Using Modified Gorti-enhanced Homomorphic Cryptosystem to Improve Security of ECG Signal

While offering vast data storage capabilities, cloud computing poses numerous security- and privacy-related challenges. This requires robust security measures, particularly for sensitive data, such as electrocardiograms (ECG). Homomorphic encryption (HE) emerges as a promising solution by enabling secure computations to be performed directly on encrypted data. This study introduces a novel approach to enhance the security of ECG data. We modified the Gorti-enhanced homomorphic cryptosystem (MEHC) method by optimizing its key generation procedure and then applied the linear congruential generator (LCG) algorithm to create a list of huge prime integers. Furthermore, we increased the modulus value and enlarged the message space. These enhancements boosted overall security by substantially improving immunity to factorization attacks. We used quantization and fixed-point representation to enhance the encryption process. As an additional security layer, an evaluation process has been added to the proposed algorithm which performs various mathematical operations homomorphically on the encrypted data, rather than on the original data. This modified algorithm enables efficient and secure encryption of ECG data while preserving the ability to reliably identify arrhythmias, such as bradycardia and tachycardia. Using the MIT-BIH arrhythmia database, the proposed MEHC system demonstrated high accuracy (98.48%), sensitivity (99.10%) and positive predictive value (99.33%), while effectively safeguarding the ECG data. These results validate the efficacy of the MEHC system and confirm its suitability for secure and reliable ECG signal processing in healthcare applications.