The Different Stages of Privacy: Defining Crypto’s Next Evolution

By Guy Zyskind – MIT PhD in Cryptography, 2x Founder

As Ethereum scaling reaches maturity, the industry’s focus shifts to privacy — but without clear standards, users can’t evaluate competing solutions. We propose a simple framework to guide the next phase of blockchain development.

Why We Need Privacy Stages

The Ethereum scaling race taught us something important: vocabulary shapes progress.
When optimistic vs. zk rollups dominated discussion, the ecosystem eventually created rollup stages — a shared language that clarified roadmaps and accelerated development.

As scaling matures and transaction costs drop, privacy is becoming the next major frontier.
Payment giants like Circle and Stripe are exploring private stablecoins.
Healthcare requires encrypted computation.
Institutions want a confidential settlement.
AI Agents need privacy too.

Yet we have no shared framework for evaluating privacy guarantees.

Dozens of projects across MPC, FHE, and TEE architectures are building solutions, but users can’t meaningfully compare them.

We need privacy stages.

This article introduces a testable, objective taxonomy — similar to rollup stages — focused on the core question:

Who can decrypt your data?
(Just like rollup stages fundamentally ask: who can steal your funds?)

Global Privacy: The Standard We’re Setting

Global privacy means:

• The blockchain’s shared state — balances, contract storage, app data — is encrypted at rest and during computation.
• No single party can decrypt everything.
• The system can still compute on private data to support advanced use cases.

This enables:

• Sealed-bid auctions
• Confidential risk analysis
• Fraud detection without disclosure

This is distinct from local privacy (e.g., Railgun, Privacy Pools), which hides individual inputs but keeps global state visible — limiting composability.

Projects like Aztec and Worldcoin are moving toward global privacy for this reason.

The Technical Foundation: T-out-of-N Security

Privacy security follows a T-out-of-N model:

• T = minimum operators whose collusion breaks privacy
• N = total operators holding decryption authority

Different technologies offer different guarantees:

Trusted Execution Environments (TEEs)

• Very fast, good UX
• But effectively T = 1
• Vendor bugs, firmware flaws, or side-channel attacks can leak everything
• New vulnerabilities appear yearly

Fully Homomorphic Encryption (FHE) & Multi-Party Computation (MPC)

• Cryptographic secret sharing allows configurable T
• Higher T = better privacy
• But N−T+1 operators can halt decryption (liveness tradeoff)

The Privacy Stages Framework

Stage 0 — TEE-Only (“Trust the Box”)

Definition:
Global state is decrypted inside a hardware enclave; observers see only ciphertext.

Pros:

• Excellent performance
• Easy developer experience

Cons:

• T = 1
• Any enclave compromise leaks all data
• Frequent, slow-to-patch vulnerabilities

Use case:
Good for proofs-of-concept and certain ML workloads, but insufficient alone for blockchain privacy.

Stage 1 — Pure Cryptography with Training Wheels

Definition:
FHE/MPC provides encrypted computation with configurable T-out-of-N security, but without hardening features like blocking quorums.

Risk:
If N = 10, T = 7, but 8 operators belong to the same team — privacy can still fail.

Assessment:
More secure than TEE-only, but trust assumptions must be scrutinized.

Stage 2 — Blocking Quorum + Defense-in-Depth

Definition:
Cryptographic protection (FHE/MPC) is reinforced with additional safeguards:

• Distributed key generation (no trusted setup)
• Independent, non-colluding operator set
• Optional TEEs as extra layers
• Permissionless operation
• Economic incentives and penalties

Outcome:
The practical gold standard — privacy breaches require either major cryptographic failure or massive, coordinated collusion.

Stage ℵ (Aleph) — Indistinguishable Obfuscation

Definition:
Theoretical end-state where programs themselves become the vault, eliminating key management.

Reality:
Not practical today — relies on heavy assumptions and fragile constructions.
Best seen as a long-term north star.

Privacy’s Moment Has Arrived

Institutional demand is rising:

• Payment processors need confidential settlement
• Healthcare requires encrypted computation
• Financial institutions want private liquidity
• Global enterprises face compliance requirements transparent chains cannot meet

This time, privacy adoption is driven not by speculation but by real business needs.

Setting the Standard

Privacy technology has matured — but without clear evaluation criteria, distinguishing real security from marketing is nearly impossible.

The privacy stages framework:

• Creates shared benchmarks
• Helps users make informed choices
• Encourages competition and technical progress
• Aligns ecosystem development
• Mirrors what rollup stages did for Layer 2s

The infrastructure exists. The demand is here.
Now we need the taxonomy.

Privacy stages are the foundation for crypto’s next evolution — enabling privacy as a first-class blockchain primitive, not an optional add-on.

Conclusion

Standards accelerate progress.
Privacy stages give the ecosystem a way to evaluate, compare, and meaningfully discuss privacy systems as crypto enters a new era.

Teams adopting this framework help move the industry toward clarity, accountability, and real privacy — built for the future, not the past.