一个混合ECC-AES加密框架以实现基于云的安全和高效数据保护
1Department of Computer Science and Engineering, Research scholar, Anna University, Chennai, Tamil Nadu, India. selviresearch24@gmail.com.
Scientific reports
|August 22, 2025
概括
SymECCipher为数字心理健康数据提供了更高的安全性. 这种混合加密框架使用圆曲线加密和高级加密标准,以在医疗保健应用中更快,更安全地处理数据.
科学领域:
- 数字医疗安全
- 加密框架
- 在医疗领域的数据隐私
背景情况:
- 在数字医疗保健中保护敏感的心理健康数据是一个重大挑战.
- 现有的加密方法在速度和计算开销方面存在低效.
- 需要对基于云的医疗应用程序提供强大,高效的加密解决方案.
研究的目的:
- 推出SymECCipher,一个用于数字心理健康数据的新型混合加密框架.
- 评估SymECCipher与传统加密模型的性能.
- 证明该框架适用于安全的基于云的医疗保健应用程序和保护隐私的数据分析.
主要方法:
- 结合圆曲线加密 (ECC) 进行密钥交换和高级加密标准 (AES)进行数据加密.
- 开发用户,医生和云模块来管理患者记录和治疗建议.
- 在加密框架内实施基于机器学习 (ML) 的低压检测.
主要成果:
- 与RSA-2048和AES-256相比,SymECCipher的加密 (5ms) 和解密 (4ms) 时间显著降低.
- 该框架显示了1000Mbps的高吞吐量,确保了高效的数据处理.
- 统计分析证实计算开销减少了25-40%,表现出卓越的性能.
结论:
- 提供可扩展,抗量子和区块链兼容的安全数字心理健康数据解决方案.
- 该框架提高了实时医疗数据存储和检索的效率.
- SymECCipher显示了大规模医疗部署的潜力,包括与ML集成用于隐私保护分析.
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