Refined RSA Encryption Algorithm to Safeguard Privacy in Healthcare Data

In the medical domain, patient data is extensively employed for disease processing and prediction. Unfortunately, these data are often publicly accessible and lack adequate privacy safeguards. Cryptography emerges as a pivotal solution in addressing this concern Methods: This study delves into diverse techniques to fortify the security of clinical records against unauthorized access. Safeguarding patient data necessitates the integration of various machine learning and encryption algorithms. However, current algorithms fall short of effectively securing this data. The research utilizes a sample patient dataset comprising 20,000 records, encompassing information such as name, age, date of birth, gender, and illness type. The proposed algorithm's performance is evaluated based on parameters like accuracy, precision, recall, f-measure, and Root Mean Square Error. Findings: We introduce the Enhanced Asymmetric Cryptography Algorithm (RSA) algorithm, a novel approach aimed at heightening data privacy. RSA, utilizing intricate mathematics, ensures the confidentiality and reliability of sensitive information, making it challenging for unauthorized entities to decipher. The encryption technique primarily focuses on shielding data from intruders seeking unauthorized access. Novelty: Analysis of algorithm performance reveals that the Improved RSA algorithm surpasses the existing RSA algorithm, achieving an accuracy of 95.2%. This underscores the superior effectiveness of the proposed algorithm in securing sensitive data through a more sophisticated approach.