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Mind Network has pioneered a quantum-resistant fully homomorphic encryption ($FHE) infrastructure that drives a fully encrypted Internet through secure data and AI computing. Outlook on several future areas of FHE
AI field
- Privacy protection for AI as a service (AIaaS): Users encrypt the original data and upload it to the cloud server. The server performs homomorphic computing on the ciphertext and generates encrypted output and returns it to the user. Only the user can decrypt the result, ensuring data privacy.
- Recommendation system that protects consumer privacy: Use FHE to build a recommendation system. When providing personalized recommendations to users, ensure that the recommended content is kept confidential to the system and protect user preference information.
Medical field
- Encrypted medical data sharing and analysis: Patient medical data is uploaded to the service provider in encrypted form. Medical institutions can process and analyze the encrypted data, which not only protects patient privacy, but also facilitates medical research and disease diagnosis.
- Privacy-protected telemedicine monitoring: Through FHE technology, the patient's physiological data collected by telemedicine equipment can be encrypted, transmitted and processed, and doctors can analyze and diagnose without accessing plaintext data.
DeFi field
- Privacy-protected transactions: FHE enables transactions and capital flows without leaking sensitive financial information, reducing market risks and protecting user privacy.
- Compliance and risk control: Financial institutions can conduct risk analysis on encrypted transaction data to meet privacy regulations and prevent data leakage.
Game field
- Protect player data privacy: Players' scores, game progress and other data are protected in an encrypted state, while allowing game logic to run on the chain without exposing data, enhancing game fairness and security.
- Privacy-protected virtual item transactions: In in-game virtual item transactions, the use of FHE can protect the privacy information of both parties to the transaction, such as transaction amount, item attributes, etc.
