About the Journal
Journal of Information Hiding and Privacy Protection focuses on original papers addressing novel ideas, issues, theoretical analysis, implementation, experimental results, systems and applications in the field of Watermarking, Data Hiding, Multimedia Security, and Privacy Protection.
Indexing and Abstracting
Starting from July 2023, Journal of Information Hiding and Privacy Protection will transition to a continuous publication model, accepted articles will be promptly published online upon completion of the peer review and production processes.
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Open Access
ARTICLE
Pairwise Reversible Data Hiding for Medical Images with Contrast Enhancement
Journal of Information Hiding and Privacy Protection, Vol.6, pp. 1-19, 2024, DOI:10.32604/jihpp.2024.051354 - 24 June 2024
Abstract Contrast enhancement in medical images has been vital since the prevalence of image representations in healthcare. In this research, the PRDHMCE (pairwise reversible data hiding for medical images with contrast enhancement) algorithm is proposed as an automatic contrast enhancement (CE) method for medical images based on region of interest (ROI) and non-region of interest (NROI). The PRDHMCE algorithm strategically enhances the ROI after segmentation using histogram stretching and data embedding. An initial histogram evaluation compares histogram bins with their neighbours to select the bin with the maximum pixel count. The selected bin is set as More >
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Open Access
ARTICLE
An Overview of Adversarial Attacks and Defenses
Journal of Information Hiding and Privacy Protection, Vol.4, No.1, pp. 15-24, 2022, DOI:10.32604/jihpp.2022.029006
Abstract In recent years, machine learning has become more and more popular, especially the continuous development of deep learning technology, which has brought great revolutions to many fields. In tasks such as image classification, natural language processing, information hiding, multimedia synthesis, and so on, the performance of deep learning has far exceeded the traditional algorithms. However, researchers found that although deep learning can train an accurate model through a large amount of data to complete various tasks, the model is vulnerable to the example which is modified artificially. This technology is called adversarial attacks, while the More >
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Open Access
ARTICLE
Conceptual Modeling and Simulation Application Analysis of In-service Assessment
Journal of Information Hiding and Privacy Protection, Vol.4, No.1, pp. 53-60, 2022, DOI:10.32604/jihpp.2022.032109
Abstract Firstly, this paper expounds the conceptual connotation of in-service assessment in the new system, then applies modeling and Simulation in the field of in-service assessment, establishes the conceptual model of in-service assessment and its process, and finally analyzes the application of modeling and simulation in the specific links of in-service assessment. More >
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Open Access
ARTICLE
Intrusion Detection System Using a Distributed Ensemble Design Based Convolutional Neural Network in Fog Computing
Journal of Information Hiding and Privacy Protection, Vol.4, No.1, pp. 25-39, 2022, DOI:10.32604/jihpp.2022.029922
Abstract With the rapid development of the Internet of Things (IoT), all kinds of data are increasing exponentially. Data storage and computing on cloud servers are increasingly restricted by hardware. This has prompted the development of fog computing. Fog computing is to place the calculation and storage of data at the edge of the network, so that the entire Internet of Things system can run more efficiently. The main function of fog computing is to reduce the burden of cloud servers. By placing fog nodes in the IoT network, the data in the IoT devices can… More >
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Open Access
ARTICLE
SPN-Based Performance Analysis of Multiple Users’ Behaviors for SNS
Journal of Information Hiding and Privacy Protection, Vol.4, No.1, pp. 1-13, 2022, DOI:10.32604/jihpp.2022.026440
Abstract With the rapid development of various applications of Information Technology, big data are increasingly generated by social network services (SNS) nowadays. The designers and providers of SNS distribute different client applications for PC, Mobile phone, IPTV etc., so that users can obtain related service via mobile or traditional Internet. Good scalability and considerably short time delay are important indices for evaluating social network systems. As a result, investigating and mining the principle of users’ behaviors is an important issue which can guide service providers to establish optimal systems with SNS. On the basis of analyzing… More >
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Open Access
ARTICLE
A Survey of Anti-forensic for Face Image Forgery
Journal of Information Hiding and Privacy Protection, Vol.4, No.1, pp. 41-51, 2022, DOI:10.32604/jihpp.2022.031707
Abstract Deep learning related technologies, especially generative adversarial network, are widely used in the fields of face image tampering and forgery. Forensics researchers have proposed a variety of passive forensic and related anti-forensic methods for image tampering and forgery, especially face images, but there is still a lack of overview of anti-forensic methods at this stage. Therefore, this paper will systematically discuss the anti-forensic methods for face image tampering and forgery. Firstly, this paper expounds the relevant background, including the relevant tampering and forgery methods and forensic schemes of face images. The former mainly includes four More >
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Open Access
REVIEW
A Survey of GAN Based Image Synthesis
Journal of Information Hiding and Privacy Protection, Vol.4, No.2, pp. 79-88, 2022, DOI:10.32604/jihpp.2022.039751
Abstract Image generation is a hot topic in the academic recently, and has been applied to AI drawing, which can bring Vivid AI paintings without labor costs. In image generation, we represent the image as a random vector, assuming that the images of the natural scene obey an unknown distribution, we hope to estimate its distribution through some observation samples. Especially, with the development of GAN (Generative Adversarial Network), The generator and discriminator improve the model capability through adversarial, the quality of the generated image is also increasing. The image quality generated by the existing GAN More >
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Open Access
ARTICLE
Video Compressed Sensing Reconstruction Based on Multi-Dimensional Reference Frame Multi Hypothesis Rediction
Journal of Information Hiding and Privacy Protection, Vol.4, No.2, pp. 61-68, 2022, DOI:10.32604/jihpp.2022.027692
Abstract In this paper, a video compressed sensing reconstruction algorithm based on multidimensional reference frames is proposed using the sparse characteristics of video signals in different sparse representation domains. First, the overall structure of the proposed video compressed sensing algorithm is introduced in this paper. The paper adopts a multi-reference frame bidirectional prediction hypothesis optimization algorithm. Then, the paper proposes a reconstruction method for CS frames at the re-decoding end. In addition to using key frames of each GOP reconstructed in the time domain as reference frames for reconstructing CS frames, half-pixel reference frames and scaled More >
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Open Access
REVIEW
An Overview of Image Tamper Detection
Journal of Information Hiding and Privacy Protection, Vol.4, No.2, pp. 103-113, 2022, DOI:10.32604/jihpp.2022.039766
Abstract With the popularization of high-performance electronic imaging equipment and the wide application of digital image editing software, the threshold of digital image editing becomes lower and lower. This makes it easy to trick the human visual system with professionally altered images. These tampered images have brought serious threats to many fields, including personal privacy, news communication, judicial evidence collection, information security and so on. Therefore, the security and reliability of digital information has been increasingly concerned by the international community. In this paper, digital image tamper detection methods are classified according to the clues that More >
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Open Access
REVIEW
An Overview of Double JPEG Compression Detection and Anti-detection
Journal of Information Hiding and Privacy Protection, Vol.4, No.2, pp. 89-101, 2022, DOI:10.32604/jihpp.2022.039764
Abstract JPEG (Joint Image Experts Group) is currently the most widely used image format on the Internet. Existing cases show that many tampering operations occur on JPEG images. The basic process of the operation is that the JPEG file is first decompressed, modified in the null field, and then the tampered image is compressed and saved in JPEG format, so that the tampered image may be compressed several times. Therefore, the double compression detection of JPEG images can be an important part for determining whether an image has been tampered with, and the study of double More >
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Open Access
REVIEW
A Survey of Privacy Preservation for Deep Learning Applications
Journal of Information Hiding and Privacy Protection, Vol.4, No.2, pp. 69-78, 2022, DOI:10.32604/jihpp.2022.039284
Abstract Deep learning is widely used in artificial intelligence fields such as computer vision, natural language recognition, and intelligent robots. With the development of deep learning, people’s expectations for this technology are increasing daily. Enterprises and individuals usually need a lot of computing power to support the practical work of deep learning technology. Many cloud service providers provide and deploy cloud computing environments. However, there are severe risks of privacy leakage when transferring data to cloud service providers and using data for model training, which makes users unable to use deep learning technology in cloud computing More >
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Open Access
REVIEW
Survey on the Loss Function of Deep Learning in Face Recognition
Journal of Information Hiding and Privacy Protection, Vol.3, No.1, pp. 29-45, 2021, DOI:10.32604/jihpp.2021.016835
Abstract With the continuous development of face recognition network, the
selection of loss function plays an increasingly important role in improving
accuracy. The loss function of face recognition network needs to minimize the
intra-class distance while expanding the inter-class distance. So far, one of our
mainstream loss function optimization methods is to add penalty terms, such as
orthogonal loss, to further constrain the original loss function. The other is to
optimize using the loss based on angular/cosine margin. The last is Triplet loss
and a new type of joint optimization based on HST Loss and ACT More >
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Open Access
ARTICLE
A Fast Detection Method of Network Crime Based on User Portrait
Journal of Information Hiding and Privacy Protection, Vol.3, No.1, pp. 17-28, 2021, DOI:10.32604/jihpp.2021.017497
Abstract In order to quickly and accurately find the implementer of the network
crime, based on the user portrait technology, a rapid detection method for users
with abnormal behaviorsis proposed. This method needs to construct the abnormal
behavior rule base on various kinds of abnormal behaviors in advance, and
construct the user portrait including basic attribute tags, behavior attribute tags and
abnormal behavior similarity tagsfor network users who have abnormal behaviors.
When a network crime occurs, firstly get the corresponding tag values in all user
portraits according to the category of the network crime. Then, use More >
Copyright © 2024 The Author(s). Published by Tech Science Press.
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