A hybrid ECC-AES encryption framework for secure and efficient cloud-based data protection
Abstract In digital healthcare, ensuring the privacy and security of sensitive mental health data remains a critical challenge. This paper introduces SymECCipher, a novel hybrid encryption framework that integrates Elliptic Curve Cryptography (ECC) for key exchange and the Advanced Encryption Standa...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-01315-5 |
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| Summary: | Abstract In digital healthcare, ensuring the privacy and security of sensitive mental health data remains a critical challenge. This paper introduces SymECCipher, a novel hybrid encryption framework that integrates Elliptic Curve Cryptography (ECC) for key exchange and the Advanced Encryption Standard (AES) for data encryption. Unlike conventional encryption models such as RSA-2048 (15ms encryption, 12ms decryption) and AES-256 (6ms encryption, 5ms decryption), SymECCipher achieves significantly lower encryption time (5ms) and decryption time (4ms) while maintaining a high throughput of 1000 Mbps, ensuring secure and efficient data encryption. The proposed methodology is designed to handle secure cloud-based healthcare applications, implemented in the form of User, Doctor, and Cloud Modules to handle patient records and treatment recommendations. This model addresses existing encryption inefficiencies by balancing high-speed cryptographic operations with robust data security, making it suitable for real-time medical data storage and retrieval. Statistical analysis confirms its superior performance, demonstrating a 25–40% reduction in computational overhead compared to traditional cryptosystems. Furthermore, this work outlines the integration of machine learning (ML)-based depression detection within the encrypted framework, ensuring privacy-preserving data analysis. The results highlight SymECCipher’s potential for large-scale healthcare deployment, offering a scalable, quantum-resistant, and blockchain-compatible encryption framework. Future research can be extended by integrating lattice-based cryptography, to enhance quantum security and extending SymECCipher’s applicability to wearable health devices and telemedicine platforms. |
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| ISSN: | 2045-2322 |