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  • Open Access

    ARTICLE

    Deep Learning for Distinguishing Computer Generated Images and Natural Images: A Survey

    Bingtao Hu*, Jinwei Wang

    Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 95-105, 2020, DOI:10.32604/jihpp.2020.010464

    Abstract With the development of computer graphics, realistic computer graphics (CG) have become more and more common in our field of vision. This rendered image is invisible to the naked eye. How to effectively identify CG and natural images (NI) has been become a new issue in the field of digital forensics. In recent years, a series of deep learning network frameworks have shown great advantages in the field of images, which provides a good choice for us to solve this problem. This paper aims to track the latest developments and applications of deep learning in the field of CG and… More >

  • Open Access

    REVIEW

    A Survey of GAN-Generated Fake Faces Detection Method Based on Deep Learning

    Xin Liu*, Xiao Chen

    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 the respective data sets. On… More >

  • Open Access

    ARTICLE

    A Novel Image Retrieval Method with Improved DCNN and Hash

    Yan Zhou, Lili Pan*, Rongyu Chen, Weizhi Shao

    Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 77-86, 2020, DOI:10.32604/jihpp.2020.010486

    Abstract In large-scale image retrieval, deep features extracted by Convolutional Neural Network (CNN) can effectively express more image information than those extracted by traditional manual methods. However, the deep feature dimensions obtained by Deep Convolutional Neural Network (DCNN) are too high and redundant, which leads to low retrieval efficiency. We propose a novel image retrieval method, which combines deep features selection with improved DCNN and hash transform based on high-dimension features reduction to gain lowdimension deep features and realizes efficient image retrieval. Firstly, the improved network is based on the existing deep model to build a more profound and broader network… More >

  • Open Access

    ARTICLE

    Image Retrieval Based on Deep Feature Extraction and Reduction with Improved CNN and PCA

    Rongyu Chen, Lili Pan*, Yan Zhou, Qianhui Lei

    Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 67-76, 2020, DOI:10.32604/jihpp.2020.010472

    Abstract With the rapid development of information technology, the speed and efficiency of image retrieval are increasingly required in many fields, and a compelling image retrieval method is critical for the development of information. Feature extraction based on deep learning has become dominant in image retrieval due to their discrimination more complete, information more complementary and higher precision. However, the high-dimension deep features extracted by CNNs (convolutional neural networks) limits the retrieval efficiency and makes it difficult to satisfy the requirements of existing image retrieval. To solving this problem, the high-dimension feature reduction technology is proposed with improved CNN and PCA… More >

  • Open Access

    ARTICLE

    Design and Implementation of Log Data Analysis Management System Based on Hadoop

    Dunhong Yao1,2,3,*, Yu Chen4

    Journal of Information Hiding and Privacy Protection, Vol.2, No.2, pp. 59-65, 2020, DOI:10.32604/jihpp.2020.010223

    Abstract With the rapid development of the Internet, many enterprises have launched their network platforms. When users browse, search, and click the products of these platforms, most platforms will keep records of these network behaviors, these records are often heterogeneous, and it is called log data. To effectively to analyze and manage these heterogeneous log data, so that enterprises can grasp the behavior characteristics of their platform users in time, to realize targeted recommendation of users, increase the sales volume of enterprises’ products, and accelerate the development of enterprises. Firstly, we follow the process of big data collection, storage, analysis, and… More >

  • Open Access

    REVIEW

    A Survey on Adversarial Example

    Jiawei Zhang*, Jinwei Wang

    Journal of Information Hiding and Privacy Protection, Vol.2, No.1, pp. 47-57, 2020, DOI:10.32604/jihpp.2020.010462

    Abstract In recent years, deep learning has become a hotspot and core method in the field of machine learning. In the field of machine vision, deep learning has excellent performance in feature extraction and feature representation, making it widely used in directions such as self-driving cars and face recognition. Although deep learning can solve large-scale complex problems very well, the latest research shows that the deep learning network model is very vulnerable to the adversarial attack. Add a weak perturbation to the original input will lead to the wrong output of the neural network, but for the human eye, the difference… More >

  • Open Access

    ARTICLE

    Smart Contract Fuzzing Based on Taint Analysis and Genetic Algorithms

    Zaoyu Wei1,*, Jiaqi Wang2, Xueqi Shen1, Qun Luo1

    Journal of Information Hiding and Privacy Protection, Vol.2, No.1, pp. 35-45, 2020, DOI:10.32604/jihpp.2020.010331

    Abstract Smart contract has greatly improved the services and capabilities of blockchain, but it has become the weakest link of blockchain security because of its code nature. Therefore, efficient vulnerability detection of smart contract is the key to ensure the security of blockchain system. Oriented to Ethereum smart contract, the study solves the problems of redundant input and low coverage in the smart contract fuzz. In this paper, a taint analysis method based on EVM is proposed to reduce the invalid input, a dangerous operation database is designed to identify the dangerous input, and genetic algorithm is used to optimize the… More >

  • Open Access

    REVIEW

    A Survey on Face Anti-Spoofing Algorithms

    Meigui Zhang*, Kehui Zeng, Jinwei Wang

    Journal of Information Hiding and Privacy Protection, Vol.2, No.1, pp. 21-34, 2020, DOI:10.32604/jihpp.2020.010467

    Abstract The development of artificial intelligence makes the application of face recognition more and more extensive, which also leads to the security of face recognition technology increasingly prominent. How to design a face anti-spoofing method with high accuracy, strong generalization ability and meeting practical needs is the focus of current research. This paper introduces the research progress of face anti-spoofing algorithm, and divides the existing face anti-spoofing methods into two categories: methods based on manual feature expression and methods based on deep learning. Then, the typical algorithms included in them are classified twice, and the basic ideas, advantages and disadvantages of… More >

  • Open Access

    ARTICLE

    Research on Prevention of Citrus Anthracnose Based on Image Retrieval Technology

    Xuefei Du*, Xuyu Xiang

    Journal of Information Hiding and Privacy Protection, Vol.2, No.1, pp. 11-19, 2020, DOI:10.32604/jihpp.2020.010114

    Abstract Citrus anthracnose is a common fungal disease in citrus-growing areas in China, which causes very serious damage. At present, the manual management method is time-consuming and labor-consuming, which reduces the control effect of citrus anthracnose. Therefore, by designing and running the image retrieval system of citrus anthracnose, the automatic recognition and analysis of citrus anthracnose control were realized, and the control effect of citrus anthracnose was improved. In this paper, based on the self-collected and collated citrus anthracnose image database, we use three image features to realize an image retrieval system based on citrus anthracnose through SMV, AP clustering optimization.… More >

  • Open Access

    ARTICLE

    Research on Denoising of Cryo-em Images Based on Deep Learning

    Jianquan Ouyang*, Yi He, Huanrong Tang, Zhousong Fu

    Journal of Information Hiding and Privacy Protection, Vol.2, No.1, pp. 1-9, 2020, DOI:10.32604/jihpp.2020.010657

    Abstract Cryo-em (Cryogenic electron microscopy) is a technology this can build bio-macromolecule of three-dimensional structure. Under the condition of now, the projection image of the biological macromolecule which is collected by the Cryo-em technology that the contrast is low, the signal to noise is low, image blurring, and not easy to distinguish single particle from background, the corresponding processing technology is lagging behind. Therefore, make Cryoem image denoising useful, and maintaining bio-macromolecule of contour or signal of function-construct improve Cryo-em image quality or resolution of Cryo-em three-dimensional structure have important effect. This paper researched a denoising function base on GANs (generative… More >

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