Enhancing Satellite Image Security Through Multiple Image Encryption Via Hyperchaos, SVD, RC5, and Dynamic S-Box Generation

In this paper, a novel image encryption scheme is presented that leverages a combination of hyperchaotic systems, Singular Value Decomposition (SVD), RC5 operations, permutation techniques, and a custom S-box generated via the XORshift algorithm. Multiple satellite images are merged into a single augmented image prior to encryption by this algorithm, effectively protecting against traffic analysis attacks that could compromise individual encrypted images. Once the augmented image is created, it is split into RGB color channels, and each channel undergoes a four-stage encryption process. The encryption process is initiated by the generation of a chaotic sequence from a six-dimensional (6D) hyperchaotic system. This initial key sequence is then manipulated and transformed into a new key using SVD. The transformed key sequence is utilized to XOR the original image, providing an initial layer of encryption. Subsequently, the image is divided into blocks, and RC5 operations are applied to each block to enhance the security of the encryption process. Following this, a permutation operation is performed on the image using the chaotic sequence generated earlier. Finally, an S-box, created from a random sequence generated by the XORshift algorithm, is applied to the image to further obscure the pixel values. The robustness of the algorithm is validated by numerical tests, demonstrating its effectiveness against both statistical, differential attacks and brute-force attacks, making it extremely difficult for third parties, such as cloud service providers, to identify any relational patterns between the encrypted satellite images. Specific numerical values that demonstrated an enhanced security level include a key space of 27016, entropy exceeding 7.999, and a cross-correlation of ≈ 0. This encryption method not only strengthens the protection of satellite imagery against unauthorized access but also ensures the integrity and confidentiality of the images, which are crucial for applications ranging from national security to environmental monitoring in an increasingly data-driven world.