As blockchain technology evolves, the need for scalability and privacy has become more apparent. Traditional blockchains like Ethereum and Bitcoin are transparent, meaning anyone can verify transactions. However, this transparency comes at the cost of privacy and efficiency. To address this, zero-knowledge proofs (ZKPs) have emerged as powerful cryptographic tools.
Two major implementations of ZKPs in blockchain are zk-SNARKs and zk-STARKs. Both allow one party to prove to another that a statement is true without revealing any underlying information and with minimal computational resources. These technologies are critical in Layer 2 scaling solutions, privacy-preserving protocols, and decentralized applications.
This guide breaks down zk-SNARKs and zk-STARKs in a step-by-step format, comparing their strengths, weaknesses, and use cases in the blockchain world.
What Are Zero-Knowledge Proofs?
A Zero-Knowledge Proof (ZKP) allows a “prover” to convince a “verifier” that they know a value or solution to a computation without revealing what the value or solution is.
Example:
- You can prove you are over 18 without revealing your actual age.
- You can prove you own a private key without revealing it.
ZKPs have three key properties:
- Completeness: If the statement is true, a verifier will be convinced.
- Soundness: If the statement is false, a cheating prover can’t convince the verifier.
- Zero-knowledge: The verifier learns nothing other than the truth of the statement.
What are zk-SNARKs?
zk-SNARK stands for:
Zero-Knowledge Succinct Non-Interactive Argument of Knowledge
Key Properties:
- Zero-Knowledge: The verifier learns nothing about the actual data.
- Succinct: Proofs are extremely small and fast to verify.
- Non-Interactive: Only one message is sent from prover to verifier (no back-and-forth).
- Argument of Knowledge: The proof is computationally sound.
How zk-SNARKs Work (Simplified):
- The prover sets up a program (computation) that they want to prove they can run correctly.
- During a trusted setup phase, cryptographic keys are generated.
- The prover runs the computation and generates a short proof.
- The verifier uses the proof and public key to verify the computation without running it.
Example Use Case:
- Zcash uses zk-SNARKs to enable private transactions where the sender, receiver, and amount are hidden but the transaction is still valid.
Pros:
- Very fast verification time.
- Very small proof size (hundreds of bytes).
Cons:
- Requires a trusted setup, which if compromised, could break the system.
- Uses complex cryptography (elliptic curves, pairing-based cryptography).
What are zk-STARKs?
zk-STARK stands for:
Zero-Knowledge Scalable Transparent Argument of Knowledge
Key Properties:
- Zero-Knowledge: Privacy-preserving like zk-SNARKs.
- Scalable: Supports very large computations efficiently.
- Transparent: No trusted setup required.
- Argument of Knowledge: Secure against quantum attacks.
How zk-STARKs Work (Simplified):
- The computation is converted into a series of math problems using polynomial representations.
- These are encoded using Merkle trees and hash functions.
- The proof is generated and sent to the verifier.
- The verifier checks the proof using public randomness without re-running the original computation.
Example Use Case:
- StarkNet (by StarkWare) uses zk-STARKs to batch thousands of Ethereum transactions off-chain and post a single proof on-chain.
Pros:
- No trusted setup, making it more secure and transparent.
- Post-quantum secure (resistant to quantum computers).
- Scales efficiently with computation size.
Cons:
- Proof sizes are larger (tens to hundreds of kilobytes).
- Slower to verify compared to zk-SNARKs.
zk-SNARKs vs zk-STARKs: Comparison Table
| Feature | zk-SNARKs | zk-STARKs |
|---|---|---|
| Trusted Setup | Required | Not required |
| Proof Size | Small (100s of bytes) | Larger (tens to 100s of KB) |
| Verification Speed | Very fast | Moderate |
| Transparency | Less transparent (trusted setup) | Fully transparent |
| Quantum Resistance | Not secure | Secure |
| Computation Scalability | Moderate | Highly scalable |
| Used In | Zcash, Tornado Cash | StarkNet, dYdX v4 |
Use Cases in Blockchain
1. Privacy Coins
- Zcash: Uses zk-SNARKs to hide transaction data.
2. Layer 2 Rollups
- zkSync: Uses zk-SNARKs to reduce transaction cost and congestion on Ethereum.
- StarkNet: Uses zk-STARKs for scalable, private dApps.
3. Decentralized Identity
- Proving attributes (e.g., nationality, age) without revealing full identity.
4. Gaming and NFTs
- Verifying NFT authenticity or in-game achievements off-chain.
5. Audits and Proof of Solvency
- Crypto exchanges proving solvency without revealing wallets.
Challenges in Adoption
- Complexity: ZKPs are mathematically intensive and hard to implement securely.
- Hardware Constraints: Generating proofs (especially for zk-STARKs) requires significant computing power.
- Lack of Standards: Different projects adopt different proof systems, making interoperability harder.
The Future of ZK Proofs
- As Ethereum and other blockchains scale, ZK-rollups (powered by SNARKs and STARKs) are becoming mainstream.
- More zk-friendly hardware and software tools are being developed.
- Cross-chain ZK proofs may enable private and scalable interoperability.
- Web3 apps will rely heavily on verifiable computation, making ZKPs a core building block.