ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2018, Vol. 55 ›› Issue (6): 1211-1221.doi: 10.7544/issn1000-1239.2018.20170295

• 信息安全 • 上一篇    下一篇

异或-置乱框架下邻域预测加密域可逆信息隐藏

鄢舒,陈帆,和红杰   

  1. (信号与信息处理四川省重点实验室(西南交通大学) 成都 611756) (yan_shu@126.com)
  • 出版日期: 2018-06-01
  • 基金资助: 
    国家自然科学基金项目(61373180,61461047)

Reversible Data Hiding in Encrypted Image Based on Neighborhood Prediction Using XOR-Permutation Encryption

Yan Shu, Chen Fan, He Hongjie   

  1. (Sichuan Key Laboratory of Signal and Information Processing (Southwest Jiaotong University), Chengdu 611756)
  • Online: 2018-06-01

摘要: 为提高加密图像的安全性和解密图像质量,提出一种异或-置乱框架下邻域预测加密域可逆信息隐藏算法.异或-置乱加密能同时保护原始像素的统计信息和位置信息,减小图像内容泄露的风险.基于密钥伪随机选择加密像素并替换选择像素的最高有效位实现秘密信息的隐藏.图像解密阶段,采用邻域预测推断可能的携密像素并对其像素值进行修正以提高解密图像的质量.图像恢复阶段,利用5个邻域模板计算携密像素的波动性以推断携密像素的最高有效位是否被改变.分析讨论了阈值选取和预测的准确性,对比分析了异或-置乱加密与异或加密生成的加密图像的内容安全性.实验结果表明:所提的邻域预测方法能正确预测出96%以上的携密像素.与现有同类算法相比,所提算法不仅提高了加密图像内容的安全性,而且相同嵌入容量下解密图像的质量高出同类算法5~23dB.

关键词: 信息隐藏, 可逆信息隐藏, 邻域预测, 图像加密, 隐私保护

Abstract: To improve the security of encrypted image as well as the quality of decrypted image, this paper proposes a neighborhood-prediction based reversible data hiding method in encrypted image (RDH-EI) which is generated by XOR-permutation encryption. In this paper, XOR-permutation is conducted to encrypt original image, which can reduce the risk of encrypted content disclosure due to the fact that both statistical information and location information of original pixels are hidden. According to the data hiding key, some encrypted pixels are pseudo-randomly chosen for data hiding, and secret information is embedded into the most significant bit (MSB) of chosen pixels by the bit replacement operation. In the image decryption phase, the possible marked pixels are predicted and corrected by comparing the difference between each pixel and its neighborhood average value to improve the quality of decrypted image. In the image recovery phase, for each marked pixel obtained by the data hiding key, five neighborhood templates are designed to compute its fluctuation value, which is used to deduce whether the MSB of it is changed or not. This paper discusses and analyzes the threshold selection, the prediction accuracy and the security of encrypted image contents. Experimental results demonstrate that the proposed neighborhood prediction method can correctly predict at least 96% marked pixels. The proposed RDH-EI scheme can not only enhance the security of encrypted image content, but also improve the quality of decrypted image, evidenced that the PSNR is about 5~23dB higher than the existing similar RDH-EI methods with the same embedded payload.

Key words: data hiding, reversible data hiding, neighborhood prediction, image encryption, privacy protection

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