Jena Riyanka, Singh Priyanka, Mohanty Manoranjan
Research Group for Security and Privacy, Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar 382004, India.
School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane 4072, Australia.
J Imaging. 2023 Aug 27;9(9):172. doi: 10.3390/jimaging9090172.
The widespread availability of digital image-processing software has given rise to various forms of image manipulation and forgery, which can pose a significant challenge in different fields, such as law enforcement, journalism, etc. It can also lead to privacy concerns. We are proposing that a privacy-preserving framework to encrypt images before processing them is vital to maintain the privacy and confidentiality of sensitive images, especially those used for the purpose of investigation. To address these challenges, we propose a novel solution that detects image forgeries while preserving the privacy of the images. Our method proposes a privacy-preserving framework that encrypts the images before processing them, making it difficult for unauthorized individuals to access them. The proposed method utilizes a compression quality analysis in the encrypted domain to detect the presence of forgeries in images by determining if the forged portion (dummy image) has a compression quality different from that of the original image (featured image) in the encrypted domain. This approach effectively localizes the tampered portions of the image, even for small pixel blocks of size 10×10 in the encrypted domain. Furthermore, the method identifies the featured image's JPEG quality using the first minima in the energy graph.
数字图像处理软件的广泛应用引发了各种形式的图像操纵和伪造行为,这在执法、新闻等不同领域可能构成重大挑战。它还可能引发隐私问题。我们提出,在处理图像之前对其进行加密的隐私保护框架对于维护敏感图像的隐私和机密性至关重要,尤其是那些用于调查目的的图像。为应对这些挑战,我们提出了一种新颖的解决方案,该方案在保护图像隐私的同时检测图像伪造。我们的方法提出了一个隐私保护框架,在处理图像之前对其进行加密,使未经授权的个人难以访问这些图像。所提出的方法利用加密域中的压缩质量分析,通过确定加密域中伪造部分(虚拟图像)的压缩质量是否与原始图像(特征图像)不同来检测图像中是否存在伪造。即使对于加密域中大小为10×10的小像素块,这种方法也能有效地定位图像的篡改部分。此外,该方法使用能量图中的第一个最小值来识别特征图像的JPEG质量。