptive prediction error coding. The proposed RDH algorithm uses a block-based encryption scheme to preserve spatial correlation of original image in the encrypted domain and exploits a novel technique called adaptive prediction error coding to vacate room for data embedding. A key contribution of the proposed RDH algorithm is the adaptive prediction error coding. It can efficiently vacate room from encrypted image block by adaptively coding prediction errors according to block content and thus contributes to a large embedding capacity. Many experiments on benchmark image databases are done to validate performance of the proposed RDH algorithm. The results show that the average embedding rates on the open databases of UCID, BOSSBase and BOWS-2 are 1.7081, 2.4437 and 2.3083 bpp, respectively. Comparison results illustrate that the proposed RDH algorithm outperforms some state-of-the-art RDH algorithms in embedding capacity.

“…In the past decade, researchers have proposed many effective RDHEI methods [24][25][26][27][28][29]. According to the different order, either before or after encryption, there are two kinds of categories in recent RDHEI methods: (1) the methods by vacating room after encryption (VRAE) [24][25][26] and (2) the methods by reserving room before encryption (RRBE) [27][28][29].…”

Section: Introductionmentioning

confidence: 99%

“…Thus, after the encryption of the image, the LSBs of A can be used to embed data. Based on [27], Mathew and Wilscy [28] proposed an improved method using active block exchange in 2014. They divided the original image into smooth blocks and active blocks, and then they rearranged all the blocks to obtain a smooth area and an active area.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Reversible Data Hiding in Encrypted Images Using Median Edge Detector and Two’s Complement

Wang

et al. 2021

Symmetry

With the rapid development of cloud storage, an increasing number of users store their images in the cloud. These images contain many business secrets or personal information, such as engineering design drawings and commercial contracts. Thus, users encrypt images before they are uploaded. However, cloud servers have to hide secret data in encrypted images to enable the retrieval and verification of massive encrypted images. To ensure that both the secret data and the original images can be extracted and recovered losslessly, researchers have proposed a method that is known as reversible data hiding in encrypted images (RDHEI). In this paper, a new RDHEI method using median edge detector (MED) and two’s complement is proposed. The MED prediction method is used to generate the predicted values of the original pixels and calculate the prediction errors. The adaptive-length two’s complement is used to encode the most prediction errors. To reserve room, the two’s complement is labeled in the pixels. To record the unlabeled pixels, a label map is generated and embedded into the image. After the image has been encrypted, it can be embedded with the data. The experimental results indicate that the proposed method can reach an average embedding rate of 2.58 bpp, 3.04 bpp, and 2.94 bpp on the three datasets, i.e., UCID, BOSSbase, BOWS-2, which outperforms the previous work.