arXiv subjects

Zhaoxia Yin

Publications and source records attributed to Zhaoxia Yin.

65 records · Page 4Linked to original sources

arXiv2020

Multi-domain Reversible Data Hiding in JPEG

As a branch of reversible data hiding (RDH), reversible data hiding in JEPG is particularly important. Because JPEG images are widely used, it is great significance to study reversible data hiding algorithm for JEPG images. The existing JEPG reversible data methods can be divided into two categories, one is based on Discrete Cosine Transform (DCT) coefficients modification, the other is based on Huffman table modification, the methods based on DCT coefficient modification result in large file expansion and visual quality distortion, while the methods based on entropy coding domain modification have low capacity and they may lead to large file expansion. In order to effectively solve the problems in these two kinds of methods, this paper proposes a reversible data hiding in JPEG images methods based on multi-domain modification. In this method, the secret data is divided into two parts by payload distribution algorithm, part of the secret data is first embedded in the DCT coefficient domain, and then the remaining secret data is embedded in the entropy coding domain. Experimental results demonstrate that most JPEG image files with this scheme have smaller file size increment and higher payload than previous RDH schemes.

cs.MM↗

arXiv2019

An Efficient Pre-processing Method to Eliminate Adversarial Effects

Deep Neural Networks (DNNs) are vulnerable to adversarial examples generated by imposing subtle perturbations to inputs that lead a model to predict incorrect outputs. Currently, a large number of researches on defending adversarial examples pay little attention to the real-world applications, either with high computational complexity or poor defensive effects. Motivated by this observation, we develop an efficient preprocessing method to defend adversarial images. Specifically, before an adversarial example is fed into the model, we perform two image transformations: WebP compression, which is utilized to remove the small adversarial noises. Flip operation, which flips the image once along one side of the image to destroy the specific structure of adversarial perturbations. Finally, a de-perturbed sample is obtained and can be correctly classified by DNNs. Experimental results on ImageNet show that our method outperforms the state-of-the-art defense methods. It can effectively defend adversarial attacks while ensure only very small accuracy drop on normal images.

cs.CV↗

arXiv2019

An Improved Reversible Data Hiding in Encrypted Images using Parametric Binary Tree Labeling

This work proposes an improved reversible data hiding scheme in encrypted images using parametric binary tree labeling(IPBTL-RDHEI), which takes advantage of the spatial correlation in the entire original image but not in small image blocks to reserve room for hiding data. Then the original image is encrypted with an encryption key and the parametric binary tree is used to label encrypted pixels into two different categories. Finally, one of the two categories of encrypted pixels can embed secret information by bit replacement. According to the experimental results, compared with several state-of-the-art methods, the proposed IPBTL-RDHEI method achieves higher embedding rate and outperforms the competitors. Due to the reversibility of IPBTL-RDHEI, the original plaintext image and the secret information can be restored and extracted losslessly and separately.

cs.MM↗

arXiv2019

High Capacity Lossless Data Hiding in JPEG Bitstream Based on General VLC Mapping

JPEG is the most popular image format, which is widely used in our daily life. Therefore, reversible data hiding (RDH) for JPEG images is important. Most of the RDH schemes for JPEG images will cause significant distortions and large file size increments in the marked JPEG image. As a special case of RDH, the lossless data hiding (LDH) technique can keep the visual quality of the marked images no degradation. In this paper, a novel high capacity LDH scheme is proposed. In the JPEG bitstream, not all the variable length codes (VLC) are used to encode image data. By constructing the mapping between the used and unused VLCs, the secret data can be embedded by replacing the used VLC with the unused VLC. Different from the previous schemes, our mapping strategy allows the lengths of unused and used VLCs in a mapping set to be unequal. We present some basic insights into the construction of the mapping relationship. Experimental results show that most of the JPEG images using the proposed scheme obtain smaller file size increments than previous RDH schemes. Furthermore, the proposed scheme can obtain high embedding capacity while keeping the marked JPEG image with no distortion.

cs.MM↗

arXiv2019

Separable Reversible Data Hiding Based on Integer Mapping and Multi-MSB Prediction for Encrypted 3D Mesh Models

Reversible data hiding in encrypted domain (RDH-ED) has received tremendous attention from the research community because data can be embedded into cover media without exposing it to the third party data hider and the cover media can be losslessly recovered after the extraction of the embedded data. Although, in recent years, extensive studies have been carried out about images based RDH-ED, little attention is paid to RDH-ED in 3D meshes due to its complex data structure and irregular geometry. In this paper, we propose a separable RDH-ED method for 3D meshes based on integer mapping and Multi-MSB (multiplication most significant bit) prediction. The proposed method divides all the vertices of the mesh into the "embedded" set and "reference" set, and maps decimals of the vertex into integers. Then, we calculate the Multi-MSB prediction errors for the vertices of the "embedded" set and a bit-stream encryption technique will be executed. Finally, additional data is embedded by replacing the Multi-MSB of the encrypted vertex coordinates. According to different permissions, recipient can obtain the original plaintext meshes, additional data or both. Experimental results show that the proposed method has higher embedding capacity and higher quality of the recovered meshes compared to the state-of-art methods.

cs.MM↗

arXiv2019

Multiple reconstruction compression framework based on PNG image

It is shown that neural networks (NNs) achieve excellent performances in image compression and reconstruction. However, there are still many shortcomings in the practical application, which eventually lead to the loss of neural network image processing ability. Based on this, this paper proposes a joint framework based on neural network and zoom compression. The framework first encodes the incoming PNG or JPEG image information, and then the image is converted into binary input decoder to reconstruct the intermediate state image, next we import the intermediate state image into the zooming compressor and re-pressurize it, and reconstruct the final image. From the experimental results, this method can better process the digital image and suppress the reverse expansion problem, and the compression effect can be improved by 4 to 10 times as much as that of using RNN alone, showing better ability in application. In this paper, the method is transmitted over a digital image, the effect is far better than the existing compression method alone, the Human visual system can not feel the change of the effect.

cs.MM↗

arXiv2019

Reversible Data Hiding in Encrypted Images based on Pixel Prediction and Bit-plane Compression

Reversible data hiding in encrypted images (RDHEI) receives growing attention because it protects the content of the original image while the embedded data can be accurately extracted and the original image can be reconstructed lossless. To make full use of the correlation of the adjacent pixels, this paper proposes an RDHEI scheme based on pixel prediction and bit-plane compression. Firstly, to vacate room for data embedding, the prediction error of the original image is calculated and used for bit-plane rearrangement and compression. Then, the image after vacating room is encrypted by a stream cipher. Finally, the additional data is embedded in the vacated room by multi-LSB substitution. Experimental results show that the embedding capacity of the proposed method outperforms the state-of-the-art methods.

cs.MM↗

arXiv2019

Image Encryption Algorithm Based on Facebook Social Network

Facebook is the online social networks (OSNs) platform with the largest number of users in the world today, information protection based on Facebook social network platform have important practical significance. Since the information users share on social networks is often based on images, this paper proposes a more secure image encryption algorithm based on Facebook social network platform to ensure the loss of information as much as possible. When the sender encrypts the image for uploading, it can first resist the third party's attack on the encrypted image and prevent the image data from leaking, simultaneously processed by some unknown processing such as compression and filtering of the image on the Facebook platform, the receiver can still decrypt the corresponding image data.

cs.MM↗

arXiv2019

Reversible data hiding based on reducing invalid shifting of pixels in histogram shifting

In recent years, reversible data hiding (RDH), a new research hotspot in the field of information security, has been paid more and more attention by researchers. Most of the existing RDH schemes do not fully take it into account that natural image's texture has influence on embedding distortion. The image distortion caused by embedding data in the image's smooth region is much smaller than that in the unsmooth region, essentially, it is because embedding additional data in the smooth region corresponds to fewer invalid shifting pixels (ISPs) in histogram shifting. Thus, we propose a RDH scheme based on the images texture to reduce invalid shifting of pixels in histogram shifting. Specifically, first, a cover image is divided into two sub-images by the checkerboard pattern, and then each sub-image's fluctuation values are calculated. Finally, additional data can be embedded into the region of sub-images with smaller fluctuation value preferentially. The experimental results demonstrate that the proposed method has higher capacity and better stego-image quality than some existing RDH schemes.

cs.MM↗

arXiv2019

Reversible Data Hiding in JPEG Images with Multi-objective Optimization

Among various methods of reversible data hiding (RDH) in JPEG images, the consideration in designing is only the image quality, but the image quality and the file size expansion are equally important in JPEG images. Based on this situation, we propose a RDH scheme in JPEG images considering both the image quality and the file size expansion while designing the algorithm. The multi-objective optimization strategy is utilized to realize the balance of the two objectives. Specifically, the cover is divided into several non-overlapping signals firstly, and after that, the embedding costs of signals are calculated using the knowledge of the JPEG compression. Next, the optimized combination of signals for embedding data is gained by the multi-objective optimization. Experimental results show the better performance of our proposed RDH compared with state-of-the-art RDH in JPEG images.

cs.MM↗

arXiv2018

Reversible Data Hiding in Encrypted Images based on MSB Prediction and Huffman Coding

With the development of cloud storage and privacy protection, reversible data hiding in encrypted images (RDHEI) has attracted increasing attention as a technology that can embed additional data in the encryption domain. In general, an RDHEI method embeds secret data in an encrypted image while ensuring that the embedded data can be extracted error-free and the original image can be restored lossless. In this paper, A high-capacity RDHEI algorithm is proposed. At first, the Most Significant Bits (MSB) of each pixel was predicted adaptively and marked by Huffman coding in the original image. Then, the image was encrypted by a stream cipher method. At last, the vacated space can be used to embed additional data. Experimental results show that our method achieved higher embedding capacity while comparing with the state-of-the-art methods.

cs.MM↗