Special lssues
Table of Content

Information Hiding and Multimedia Security

Submission Deadline: 15 March 2020 (closed)

Guest Editors

Prof. Chin-Chen Chang, Feng Chia University, Taiwan
Prof. Dan Feng, Huazhong University of Science and Technology, China
Prof. Yongfeng Huang, Tsinghua University, China


The development of the Internet, the popularity of the e-government and e-commerce pose new challenges to the secure storage, secure transmission and secure access of information. As a new technology to ensure information security, information hiding has attracted many scholars' interest and has become a research hotspot all over the world. This special issue aims to provide an academic platform for researchers in this field to exchange new ideas, new methods, and new technologies. Submissions on information hiding and related information security topics are welcomed. The excellent papers of 15th Chinese national Information Hiding and multimedia information security Workshop (CIHW2019) will be considered for inclusion in the Special Issue. All submitted papers will undergo the Journal's standard peer-review process. The official website of CIHW is http://www.cihw.org.cn

Topics of interests include, but are not limited to:
• Information hiding theory and model;

• Steganography and steganalysis;

• Digital watermarking and digital rights management (DRM);

• Digital watermarking technology and anti-counterfeiting;

• Unconventional carrier information hiding;

• Digital forensics;

• Software protection;

• Multimedia data retrieval and certification;

• Wireless communication security;

• Data transmission security;

• Information content security;

• Encrypted domain signal processing;

• Multimedia security in cloud computing;

• Big data security privacy protection;

• Cryptography.


Information Hiding; Steganography; Steganalysis; Multimedia Security

Published Papers

  • Open Access


    3D Multilayered Turtle Shell Models for Image Steganography

    Ji-Hwei Horng, Juan Lin, Yanjun Liu, Chin-Chen Chang
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 879-906, 2020, DOI:10.32604/cmes.2020.09355
    (This article belongs to the Special Issue: Information Hiding and Multimedia Security)
    Abstract By embedding secret data into cover images, image steganography can produce non-discriminable stego-images. The turtle shell model for data hiding is an excellent method that uses a reference matrix to make a good balance between image quality and embedding capacity. However, increasing the embedding capacity by extending the area of basic structures of the turtle shell model usually leads to severe degradation of image quality. In this research, we innovatively extend the basic structure of the turtle shell model into a three-dimensional (3D) space. Some intrinsic properties of the original turtle shell model are well More >

  • Open Access


    Multiple Images Steganography of JPEG Images Based on Optimal Payload Distribution

    Yang Pei, Xiangyang Luo, Yi Zhang, Liyan Zhu
    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 417-436, 2020, DOI:10.32604/cmes.2020.010636
    (This article belongs to the Special Issue: Information Hiding and Multimedia Security)
    Abstract Multiple images steganography refers to hiding secret messages in multiple natural images to minimize the leakage of secret messages during transmission. Currently, the main multiple images steganography algorithms mainly distribute the payloads as sparsely as possible in multiple cover images to improve the detection error rate of stego images. In order to enable the payloads to be accurately and efficiently distributed in each cover image, this paper proposes a multiple images steganography for JPEG images based on optimal payload redistribution. Firstly, the algorithm uses the principle of dynamic programming to redistribute the payloads of the… More >

  • Open Access


    Coverless Text Hiding Method Based on Improved Evaluation Index and One-Bit Embedding

    Ning Wu, Yi Yang, Lian Li, Zhongliang Yang, Poli Shang, Weibo Ma, Zhenru Liu
    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1035-1048, 2020, DOI:10.32604/cmes.2020.010450
    (This article belongs to the Special Issue: Information Hiding and Multimedia Security)
    Abstract In the field of information hiding, text is less redundant, which leads to less space to hide information and challenging work for researchers. Based on the Markov chain model, this paper proposes an improved evaluation index and onebit embedding coverless text steganography method. In the steganography process, this method did not simply take the transition probability as the optimization basis of the steganography model, but combined it with the sentence length in the corresponding nodes in the model to gauge sentence quality. Based on this, only two optimal conjunctions of the current words are retained More >

  • Open Access


    Image Information Hiding Method Based on Image Compression and Deep Neural Network

    Xintao Duan, Daidou Guo, Chuan Qin
    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.2, pp. 721-745, 2020, DOI:10.32604/cmes.2020.09463
    (This article belongs to the Special Issue: Information Hiding and Multimedia Security)
    Abstract Image steganography is a technique that hides secret information into the cover image to protect information security. The current image steganography is mainly to embed a smaller secret image in an area such as a texture of a larger-sized cover image, which will cause the size of the secret image to be much smaller than the cover image. Therefore, the problem of small steganographic capacity needs to be solved urgently. This paper proposes a steganography framework that combines image compression. In this framework, the Vector Quantized Variational AutoEncoder (VQ-VAE) is used to achieve the compression More >

  • Open Access


    Enhancing Embedding-Based Chinese Word Similarity Evaluation with Concepts and Synonyms Knowledge

    Fulian Yin, Yanyan Wang, Jianbo Liu, Meiqi Ji
    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.2, pp. 747-764, 2020, DOI:10.32604/cmes.2020.010579
    (This article belongs to the Special Issue: Information Hiding and Multimedia Security)
    Abstract Word similarity (WS) is a fundamental and critical task in natural language processing. Existing approaches to WS are mainly to calculate the similarity or relatedness of word pairs based on word embedding obtained by massive and high-quality corpus. However, it may suffer from poor performance for insuf- ficient corpus in some specific fields, and cannot capture rich semantic and sentimental information. To address these above problems, we propose an enhancing embedding-based word similarity evaluation with character-word concepts and synonyms knowledge, namely EWS-CS model, which can provide extra semantic information to enhance word similarity evaluation. The More >

  • Open Access


    Constructive Texture Steganography Based on Compression Mapping of Secret Messages

    Fengyong Li, Zongliang Yu, Chuan Qin
    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.1, pp. 393-410, 2020, DOI:10.32604/cmes.2020.09452
    (This article belongs to the Special Issue: Information Hiding and Multimedia Security)
    Abstract This paper proposes a new constructive texture synthesis steganographic scheme by compressing original secret messages. First, we divide the original message into multiple bit blocks, which are transferred to decimal values and compressed into small decimal values by recording their interval sign characters. Then, a candidate pattern is generated by combining the given source pattern and boundary extension algorithm. Furthermore, we segment the candidate pattern into multiple candidate patches and use affine transformation algorithm to locate secret positions on a blank canvas, which are used to hide the sign characters by mapping the candidate patches. More >

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