Satellite image encryption using amalgamation of randomized three chaotic maps and DNA encoding
Mohit Dua, Rahul Bhogal, Shelza Dua, Nidhi Chakravarty · Physica Scripta · 2024
Abstract In today’s world of critical global connectivity, satellite communication plays a vital role for businesses, governments, and individuals. Key applications, including climate change monitoring, military surveillance, and real-time event broadcasting, heavily rely on transmitting image data rather than text. As a result, ensuring the secure transmission of images through efficient and robust encryption techniques has become a focal point of interest for both academia and industry. Image encryption is essential for securing sensitive visual data, protecting privacy, and making certain that only authorized users are able to access the required content. It prevents unauthorized access, tampering, and misuse of images, which is crucial for confidential and secure communications. The work in this paper develops a satellite image encryption scheme that employs a novel 1D Cosine Sinusoidal Chaotic (1DCSC) map, and two earlier proposed Sine-Tangent Chaotic (STC) and Improved Cosine Fractional Chaotic (ICFCM) maps, in conjunction with Deoxyribonucleic Acid (DNA) operations. The proposed scheme encrypts a given input image in four steps. In the initial step, 384-bit shared key and a 128-bit initial vector are used to create three different keys. In step two, three different chaotic sequences are produced using these keys and 1DCSC, STC, and ICFCM maps. These chaotic sequences chosen randomly to encrypt red, blue or green components of the given input image. In step three, these three chaotic sequences and the three components of the input image are DNA encoded. In the final step, DNA XOR based diffusion operation is applied between these DNA-encoded color image components and DNA encoded chaotic sequences to create green, red, and blue components of the cipher image. The proposed scheme obtains entropy value 7.9997, Unified Average Changing Intensity (UACI) value 33.32, and Number of Pixels Change Rate (NPCR) value 99.67%.