Closed CraigOpie closed 1 year ago
This project requires an evaluation and comparison of privacy-preserving techniques compatible with Hyperledger Fabric, such as Zero Knowledge Proofs (ZKPs), Secure Multi-Party Computation (MPC), and homomorphic encryption, to determine the most suitable techniques based on the requirements outlined above.
I have created a Decision Making Matrix (DMM) to evaluate and compare the three privacy-preserving techniques. The DMM has a scoring system of 1 to 5 for the criteria of scalability, compliance, privacy, security, and efficiency. The breakdown and reasoning for each row are provided below the DMM.
Technique | Scalability | Compliance | Privacy | Security | Efficiency |
---|---|---|---|---|---|
Zero Knowledge Proofs (ZKPs) | 3 | 5 | 5 | 5 | 3 |
Secure Multi-Party Computation | 2 | 4 | 4 | 4 | 2 |
Homomorphic Encryption | 1 | 4 | 5 | 5 | 1 |
Zero Knowledge Proofs (ZKPs)
Secure Multi-Party Computation (MPC)
Homomorphic Encryption
Based on the DMM, Zero Knowledge Proofs (ZKPs) is the best-fitting technique, as it has the highest overall score and best matches the given requirements. ZKPs meet the specific needs for managing API access for embedded IoT devices and health records, allowing anonymous access to information, and ensuring scalability and compliance with Department of Defense and HIPAA requirements. Although ZKPs might have limitations in terms of computational efficiency, they provide the necessary security, privacy, and compliance needed for this use case.
Description: Research privacy-preserving techniques compatible with the chosen blockchain platform.