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    王垚飞

    • 副教授 硕士生导师
    • 教师英文名称:Yaofei Wang
    • 教师拼音名称:Wang Yaofei
    • 所在单位:计算机与信息学院
    • 学历:博士研究生毕业
    • 性别:男
    • 学位:工学博士学位
    • 在职信息:在职
    • 毕业院校:中国科学技术大学
    • 2020-12-31曾获荣誉当选:博士研究生国家奖学金

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    Improving the embedding strategy for batch adaptive steganography

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    所属单位:中国科学技术大学

    发表刊物:International Workshop on Digital Forensics and Watermarking

    刊物所在地:South Korea

    摘要:Recent works have demonstrated that images with more texture regions should be selected as the sub-batch of covers to carry the total message when applying batch steganography to adaptive steganography and the core challenge of which is how to evaluate the texture complexity of image accurately according to the need of steganography security. In this paper, we first propose three methods for measuring the texture complexity of image to select images with highly textured content, then put forward our universal embedding strategy for batch adaptive steganography in both spatial and JPEG domain. To assess the security of embedding strategies for batch adaptive steganography, we use a pooling steganalysis method based majority decision for the omniscient Warden, who informed by the average payload, embedding algorithm and cover source. Given a batch of images, our proposed embedding strategy is to select images with largest residual values to carry the total message, which is named max-residual-greedy (MRG) strategy. Experimental results show that the proposed embedding strategy outperforms the previous ones for batch adaptive steganography. © 2019, Springer Nature Switzerland AG.

    论文类型:论文集

    学科门类:工学

    文献类型:C

    卷号:11378

    页面范围:248-260

    ISSN号:03029743

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    收录刊物:SCI、EI