U-TPE:用于无损恢复的通用近似缩略图保留加密方法

IF 2.6 4区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Haiju Fan , Shaowei Shi , Ming Li
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引用次数: 0

摘要

由于本地存储空间有限,越来越多的人习惯将图片上传到云端,这引起了人们对隐私泄露的担忧。传统的解决方案是直接加密图片。然而,这样一来,用户就无法轻松浏览存储在云中的图像。显然,传统方法失去了云图像的可视化可用性。为了解决这个问题,我们提出了缩略图保留加密(TPE)方法。虽然近似 TPE 比理想 TPE 更有效,但它无法无损还原原始图像,也无法加密一些具有纹理特征的图像。受上述启发,我们提出了一种无损恢复的通用近似缩略图保留加密方法。该方法将图像分成大小相等的块,每个块又分为嵌入区和调整区。嵌入区的像素通过预测被记录下来。然后,将还原图像所需的辅助信息加密并隐藏在加密图像的嵌入区中。最后,调整每个区块中调整区域的像素值,使其平均值接近原始区块。实验结果表明,所提出的方法不仅能无损还原图像,还能处理具有不同纹理特征的图像,实现了良好的通用性。在 BOWS2 数据集上,通过调整块大小,可以加密所有图像。此外,它还能抵御第三方的人脸识别和对比,在平衡隐私性和视觉可用性方面取得了令人满意的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
U-TPE: A universal approximate thumbnail-preserving encryption method for lossless recovery
Due to the limited local storage space, more and more people are accustomed to uploading images to the cloud, which has aroused concerns about privacy leaks. The traditional solution is to encrypt the images directly. However, in this way, users cannot easily browse the images stored in the cloud. Obviously, the traditional method has lost the visual usability of cloud images. To solve this problem, the Thumbnail-Preserving Encryption (TPE) method is proposed. Although approximate-TPE is more efficient than ideal TPE, it cannot restore the original image without damage and cannot encrypt some images with texture features. Inspired by the above, we propose a universal approximate thumbnail-preserving encryption method with lossless recovery. This method divides the image into equal-sized chunks, each of which is further divided into an embedding area and an adjustment area. The pixels of the embedding area are recorded by prediction. Then, the auxiliary information necessary to restore the image is encrypted and hidden in the embedding area of the encrypted image. Finally, the pixel values of the adjustment area in each block are adjusted so that the average value is close to the original block. Experimental results show that the proposed method can not only restore images losslessly but also process images with different texture features, achieving good generality. On the BOWS2 dataset, all images can be encrypted by adjusting the block size. In addition, it can resist third-party face recognition and comparison, achieving satisfactory results in balancing privacy and visual usability.
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来源期刊
Journal of Visual Communication and Image Representation
Journal of Visual Communication and Image Representation 工程技术-计算机:软件工程
CiteScore
5.40
自引率
11.50%
发文量
188
审稿时长
9.9 months
期刊介绍: The Journal of Visual Communication and Image Representation publishes papers on state-of-the-art visual communication and image representation, with emphasis on novel technologies and theoretical work in this multidisciplinary area of pure and applied research. The field of visual communication and image representation is considered in its broadest sense and covers both digital and analog aspects as well as processing and communication in biological visual systems.
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