孙光民, 王皓. 基于魔方密码的图像加密解密技术[J]. 北京工业大学学报, 2021, 47(8): 833-841. DOI: 10.11936/bjutxb2020120003
    引用本文: 孙光民, 王皓. 基于魔方密码的图像加密解密技术[J]. 北京工业大学学报, 2021, 47(8): 833-841. DOI: 10.11936/bjutxb2020120003
    SUN Guangmin, WANG Hao. Image Encryption and Decryption Technology Based on Rubik's Cube and Dynamic Password[J]. Journal of Beijing University of Technology, 2021, 47(8): 833-841. DOI: 10.11936/bjutxb2020120003
    Citation: SUN Guangmin, WANG Hao. Image Encryption and Decryption Technology Based on Rubik's Cube and Dynamic Password[J]. Journal of Beijing University of Technology, 2021, 47(8): 833-841. DOI: 10.11936/bjutxb2020120003

    基于魔方密码的图像加密解密技术

    Image Encryption and Decryption Technology Based on Rubik's Cube and Dynamic Password

    • 摘要: 为了提高加密图像的破解难度且不显著增加图像还原时间,提出了一种保护图像数据的方法,它可以解决现存的问题.首先,提出一种动态密码校验技术,其特点是可以扩展密文位数,在明文不变的情况下保证每次产生的密文不同,从而防止密码算法被字典或穷举方法破解,同时可根据计算机系统环境自主调整加密解密性能;其次,提出魔方密码算法,将像素和密码数据重新排列成六面体结构,按照十字轴的形式混淆面与位上的数据,达到加密图像的目的,还原时按照魔方原理以密码数据序列和像素相关性为依据,依次对各个面上的数据进行排列,从而复原已加密的图像.实验结果表明,该方法可以有效防止图像隐私泄露和算法被破解,避免神经网络对像素信息进行重放,可以高效地运行在基于网络的图像系统中.

       

      Abstract: To improve the cracking difficulty of encrypted images and not significantly increase the decryption time, a method to protect image data was proposed in this paper. First, a dynamic cipher verification method was proposed, which expanded the number of cipher text and ensured that the cipher text was different each time when typing the same plaintext so as to prevent the cipher algorithm from being cracked by dictionary or exhaustive method. At the same time, the encryption and decryption performance was adjusted independently according to the computer system environment. Second, the Rubik's cube algorithm was proposed, which the pixel and password data was rearranged into a hexahedral structure, the data on the face and bit was confused according to the form of cross axis, and the purpose of encrypting the image was achieved. According to the Rubik's cube principle, the data on each face was arranged in turn according to the password data sequence and pixel correlation. Experimental results show that this method can effectively prevent image privacy leakage and algorithm cracking, avoid the neural network to replay the pixel information, and run efficiently in the online image recognition system.

       

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