Srivenkateswaran C, Jaya Mabel Rani A, Senthil Kumaran R, Vinston Raja R
Department of Artificial Intelligence and Data Science, Rajalakshmi Institute of Technology, Chennai, India.
Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India.
Technol Health Care. 2025 May;33(3):1232-1257. doi: 10.1177/09287329241291397. Epub 2024 Nov 25.
The study's novel contribution is the development and evaluation of a hybrid encryption scheme combining Elliptic Curve Cryptography (ECC) with the Serpent symmetric encryption algorithm, demonstrating enhanced security and performance for safeguarding healthcare data in cluster environments while ensuring scalability, interoperability, and compliance with HIPAA regulations. The primary objectives include assessing the suitability of the ECC-Serpent hybrid encryption for safeguarding healthcare data, ensuring the scalability and interoperability of this encryption solution with existing healthcare systems, and implementing secure communication channels within cluster environments. The combination of Elliptic Curve Cryptography (ECC) and the Serpent algorithm leverages ECC's efficient key management and Serpent's robust symmetric encryption to provide enhanced security and performance, ensuring scalable and resilient data protection in cluster environments. This hybrid approach addresses both key distribution efficiency and high encryption strength, which are critical for securing sensitive healthcare data. This hybrid approach addresses key distribution efficiency and high encryption strength, which are critical for securing sensitive healthcare data. The study employs a hierarchical key management strategy, utilizing ECC for secure key exchange and distribution, paired with regular key rotation and storage practices to maintain compliance with HIPAA regulations and ensure the ongoing protection of sensitive healthcare data. Overall, the research underscores the critical need for healthcare organizations to adhere to HIPAA regulations and implement robust encryption measures to protect patient privacy and secure sensitive medical information. The study concludes that the ECC-Serpent hybrid encryption scheme is a viable and effective solution for enhancing healthcare data security in cluster environments, ensuring both data integrity and regulatory compliance. The implemented Python framework yielded promising results, the key finding is that the ECC-Serpent hybrid encryption scheme is a viable and effective solution for enhancing healthcare data security in cluster environments, achieving an accuracy rate of 97.5% in safeguarding patient data.
该研究的新颖贡献在于开发并评估了一种将椭圆曲线密码学（ECC）与蛇形对称加密算法相结合的混合加密方案，证明了其在集群环境中保护医疗数据方面具有更高的安全性和性能，同时确保了可扩展性、互操作性以及符合《健康保险流通与责任法案》（HIPAA）的规定。主要目标包括评估ECC - 蛇形混合加密在保护医疗数据方面的适用性，确保该加密解决方案与现有医疗系统的可扩展性和互操作性，以及在集群环境中实现安全通信通道。椭圆曲线密码学（ECC）和蛇形算法的结合利用了ECC高效的密钥管理和蛇形强大的对称加密，以提供更高的安全性和性能，确保在集群环境中实现可扩展且具弹性的数据保护。这种混合方法解决了密钥分发效率和高加密强度问题，这对于保护敏感医疗数据至关重要。该研究采用分层密钥管理策略，利用ECC进行安全的密钥交换和分发，并结合定期的密钥轮换和存储做法，以保持符合HIPAA规定并确保对敏感医疗数据的持续保护。总体而言，该研究强调了医疗组织遵守HIPAA规定并实施强大加密措施以保护患者隐私和确保敏感医疗信息安全的迫切需求。研究得出结论，ECC - 蛇形混合加密方案是增强集群环境中医疗数据安全性的可行且有效解决方案，可确保数据完整性和法规合规性。所实施的Python框架产生了令人鼓舞的结果，关键发现是ECC - 蛇形混合加密方案是增强集群环境中医疗数据安全性的可行且有效解决方案，在保护患者数据方面的准确率达到了97.5%。
