Authors: Mary M. Asia, Dr. John Lenon E. Agatep
Abstract: The healthcare industry is a critical sector globally, directly influencing human life. Ensuring the confidentiality, integrity, and authenticity of health data is paramount for protecting individual privacy. While Advanced Encryption Standard (AES) is widely recognized encryption technique, it has inherent vulnerabilities, particularly in secure key sharing. Compromises in these channels can undermine the overall strength of AES encryption. In response to the rising threat of data breaches, numerous cryptographic algorithms have been developed to protect digital health records and communication. These include symmetric algorithms like the Advanced Encryption Standard (AES) and Data Encryption Standard (DES), and asymmetric algorithms like RSA and Elliptic Curve Cryptography (ECC). This study presents an enhanced AES algorithm integrated with Elliptic Curve Diffie-Hellman (ECDH), which strengthens key management by offering secure key generation and additional cryptographic layers. The research employed an experimental design, utilizing PyCryptodome for implementation, alongside tools such as NumPy, psutil, and Matplotlib for performance testing and analysis. Comparative evaluations between the enhanced AES-ECDH and standard AES algorithm were conducted in terms of execution time, CPU usage, memory consumption, and security analysis. To uphold ethical standards, dummy datasets were used, ensuring no sensitive information was compromised during testing. The findings revealed that while the enhanced AES-ECDH algorithm significantly improves security—offering features like forward secrecy and heightened resistance to various attacks—it comes at the expense of increased resource consumption. Despite this trade-off, enhanced algorithm is highly suitable for scenarios that prioritize data protection over system performance, especially in healthcare environments.
Published by: vikaspatanker
