ISSN:2637-4234(print)
ISSN:2637-4226(online)
Publication Frequency:Continuously
Journal of Information Hiding and Privacy Protectionfocuses 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.
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.
Open Access
ARTICLE
Journal of Information Hiding and Privacy Protection, Vol.5, pp. 1-18, 2023, DOI:10.32604/jihpp.2023.041972
Abstract In the contemporary era, the abundant availability of health information through internet and mobile technology raises concerns. Safeguarding and maintaining the confidentiality of patients’ medical data becomes paramount when sharing such information with authorized healthcare providers. Although electronic patient records and the internet have facilitated the exchange of medical information among healthcare providers, concerns persist regarding the security of the data. The security of Electronic Health Record Systems (EHRS) can be improved by employing the Cuckoo Search Algorithm (CS), the SHA-256 algorithm, and the Elliptic Curve Cryptography (ECC), as proposed in this study. The suggested… More >
Open Access
ARTICLE
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 >
Open Access
ARTICLE
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 >
Open Access
ARTICLE
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 >
Open Access
ARTICLE
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 >
Open Access
ARTICLE
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 >
Open Access
REVIEW
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 >
Open Access
ARTICLE
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 >
Open Access
REVIEW
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 >
Open Access
REVIEW
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 >
Open Access
REVIEW
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 >
Open Access
ARTICLE
Journal of Information Hiding and Privacy Protection, Vol.1, No.1, pp. 43-48, 2019, DOI:10.32604/jihpp.2019.05797
Abstract At present, the coverless information hiding has been developed. However, due to the limited mapping relationship between secret information and feature selection, it is challenging to further enhance the hiding capacity of coverless information hiding. At the same time, the steganography algorithm based on object detection only hides secret information in foreground objects, which contribute to the steganography capacity is reduced. Since object recognition contains multiple objects and location, secret information can be mapped to object categories, the relationship of location and so on. Therefore, this paper proposes a new steganography algorithm based on object More >
Open Access
ARTICLE
Journal of Information Hiding and Privacy Protection, Vol.1, No.2, pp. 49-60, 2019, DOI:10.32604/jihpp.2019.05881
Abstract A new information hiding technology named coverless information hiding is proposed. It uses original natural images as stego images to represent secret information. The focus of coverless image steganography method is how to represent image features and establish a map relationship between image feature and the secret information. In this paper, we use three kinds of features which are Local Binary Pattern (LBP), the mean value of pixels and the variance value of pixels. On this basis, we realize the transmission of secret information. Firstly, the hash sequence of the original cover image is obtained More >
Open Access
ARTICLE
Journal of Information Hiding and Privacy Protection, Vol.1, No.2, pp. 61-68, 2019, DOI:10.32604/jihpp.2019.05943
Abstract In recent years, with the explosive development in Internet, data storage and data processing technologies, privacy preservation has been one of the greater concerns in data mining. A number of methods and techniques have been developed for privacy preserving data mining. This paper provided a wide survey of different privacy preserving data mining algorithms and analyzed the representative techniques for privacy preservation. The existing problems and directions for future research are also discussed. More >
Open Access
ARTICLE
Journal of Information Hiding and Privacy Protection, Vol.1, No.2, pp. 87-93, 2019, DOI:10.32604/jihpp.2019.07189
Abstract Internet brings us not only the convenience of communication but also some security risks, such as intercepting information and stealing information. Therefore, some important information needs to be hidden during communication. Steganography is the most common information hiding technology. This paper provides a literature review on digital image steganography. The existing steganography algorithms are classified into traditional algorithms and deep learning-based algorithms. Moreover, their advantages and weaknesses are pointed out. Finally, further research directions are discussed. More >
Open Access
REVIEW
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 >
Open Access
ARTICLE
Journal of Information Hiding and Privacy Protection, Vol.1, No.1, pp. 1-10, 2019, DOI:10.32604/jihpp.2019.06043
Abstract Internet of Things (IoT) is an emerging paradigm involving intelligent sensor networks that incorporates embedded technology for collecting data, communicating with external environments. Recently, cloud computing together with fog computing has become an important research area of the Internet of Things because of big data processing capabilities. It is a promising technology that utilizes cloud or fog computing / architecture to improve sensor computing, storage, and communication capabilities. However, recently it has been shown that this computing/architecture may be vulnerable to various attacks because of the openness nature of the wireless network. Therefore, it becomes… More >
Open Access
ARTICLE
Journal of Information Hiding and Privacy Protection, Vol.1, No.2, pp. 69-75, 2019, DOI:10.32604/jihpp.2019.06357
Abstract Relation extraction is an important task in NLP community. However, some models often fail in capturing Long-distance dependence on semantics, and the interaction between semantics of two entities is ignored. In this paper, we propose a novel neural network model for semantic relation classification called joint self-attention bi-LSTM (SA-Bi-LSTM) to model the internal structure of the sentence to obtain the importance of each word of the sentence without relying on additional information, and capture Long-distance dependence on semantics. We conduct experiments using the SemEval-2010 Task 8 dataset. Extensive experiments and the results demonstrated that the More >
Open Access
REVIEW
Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 87-94, 2020, DOI:10.32604/jihpp.2020.09839
Abstract In recent years, with the rapid growth of generative adversarial
networks (GANs), a photo-realistic face can be easily generated from a random
vector. Moreover, the faces generated by advanced GANs are very realistic. It is
reasonable to acknowledge that even a well-trained viewer has difficulties to
distinguish artificial from real faces. Therefore, detecting the face generated by
GANs is a necessary work. This paper mainly introduces some methods to detect
GAN-generated fake faces, and analyzes the advantages and disadvantages of
these models based on the network structure and evaluation indexes, and the
results obtained in More >
Open Access
ARTICLE
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 >