A Mathematical Approach to Enhance Cybersecurity in AI-Driven Healthcare Diagnostics Using J-Transform
Prabakaran Raghavendran, Tharmalingam Gunasekar · Advances in computational intelligence and robotics book series · 2025
In this paper, we propose a new method of encryption and decryption that relies on the mathematical tool J-Transform to secure data in the form of complex transformations. The sound theoretical foundation of the proposed method is the application of J-Transform to functions of exponential order. Our method consists of converting the plaintext into numeric form, dividing the data into fixed-size blocks, and using a block cipher for encryption. The process works by taking a numeric sequence to construct the polynomial representation. Then apply modular transformations. Finally, execute the J-Transform to produce ciphertext. The decryption process is all explained and uses inverse transformations to actually recover the plaintext. Each stage of transformation is also graphically represented with graphical representation to show that the process of J-Transforming introduces non-linearity to the complexity of the data. This methodology improves the security of the data but ensures the integrity of the original message. It is a great contribution to cryptography.