| Resumen |
In the context of smart cities, where the deployment of surveillance systems and security cameras is becoming increasingly ubiquitous, the efficient management of digital images and their confidentiality has become a critical challenge. In this work, we present an innovative scheme which considers two components: compressive sensing and S-Boxes for image compression and confusion property in the Shannon’s information theory context, respectively. The integration of these two building blocks provides a comprehensive solution for the efficient and secure transmission of image data in urban environments. Our scheme expands the compressed image into a 24-bit RGB image and uses three S-Boxes to replace the information of each color channel. One of the new features is that the S-Boxes evolve based on a key. In this sense, the scheme offers a solution for smart cities aiming to optimize the management of digital image data and simultaneously achieving the security of transmitted information. The processed images have been analyzed, and obtained to show that our scheme brings perceptual and cryptographic security to digital images, without compromising the recovered image. Its implementation can significantly contribute to efficiency and security, in the use of surveillance cameras in modern urban environments of smart cities. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. |
