# Privacy-Preserving Data Sharing in Telehealth Services
## 3 Method  
The proposed algorithm employs blockchain technology and advanced cryptographic techniques to establish a secure and privacy-preserving framework for healthcare data management in telemedicine. Initially, the algorithm encrypts patient health data using homomorphic encryption, ensuring that only encrypted data are managed or accessed, which protects the data from unauthorized access. These encrypted data are then stored on a blockchain, providing a secure, immutable record that supports data integrity and auditability. The system facilitates secure data access and sharing through secure multi-party computation (SMPC), allowing computations on encrypted data without revealing individual inputs, thus maintaining data confidentiality. Access control and permission management are implemented using smart contracts on the blockchain, which check and enforce the patient-set permissions before any operations are performed, ensuring compliance with patient preferences and legal standards. The framework includes mechanisms for data integrity auditing and compliance monitoring, where each transaction is verifiable against blockchain integrity checks and compliance with regulations like the HIPAA or the GDPR. This comprehensive approach demonstrates a robust system for managing sensitive health data, effectively balancing security, privacy, and regulatory compliance. Homomorphic encryption (HE) is a form of encryption that allows computations to be performed on ciphertexts, generating an encrypted result that, when decrypted, matches the result of operations performed on the plaintext. This method is pivotal in our framework as it enables the performing of complex data analyses securely without exposing the underlying data. Specifically, our implementation uses a partially homomorphic encryption scheme, which supports both addition and multiplication on encrypted data but limits the depth of these operations to maintain manageable computation times. Secure multi-party computation (SMPC) further enhances this by allowing multiple parties to jointly compute a function over their inputs while keeping those inputs private. In our framework, SMPC is implemented via a protocol that combines homomorphic encryption with threshold cryptography to ensure that no single party can access the full scope of the data or computation results. The process involves distributing decryption keys among a predefined number of parties, where a subset is required to collaborate to decrypt the result, thus ensuring data privacy and security throughout the computation process. These technologies are integrated into our proposed framework using established cryptographic libraries that support scalability and efficiency, such as Microsoft SEAL for HE and MP-SPDZ for SMPC. By providing detailed descriptions and specific examples of these implementations, we aim to clarify their applications and operational frameworks within our proposed system, offering readers a clearer understanding of how privacy and data integrity are maintained. **Step 1: Data Encryption**  
Patients encrypt their data using their private key before they are shared or stored, ensuring that only encrypted data are handled by other parties  
* **Equation**: \(\mathrm{C}=\mathrm{E}_{\mathrm{kp}}(\mathrm{D})\)  
* D: original patient health data. * \(\mathrm{k}_{\mathrm{p}}\): patient's private key. * C: encrypted data. * E: encryption function using homomorphic encryption. **Step 2: Secure Data Storage**  
Encrypted data C are securely stored on the blockchain, providing a decentralized and immutable record. * **Equation**: \(\mathrm{B}=\mathrm{append}(\mathrm{C})\)  
* B: blockchain storage. append: function to add encrypted data C to the blockchain. **Step 3: Data Access and Sharing using SMPC**  
SMPC protocols compute functions on encrypted data from multiple parties, ensuring that no party learns anything about the others' inputs besides the final result. * **Equation**: R = f(C1, C2,..., Cn)
* **Explanation**:  
* Ci: encrypted input data from the i-th party.