ISSN 1000-1239 CN 11-1777/TP

Journal of Computer Research and Development ›› 2021, Vol. 58 ›› Issue (5): 1065-1074.doi: 10.7544/issn1000-1239.2021.20200898

Special Issue: 2021人工智能安全与隐私保护技术专题

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Secret Image Sharing Schemes Based on Region Convolution Neural Network

Liu Yanxiao1,2, Wu Ping1, Sun Qindong1   

  1. 1(Faculty of Computer Science and Engineering, Xi’an University of Technology, Xi’an 710048);2(Guangxi Key Laboratory of Trusted Software (Guilin University of Electronic Technology), Guilin, Guangxi 541004)
  • Online:2021-05-01
  • Supported by: 
    This work was supported by the Natural Science Basic Research Project of Shaanxi Province (2019JQ-736), the Youth Innovation Team of Shaanxi Universities, the Guangxi Key Laboratory of Trusted Software (KX202036), and the Project of Xi’an Science and Technology Bureau (GXYD14.12, GXYD14.13).

Abstract: Digital image has become an important information carrier in the era of rapid network development, the security protection of image information has also become an important research topic in the security field. Secret image sharing is a threshold based approach that can protect confidential information in an image among multiple users. This scheme encrypts the secret image into several shadow images according a threshold and distributes them to different users. When the number of users reaches the threshold, the original image can be reconstructed, otherwise the user cannot obtain any information about the original image. The classification and recognition of image information is the premise and basis for image secret sharing, CNN (convolutional neural network) has higher accuracy and faster speed in image classification and recognition. In this paper, we combine CNN based image recognition and classification with secret image sharing together to applying the tool of deep learning in the field of information protection. First, we adopt Faster RCNN (region convolutional neural network) model to segment a secret image into multiple regions, where each region has dierent level, then progressive secret image sharing and secret image sharing with essential shadows are constructed, where the region with higher importance level needs higher threshold in reconstruction, this feature makes the image secret sharing scheme suitable for more application scenarios Compared with traditional image recognition methods based on artificial features, the use of Faster RCNN can greatly improve the efficiency of image classification and recognition, thereby further enhancing the application value of image secret sharing.

Key words: security, secret image sharing, threshold, image recognition, convolutional neural network (CNN)

CLC Number: