A novel approach for encryption and decryption of digital imaging and communications using mathematical modelling in internet of medical things

This research introduces an innovative algorithm for the encryption and decryption of greyscale digital imaging and communications in medicine images utilizing Laplace transforms. The proposed method presents a ground breaking approach to image encryption, effectively concealing visual information and ensuring a robust, secure, and reliable encryption process. By leveraging the inherent strengths of Laplace transform, the algorithm guarantees the complete retrieval of the original image without any loss, provided the correct decryption key is used. To thoroughly evaluate the performance of the algorithm, multiple tests were conducted, including extensive statistical analyses and assessments of encryption quality. Key performance metrics were carefully measured, including correlation coefficients and entropy values, which ranged from 7.89 to 7.99. Additionally, the algorithm's effectiveness was demonstrated through peak signal-to-noise ratio values, which spanned from 7.597 to 9.915, indicating the degree of similarity between the original and encrypted images. Furthermore, the number of pixels change rate values, ranging from 99.519241 to 99.609375, highlighted the algorithm's ability to produce significantly different encrypted images from the original. The unified average changing intensity values, falling between 35.72345678 and 35.78233456, further underscored the algorithm's proficiency in altering pixel intensities uniformly. Overall, this research offers a significant advancement in the field of image encryption, combining theoretical robustness with practical efficiency.