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  • Open Access


    Conceptual Modeling and Simulation Application Analysis of In-service Assessment

    Jian-Hua Luo1, Xi Chen1,*, Hua Li1, Yu-Hang Zhou1, Jing-Wen Li2

    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


    A Survey of Anti-forensic for Face Image Forgery

    Haitao Zhang*

    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 aspects: conventional processing, fake face… More >

  • Open Access


    Intrusion Detection System Using a Distributed Ensemble Design Based Convolutional Neural Network in Fog Computing

    Aiming Wu1, Shanshan Tu1,*, Muhammad Wagas1,2,3, Yongjie Yang1, Yihe Zhang1, Xuetao Bai1

    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 be transferred to the fog… More >

  • Open Access


    An Overview of Adversarial Attacks and Defenses

    Kai Chen*, Jinwei Wang, Jiawei Zhang

    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 examples are called adversarial examples.… More >

  • Open Access


    SPN-Based Performance Analysis of Multiple Users’ Behaviors for SNS

    Zhiguo Hong1,*, Yongbin Wang2,3, Minyong Shi4

    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 the characteristics of social network… More >

  • Open Access


    A Performance Study of Membership Inference Attacks on Different Machine Learning Algorithms

    Jumana Alsubhi1, Abdulrahman Gharawi1, Mohammad Alahmadi2,*

    Journal of Information Hiding and Privacy Protection, Vol.3, No.4, pp. 193-200, 2021, DOI:10.32604/jihpp.2021.027871

    Abstract Nowadays, machine learning (ML) algorithms cannot succeed without the availability of an enormous amount of training data. The data could contain sensitive information, which needs to be protected. Membership inference attacks attempt to find out whether a target data point is used to train a certain ML model, which results in security and privacy implications. The leakage of membership information can vary from one machine-learning algorithm to another. In this paper, we conduct an empirical study to explore the performance of membership inference attacks against three different machine learning algorithms, namely, K-nearest neighbors, random forest, support vector machine, and logistic… More >

  • Open Access


    An Explanatory Strategy for Reducing the Risk of Privacy Leaks

    Mingting Liu1, Xiaozhang Liu1,*, Anli Yan1, Xiulai Li1,2, Gengquan Xie1, Xin Tang3

    Journal of Information Hiding and Privacy Protection, Vol.3, No.4, pp. 181-192, 2021, DOI:10.32604/jihpp.2021.027385

    Abstract As machine learning moves into high-risk and sensitive applications such as medical care, autonomous driving, and financial planning, how to interpret the predictions of the black-box model becomes the key to whether people can trust machine learning decisions. Interpretability relies on providing users with additional information or explanations to improve model transparency and help users understand model decisions. However, these information inevitably leads to the dataset or model into the risk of privacy leaks. We propose a strategy to reduce model privacy leakage for instance interpretability techniques. The following is the specific operation process. Firstly, the user inputs data into… More >

  • Open Access


    A Survey on Binary Code Vulnerability Mining Technology

    Pengzhi Xu1,2, Zetian Mai1,2, Yuhao Lin1, Zhen Guo1,2,*, Victor S. Sheng3

    Journal of Information Hiding and Privacy Protection, Vol.3, No.4, pp. 165-179, 2021, DOI:10.32604/jihpp.2021.027280

    Abstract With the increase of software complexity, the security threats faced by the software are also increasing day by day. So people pay more and more attention to the mining of software vulnerabilities. Although source code has rich semantics and strong comprehensibility, source code vulnerability mining has been widely used and has achieved significant development. However, due to the protection of commercial interests and intellectual property rights, it is difficult to obtain source code. Therefore, the research on the vulnerability mining technology of binary code has strong practical value. Based on the investigation of related technologies, this article firstly introduces the… More >

  • Open Access


    Verifiable Privacy-Preserving Neural Network on Encrypted Data

    Yichuan Liu1, Chungen Xu1,*, Lei Xu1, Lin Mei1, Xing Zhang2, Cong Zuo3

    Journal of Information Hiding and Privacy Protection, Vol.3, No.4, pp. 151-164, 2021, DOI:10.32604/jihpp.2021.026944

    Abstract The widespread acceptance of machine learning, particularly of neural networks leads to great success in many areas, such as recommender systems, medical predictions, and recognition. It is becoming possible for any individual with a personal electronic device and Internet access to complete complex machine learning tasks using cloud servers. However, it must be taken into consideration that the data from clients may be exposed to cloud servers. Recent work to preserve data confidentiality has allowed for the outsourcing of services using homomorphic encryption schemes. But these architectures are based on honest but curious cloud servers, which are unable to tell… More >

  • Open Access


    Pixel Based Steganography for Secure Information Hiding

    N. Shyla*, K. Kalimuthu

    Journal of Information Hiding and Privacy Protection, Vol.3, No.3, pp. 143-149, 2021, DOI:10.32604/jihpp.2021.026760

    Abstract The term “steganography” is derived from the Greek words steganos, which means “verified, concealed, or guaranteed”, and graphein, which means “writing”. The primary motivation for considering steganography is to prevent unapproved individuals from obtaining disguised data. With the ultimate goal of comprehending the fundamental inspiration driving the steganography procedures, there should be no significant change in the example report. The Least Significant Bit (LSB) system, which is one of the methodologies for concealing propelled picture data, is examined in this assessment. In this evaluation, another procedure for data stowing indefinitely is proposed with the ultimate goal of limiting the progressions… More >

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