Computationally Efficient and Statistical Attack Resistant Image Encryption System for Smart Healthcare

Medical images are of utmost importance for diagnosing diseases. However, if these images are transmitted through an insecure channel, the risk of unauthorized access significantly rises, potentially leading to the compromise of patients’ sensitive personal information. To rectify these issues, we have proposed an efficient image encryption technique. The proposed scheme works in three stages. In the first stage, the original image undergoes intra-row pixel confusion, followed by row-wise diffusion. The resultant image data undergoes intra-column pixel confusion, followed by column-wise diffusion in the second stage. Finally, the outcome produced from the second stage undergoes another round of intra-row pixel confusion and row-wise diffusion to obtain the final encrypted image. Our scheme employs an improved two-dimensional chaotic map for faster encryption. The method establishes intricate patterns, ensuring strong resistance against cryptographic attacks and unauthorized access. The proposed encryption scheme is competent to achieve the security objectives as it reports average values of IE = 7.9975, CC = 0.0011, NPCR = 99.63%, UACI = 33.52%, and an extremely large key space \(2^{234.219}\) compared to the existing techniques. Experimental results demonstrate its high-level security and acceptable encryption and decryption speeds, making it a viable solution for secure communication, real-time data transfers, and financial transactions. This sophisticated encryption algorithm offers significant advantages over current methods, safeguarding the confidentiality and integrity of visual data in various critical applications like healthcare systems.