As I continue exploring the foundations of Web3, last week I focused on Smart Contracts and Compact—Midnight’s purpose-built smart contract language. Together, these two elements form the foundation for defining and enforcing logic in privacy-preserving applications.
But logic alone isn’t enough in a decentralized system, especially when privacy is a priority. That’s where zero-knowledge proofs (ZKPs) come in.
ZKPs enable the verification of a statement's truth without revealing the underlying justification. They let applications enforce smart contract rules while keeping sensitive data private—an essential capability for building systems that balance trust, utility, and confidentiality.
In this post, I’ll break down what zero-knowledge proofs are, how they work, and how Midnight uses them to support privacy, compliance, and secure dApp development.
What Are Zero-Knowledge Proofs?
A zero-knowledge proof allows someone (the prover) to prove to another party (the verifier) that a specific statement is true, without revealing any additional information beyond the fact itself.
Think of it like this: instead of handing over your complete ID to prove you're over 18, you could use a ZKP to prove you're above the age threshold, without disclosing your exact birthday, name, or ID number.
This cryptographic technique is built on three foundational properties:
- Completeness: If the statement is true, the prover can convince the verifier that it is true.
- Soundness: If the statement is false, no dishonest prover can convince the verifier that it is true.
- Zero-knowledge: The verifier learns nothing beyond the truth of the statement.
Interactive vs. Non-Interactive Proofs
Early ZKPs required a back-and-forth exchange between prover and verifier—these are called interactive proofs. But in decentralized systems, interaction isn’t always feasible. That’s where non-interactive proofs come in.
Non-interactive ZKPs let a prover generate a single proof that anyone can verify at any time, with no additional input. Protocols like zk-SNARKs and zk-STARKs make this possible, often using techniques like the Fiat–Shamir heuristic to simulate interaction using cryptographic hashes.
This makes non-interactive ZKPs ideal for blockchains, where proofs need to be public, reusable, and verifiable by anyone.
Types of Zero-Knowledge Proof Systems
Different ZKP systems come with different tradeoffs in terms of size, speed, and trust requirements:
- Groth16 (zk-SNARK): Very small proofs, fast verification, but requires a trusted setup per circuit.
- Plonk (zk-SNARK): Slightly larger proofs, slower verification, but only needs a one-time universal setup.
- Bulletproofs: No trusted setup, but proof size grows with complexity.
- zk-STARKs: Transparent (no trusted setup), post-quantum secure, but with large proof sizes.
Midnight utilizes a Plonk-derived system called Halo 2, which supports recursive proofs and eliminates trusted setup in specific configurations, making it an ideal choice for privacy-preserving dApps that require both flexibility and scalability.
How Do ZKPs Work?
The idea behind zero-knowledge proofs might seem almost magical: one party (the prover) can prove to another (the verifier) that a statement is true, without revealing the why. But this is no sleight of hand—it’s grounded in rigorous cryptography and clever use of mathematical structures.
At the heart of a ZKP is a “statement” that the prover wants to validate without revealing the underlying secret. That statement gets encoded into a circuit, which represents the logical rules or constraints that need to be satisfied. The prover then uses a special cryptographic key, known as the proving key, along with the secret input (called the witness), to generate a succinct proof. The verifier can then check this proof using a verifying key, confirming the rules were followed, without ever seeing the private input.
This process makes ZKPs ideal for privacy-preserving smart contracts. In traditional systems, all data must be made public to verify that an action is legitimate. But with ZKPs, we can shift the trust model: rather than inspecting the data itself, the verifier checks a cryptographic proof that the data complies with the rules.
Midnight takes this further by embedding ZKPs directly into the structure and execution of smart contracts. In Midnight, the verification key of a compiled Compact smart contract becomes the identity of that contract on-chain. When users interact with it, they’re not just calling a function—they’re submitting proof that they've complied with the logic defined by that contract, without revealing their inputs.
Here's a high-level flow of how this works:
- Setup: A circuit is created. A proving key and a verifying key are generated.
- Proof Generation: The prover uses their secret (a witness) and the proving key to generate a cryptographic proof.
- Verification: The verifier uses the verifying key and the proof to confirm the statement is true, without learning anything else.
This process ensures that the smart contract logic is executed exactly as intended, without exposing the underlying data.
Midnight’s Approach to ZKPs
Midnight utilizes zero-knowledge proofs not only for theoretical privacy but also to enable real-world compliance and usability. Let’s walk through a few key elements of how ZKPs show up on the Midnight network:
Confidential Transactions
Users can transfer assets on Midnight without revealing the sender, receiver, or amount. ZKPs are used to prove that a transaction is valid (i.e., no double spending, balances add up) without revealing specific details. This ensures both privacy and integrity.
Selective Disclosure and Compliance
Midnight supports “shielded” and “unshielded” data modes. You can keep your transaction data private by default, but also selectively disclose specific information (via a ZKP or viewing key) to a regulator, auditor, or another authorized party.
This enables use cases like “prove I’m a citizen of Country X” or “prove I’m not sanctioned” without revealing your complete identity or wallet history.
For more information about selective disclosure, read my overview here!
Decentralized Identity
ZKPs are key to proving facts about identity without revealing full credentials. Midnight supports workflows like proving KYC status (“A trusted provider has verified me”) using a proof, not a document.
This allows users to interact with services that require identity checks—such as exchanges or marketplaces—without exposing sensitive personal data.
Scalability via Recursive Proofs
ZKPs also compress large computations into tiny proofs. That makes them ideal for batching transactions or reducing blockchain bloat. Midnight’s use of recursive proofs allows smart contracts and transactions to scale more efficiently than traditional blockchains.
Real-World Use Cases on Midnight
Some examples of ZKP-powered applications on Midnight are:
- Voting: Prove you’re eligible to vote and that your vote was counted, without revealing your identity or your vote.
- Whistleblowing: Submit a report anonymously, proving only that you’re authorized (e.g., an employee).
- Private Asset Swaps: Use Midnight’s Zswap to exchange tokens confidentially without revealing terms or participants.
- KYC Onboarding: Prove compliance status to a platform or dApp without exposing documents.
- Tokenized Real-World Assets: Keep ownership private while maintaining auditable transfer records. These use cases show how ZKPs on Midnight turn privacy into a practical feature, not just a theoretical promise. They lay the groundwork for a future where developers can build secure, compliant, and data-protecting applications by default.
Conclusion
Zero-knowledge proofs bring trust to trustless systems. They make it possible to prove something is true—like compliance with laws, asset ownership, or user eligibility—without revealing any sensitive details.
Midnight makes ZKPs more than theoretical. They’re deeply integrated into its smart contract architecture, transaction model, and developer tooling. Paired with the Compact language (covered in last week’s post), they create a robust foundation for building privacy-first decentralized applications.
If you’re interested in learning more, check out:
And if you’ve come across excellent ZKP explanations or tutorials, I’d love to hear about them—please share your favorites!
See you next week as I continue to unpack the core ideas that power privacy in Web3!
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