System for secure sharing of private data

System for secure sharing of private data

Secure data sharing system:

Private data registration: Private data providers can register data on a secure platform, which is protected by encryption and TEE technology.

Distributed ledger records: The security of TEE and the registration information of private data are recorded on a distributed ledger (such as blockchain) to ensure the transparency and immutability of information.

Data access control: After receiving the user's access instruction, the system triggers the secure transmission of data to TEE for processing, and records the granting of access rights.

Private data verification:

Authenticity verification: The system provides a variety of methods to verify the authenticity of private data, including comparing non-genotype information with genotype data, calculating linkage disequilibrium (LD) scores, etc.

Pseudo-twin model: By matching individuals with similar genomic information (pseudo-twins), the risk of an individual suffering from a certain disease is estimated.

Incentive and reward mechanism:

Token system: Private data users need to pay tokens to access data, and these tokens can be allocated to data providers on the distributed ledger as rewards.

Contribution evaluation: The allocation of tokens is based on the contribution of private data to the prediction model, encouraging the provision of high-quality data.

Application of distributed ledgers:

Smart contracts: Control data access conditions and reward distribution through smart contracts to ensure automatic execution and credibility of transactions.

Transparency and trust: Distributed ledgers provide open and transparent records, so that the security of TEE and the sharing conditions of data can be trusted by all participants.

Technical implementation:

Secure execution environment (TEE): Such as Intel SGX or ARM TrustZone, used to provide a secure data processing environment.

Cryptography: Encrypt and decrypt private data using encryption keys provided by TEE to ensure the security of data during transmission and processing.

Privacy protection:

Anonymous communication: Ensure privacy protection during communication by generating new point-to-point message identifiers.

Obfuscated circuits: Use obfuscated circuit technology to verify the characteristics of data while protecting the identities of senders and receivers.

Application scenarios:

Medical research: Improve the accuracy of disease prediction models by sharing and analyzing genomic data.

Insurance fraud detection: Use shared data platforms to detect and prevent insurance fraud.

Topic: Please briefly describe the main applications of artificial intelligence (AI) in the medical field.

Answer:

Artificial intelligence is widely used in the medical field, mainly including the following aspects:

Diagnostic assistance: AI can assist doctors in disease diagnosis by analyzing medical images (such as X-rays and MRI scans), improving the accuracy and efficiency of diagnosis.

Drug development: AI technology can accelerate the drug development process, and predict the effectiveness and side effects of drugs by simulating and analyzing the interaction between drugs and organisms.

Patient monitoring: AI systems can monitor patients' health status in real time, including physiological indicators such as heart rate and blood pressure, and predict health risks by analyzing patients' daily activities.

Personalized medicine: Based on the patient's genetic information, living habits and disease history, AI can help doctors develop more personalized treatment plans.

Medical robots: AI-driven robots can be used for tasks such as surgical operations, rehabilitation training, and patient care, reducing the workload of medical staff.

These applications have made AI play an increasingly important role in the medical field and improved the efficiency and quality of medical services.