Security in Medical Image Management Using Ant Colony Optimization

Abstract

Data encryption before transmission is still a crucial step in lowering security concerns in cloud-based environments. Steganography and image encryption methods validate the security of confidential data while it is being transmitted over the Internet. The paper presents the Ant Colony Optimization with Encryption Curve cryptography-based steganography technique to enhance the security of medical image management (ACO-ECC-SMIM). The initial stage is to create the stego images for the used cover image, the ACO algorithm-based image steganography technique is used. The creation of the encryption process is a key focus of the suggested ACO-ECC-SMIM strategy. The encryption process is initially carried out using an ECC technique, or elliptic curve cryptography. To maximize PSNR, the ACO technique is employed to optimize the crucial production process in the ECC model. The host image is subjected to an integer wavelet transform, and the coefficients have been altered. To determine the ideal coefficients where to conceal the data, the ACO optimization technique is utilized. The decryption and sharing reconstruction procedures are then carried out on the receiver side to create the original images. In image 1, the ACO-ECC-SMIM model showed an improved PSNR of 59.37dB. Image 5 has an improved PSNR of 59.53dB thanks to the ACO-ECC-SMIM model. A large-scale experimental investigation was conducted to show the improved performance of the proposed PIOE-SMIM method, and the findings demonstrated the superiority of the ACO-ECC-SMIM model over other approaches.