# Privacy-Preserving Data Sharing in Telehealth Services
## 4 Analysis and Evaluation
Additionally, the use of two-factor authentication, including biometrics, is justified by the need for stringent security measures that go beyond traditional password-based systems, providing a necessary layer of security to protect sensitive health information. **Encryption Method**: The proposed model uses homomorphic encryption to ensure that patient data remain encrypted both at rest and during computations. This allows for secure data processing without decrypting the sensitive information, maintaining confidentiality. Homomorphic encryption enables various mathematical operations on encrypted data, preserving privacy even when data are processed or analyzed. This method significantly improves data security in comparison to traditional encryption schemes, which require data to be decrypted before use. **Data Integrity**: Ensuring data integrity is crucial for maintaining trust in telemedicine systems. The proposed model achieves this by leveraging blockchain technology, which provides an immutable ledger for storing encrypted data. Each transaction on the blockchain is verified through cryptographic hashing, ensuring that any unauthorized modifications to patient data are immediately detected. This approach offers a transparent and verifiable method for maintaining the integrity of sensitive healthcare records, making it resistant to tampering or unauthorized changes. **Access Control**: Access control in the proposed model is implemented through the use of smart contracts on the blockchain. These smart contracts automatically enforce patient-defined permissions before granting access to any data, ensuring that only authorized parties can view or modify the information. This approach enables precise control over data sharing, complying with regulatory requirements like the HIPAA and the GDPR. By automating access control through smart contracts, the model minimizes the risk of unauthorized access while maintaining flexibility in managing data permissions. **Scalability**: The proposed model addresses scalability challenges by incorporating secure multi-party computation (SMPC) to enable computations on encrypted data. SMPC allows multiple parties to collaborate on data analysis without exposing individual inputs, making it suitable for large-scale applications in telemedicine. Additionally, by using blockchain technology, the system can efficiently manage increasing data volumes without compromising security, ensuring that it remains adaptable to the needs of expanding healthcare networks and larger user bases. **User Anonymity**: To preserve user anonymity, the proposed model utilizes encryption and pseudonymization techniques, ensuring that personal identifiers are not directly linked to health data. This approach ensures that even if the encrypted data are accessed, the user's identity remains protected. By dissociating personal details from medical records, the model enhances privacy, making it compliant with stringent data protection regulations and minimizing the risk of identity theft. **Authentication Method**: The model integrates a dual-layer authentication mechanism combining biometric verification with traditional credentials. This ensures that only authorized users can access sensitive medical data, significantly reducing the risk of unauthorized access. Biometric authentication, such as fingerprint or facial recognition, adds a robust security layer, making it difficult for attackers to impersonate legitimate users. This dual approach enhances the overall security of the telemedicine system. **Threats Addressed**: The proposed model is designed to counter a wide range of cybersecurity threats, from impersonation attacks to data breaches. It employs advanced cryptographic techniques and blockchain-based auditing to protect against unauthorized access. By addressing various attack vectors, such as replay attacks and MITM (Man-In-The-Middle) attacks, the model ensures secure communication and data integrity.