Deep Dive into Privacy Enhancing Technologies
summary
Argues privacy as a spectrum and compares concrete tools: ZK, FHE, TEE, MPC; claims FHE can reach ~20 TPS per GPU and parallelize to >100 TPS, but proving (bootstrapping) can take minutes to months (a bootstrap ~20 minutes, a full multiply could take ~28 days to prove). Proposes encryption-based confidential tokens and the Confidential Token Association, and describes Inco: an EVM-compatible private compute layer with an importable library that enables confidential tokens, private voting, hidden randomness for gaming, and a developer setup in 20 minutes.
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chapters (23)
- 0:00Introduction
- 0:31The Privacy Problem in Blockchain
- 1:36Privacy as a Spectrum
- 2:26Pseudonymity and Its Limits
- 3:13Confidentiality Use Cases
- 3:57Anonymity and Total Privacy
- 5:12Choosing the Right Privacy Model
- 5:31Compliance and Privacy
- 5:59Overview of Privacy Technologies (ZK, FHE, TEE, MPC)
- 6:23Fully Homomorphic Encryption (FHE) Explained
- 9:21FHE Challenges and Scalability
- 9:46Trusted Execution Environments (TEE)
- 11:31Commitment vs. Encryption-Based Solutions
- 12:48Flexible Decryption and Compliance
- 13:35Composability in Privacy Systems
- 14:50Confidential Token Ecosystem and Identity
- 15:47Confidential Token Association
- 16:13Introducing Inco: Private Compute Layer
- 17:26Developer Experience and Use Cases
- 18:17Private Voting and Randomness
- 18:56General Purpose Privacy Applications
- 19:13Partnerships and Call to Action
- 19:37Conclusion
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