article · IEEE Access
A multi-image encryption scheme has been developed to protect sensitive satellite imagery against unauthorised access and traffic analysis attacks. The method begins by combining multiple satellite images into a single augmented image, which is then divided into red, green, and blue colour channels. Each channel undergoes a four-stage security process. First, a six-dimensional hyperchaotic system generates a sequence modified by Singular Value Decomposition to execute an initial XOR operation on the image data. Second, the data is partitioned into blocks that undergo RC5 operations. Third, chaotic sequences permute the pixel positions. Finally, a dynamic substitution box generated through the XORshift algorithm obscures remaining pixel values. Numerical testing confirmed resistance to statistical, differential, and brute-force attacks, achieving high security metrics including near-zero cross-correlation and entropy above 7.999.
Satellite imagery plays a vital role in national security and environmental monitoring, but transmitting and storing it via third parties risks interception or traffic analysis. This scheme prevents external entities, such as cloud service providers, from discerning relational patterns between individual images, ensuring high confidentiality and data integrity across remote sensing workflows.
This algorithm is applicable to satellite operators, secure cloud hosting providers, and defence or environmental organisations handling sensitive geospatial imagery. It represents early-stage, applied algorithmic research that has been tested numerically against standard cryptographic benchmarks. Real-world adoption would require software integration into satellite downlink pipelines or secure cloud storage architectures, alongside evaluation of runtime performance and hardware efficiency.
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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 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2^{7016}$ </tex-math></inline-formula>, entropy exceeding 7.999, and a cross-correlation of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\approx 0$ </tex-math></inline-formula>. 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.
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DOI: 10.1109/access.2024.3454512
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