2. Challenges and Solutions

Challenge 1: Securing the Data Protocol

Data security is fundamental to Hippo Protocol, which employs DIDComm andElliptic Curve Cryptography (ECIES & ECDH) to encrypt and securely transmit data. Hippo Protocol empowers users with self-sovereign identity (SSI) by registering decentralized identifiers (DIDs) with the World Wide Web Consortium (W3C) and issuing millions of DIDs in partnership with leading healthcare institutions, thereby establishing a secure foundation for healthcare data storage and exchange.

Challenge 2: Scaling the Data Protocol

If users encrypt and transmit data directly, this process can lead to inefficiencies and duplication. To solve this, Hippo Protocol introduces Hippo Data Nodes, which offer cryptographic and decentralized data storage. DID holders can delegate data access control using cryptographic signatures (e.g., ECDSA, Schnorr), ensuring transparency through public recording on the Hippo Protocol Blockchain.

But how can we trust Hippo Data & Computation Nodes?

Hippo Data & Computation Nodes operate as a decentralized network of resources, preventing any single entity from manipulating encrypted data. Encryption and decryption require key aggregation from multiple nodes, ensuring security and scalability.

Challenge 3: Incentivizing Data Providers While Ensuring Usability

A key challenge is incentivizing data providers while keeping the data usable. The industry struggles with standardization and pricing of healthcare data, especially when it's encrypted and not directly visible to buyers.

Solution 1: Standardizing Data Format

Hippo Protocol adopts HL7-FHIR, a widely recognized standard in healthcare technology. We actively utilize AI to process and format the user data according to the HL7-FHIR.

Solution 2: Data Valuation Method

There is no established method for determining data value. Also, since data is encrypted at the individual level, so that Hippo Protocol does not have access to the content, Hippo Protocol has to find innovative methods to evaluate the value of the contributed data.

Option 1 (current): Under GDPR or similar regulation frameworks, healthcare data can only be sold to a third party if it is both de-identified and traceable, which makes it very difficult to give different contributors of data varying rewards based on the value of their data. Under HIPAA, healthcare data can be traded as long as it is de-identified and under consent. Therefore, the valuation is heavily dependent on the jurisdiction the owner of the data is in. Hippo Protocol will tackle the issue by dividing the proceeds from the data equally among all the contributors. In this model, users are compensated regardless of their individual data’s contribution to the outcome.

Option 2 (future): Hippo Protocol will leverage Privacy-Preserving AI (e.g., Federated Learning) to determine data value. The system evaluates individual data’s value based on its contribution to the result, ensuring data providers receive fair incentives.