Setting Up a Zero-Knowledge Proof System for Grade Privacy

Private grade verification addresses a core privacy issue in academia and employment: proving you meet a threshold (e.g., "graduated with honors") without disclosing your exact GPA or individual course scores. Traditional methods require sharing full transcripts, exposing sensitive data. A zero-knowledge proof (ZKP) system enables a student to generate a cryptographic proof that their grades satisfy a specific condition, which a verifier (like an employer) can check without learning any other information. This shifts trust from the data itself to the validity of the cryptographic proof.

Setting up such a system involves several key components. First, you need a circuit, which is a program that defines the constraint to be proven (e.g., weighted_average(grades) > 3.5). This circuit is written in a ZKP domain-specific language like Circom or Noir. Second, a trusted setup phase generates public parameters (a Proving Key and Verification Key) for the circuit. Finally, the student uses the proving key and their private inputs (grades) to generate a proof, which is verified on-chain or off-chain using the verification key.

Here is a conceptual outline of a Circom circuit for verifying a GPA is above a 3.5 threshold:

circomCopy
pragma circom 2.0.0;
template GPAVerifier() {
    // Private inputs: individual grades and credits
    signal private input grade1;
    signal private input credit1;
    // ... more grades
    signal input threshold;
    // Public output: 1 if condition met, 0 otherwise
    signal output verified;
    // Calculate weighted sum and total credits
    component weightedSum = WeightedSum();
    // Compare calculated GPA to threshold
    component comparator = GreaterThan();
    verified <== comparator.out;
}

The student would provide their private grades to this circuit to generate a proof of the statement.

For production, you must integrate this proving system with an identity layer. A student's grades must be cryptographically signed by the issuing institution (e.g., a university's private key) to prevent forgery. The ZKP circuit then verifies this signature as part of its logic, ensuring the proven grades are authentic. Platforms like Semaphore or zkSNARKs libraries such as snarkjs are commonly used to manage identity and proof generation in Ethereum applications.

The main challenges include the computational cost of proof generation (which can be high for complex circuits) and the need for a secure initial trusted setup. However, with frameworks like Circom and Hardhat plugins, developers can compile circuits, run trusted setups, and test verification contracts. This enables the creation of a system where a student can share a single, reusable proof credential for multiple verifiers, fundamentally enhancing privacy in credential verification.

To build a zero-knowledge proof (ZKP) system for grade privacy, you need a foundational understanding of cryptographic primitives and a modern development environment. The core concept is to prove a statement like "my grade is an A (≥90%)" without disclosing the exact score. This requires a circuit compiler to express the logic and a proving system to generate and verify proofs. We will use Circom for circuit design and the SnarkJS library for proof generation and verification, as they are the most mature tools in the Ethereum ecosystem for this task.

First, ensure your system meets the prerequisites. You will need Node.js (v18 or later) and npm installed. For compiling Circom circuits, you must install the Rust toolchain, as the Circom compiler is written in Rust. On a Unix-based system (Linux/macOS), you can install these using your package manager. Windows users are recommended to use WSL2 for a consistent experience. Verify your installations by running node --version, npm --version, and rustc --version in your terminal.

Next, install the specific ZKP tooling. Install the Circom compiler globally via npm: npm install -g circom. This provides the circom command to compile circuits written in the Circom language into R1CS (Rank-1 Constraint System) and Wasm components. Then, install SnarkJS: npm install -g snarkjs. SnarkJS is a JavaScript library that handles the entire ZKP workflow: performing the trusted setup, generating proofs, and verifying them on-chain or off-chain.

With the tools installed, set up a new project directory. Initialize a Node.js project with npm init -y and create a basic folder structure: circuits/ for your .circom files, build/ for compilation artifacts, and scripts/ for utility scripts. Your first circuit, grades.circom, will define the constraints for proving a grade threshold. A critical step is downloading a Powers of Tau file for the trusted setup. You can download a pre-generated file for a circuit with up to 2^14 constraints using SnarkJS: snarkjs powersoftau new bn128 14 pot14_0000.ptau.

Finally, understand the development workflow. You will 1) write the logic in Circom, 2) compile the circuit to R1CS and Wasm, 3) perform a phase 1 trusted setup with the Powers of Tau, 4) calculate the circuit-specific phase 2 setup, 5) generate a witness from private inputs, and 6) create and verify a proof. Each proof demonstrates that a secret grade meets a public threshold, enabling privacy-preserving verification for applications like job applications or credential checks without leaking sensitive data.

A zero-knowledge proof (ZKP) system for grade privacy allows a student to prove they have achieved a certain academic standing—like graduating with honors or passing a course—without disclosing their exact transcript. The core architecture involves three main parties: the Issuer (the university), the Prover (the student), and the Verifier (an employer or another institution). The system's security and privacy rely on cryptographic commitments and succinct proofs, ensuring the verifier learns only the validity of the claim, not the sensitive data behind it.

The process begins with credential issuance. The university acts as a trusted authority, generating a cryptographic commitment to the student's grade data. This commitment, often a Merkle root of a hash tree containing all student records, is published to a public ledger or a verifiable data registry. The student receives a signed credential, which includes their specific grade data and a cryptographic proof (like a Merkle proof) that links their data to the public commitment. This establishes the credential's authenticity and immutability.

When proof is required, the student becomes the Prover. Using a ZK-SNARK or ZK-STARK circuit—written in a language like Circom or Noir—the student generates a proof. This circuit encodes the logic of the claim (e.g., "My GPA is > 3.5"). The prover inputs their private grade data and the Merkle proof from their credential. The ZK circuit executes the computation, verifying the data is valid against the public commitment and that the GPA condition holds, all without exposing the inputs. The output is a small, easily verified proof.

The Verifier receives only the proof and the public parameters: the circuit's verification key, the public commitment (Merkle root), and the statement to be verified (e.g., "GPA > 3.5"). By running the efficient verification algorithm, the verifier can be cryptographically assured the claim is true, with trust rooted in the university's original signature. This architecture decouples verification from data disclosure, enabling privacy-preserving checks for scholarships, job applications, or credit transfers.

Key technical considerations include the choice of proving system (ZK-SNARKs require a trusted setup but have small proofs, while ZK-STARKs are transparent but larger), the data availability of the public commitments, and the design of the credential format. Standards like W3C Verifiable Credentials and IETF SD-JWT can be integrated to ensure interoperability. The system must also account for key management for issuers and the potential need for credential revocation, which can be handled via accumulator schemes or status lists.

The first step in building a zero-knowledge proof (ZKP) system for grade privacy is to define the circuit logic. A ZK circuit is a set of arithmetic constraints that a prover must satisfy. For our use case, the circuit must prove two things: that a submitted grade is within the valid range (e.g., 0-100) and that it matches the hash of the official grade stored on-chain, all without revealing the grade itself. We use Circom (Circuit Compiler), a popular language for writing ZK circuits that compile to the R1CS (Rank-1 Constraint System) format used by proof systems like Groth16.

Our circuit will have two primary private inputs (known only to the prover): the actual grade and a secret salt. The single public input (known to the verifier) will be the computed gradeHash. The core logic uses a GreaterThan and LessThan template to enforce the range, and the Poseidon hash function—a ZK-friendly hash—to compute the commitment. The circuit's output is a binary signal verifying all constraints are met. Here's a simplified interface for our main circuit component:

circomCopy
template GradeProof() {
    signal input grade;
    signal input salt;
    signal input gradeHash;
    // ... constraints go here
}

A critical design consideration is selecting the right hash function. Standard hashes like SHA-256 are computationally expensive in a ZK context. We use Poseidon, a hash function built for efficiency in arithmetic circuits, which is available in the circomlib library. The circuit will compute calculatedHash = Poseidon([grade, salt]) and enforce that calculatedHash == gradeHash. This proves the prover knows a grade and salt that produce the public hash, without disclosing them.

Finally, we must define the numeric field for our arithmetic. Circom circuits operate over a finite field, typically the scalar field of the BN254 curve (used by Ethereum). This means all inputs and computations are modulo a large prime number (~254 bits). Grades must be converted into field elements. The range check 0 <= grade <= 100 must be implemented using field arithmetic, ensuring no underflow or overflow. Using pre-built circomlib comparators like GreaterEqThan and LessEqThan handles this safely.

Once the Circom code is written, it is compiled. The compiler outputs the R1CS constraint system and a witness generator (in WebAssembly). These artifacts are used in the next steps: generating proofs with snarkjs and integrating the verifier into a smart contract. Proper circuit design is foundational; a flawed constraint can create security vulnerabilities or allow false proofs.

The core challenge is to create a system where a student can prove they have a grade above a certain threshold (e.g., "Prove my grade is > 90%") without revealing the exact score. To do this, you need a backend service that can attest to the authenticity of the student's grade data. This service acts as a trusted data source, or oracle, for the zero-knowledge circuit. It must securely fetch the raw grade from the institutional database, sign it cryptographically, and provide it to the student's client for proof generation.

A typical integration uses a REST API endpoint, such as GET /api/grade/{studentId}/attestation. When called with proper authentication, this endpoint queries the gradebook database, retrieves the student's numeric grade, and returns a signed message containing the grade and a nonce to prevent replay attacks. The signature is created using the backend's private key, and the corresponding public key is hardcoded into the ZK circuit. This allows the circuit to verify that the grade data came from the authorized source before using it in any computations.

Here is a simplified Node.js example of the attestation endpoint using the ethers library for signing:

javascriptCopy
app.get('/api/grade/:studentId/attestation', authMiddleware, async (req, res) => {
  const grade = await db.getGrade(req.params.studentId); // e.g., 85
  const nonce = Date.now();
  const messageHash = ethers.utils.solidityKeccak256(
    ['uint256', 'uint256'],
    [grade, nonce]
  );
  const signature = await wallet.signMessage(ethers.utils.arrayify(messageHash));
  res.json({ grade, nonce, signature });
});

The student's ZK client then uses this grade, nonce, and signature tuple as a private input to generate the proof.

Security considerations are paramount. The backend must implement robust authentication (like OAuth 2.0 with the university's SSO) to ensure only the legitimate student can request their own attestation. The signing key must be stored securely, preferably in a hardware security module (HSM) or a cloud key management service. Furthermore, the attestation should have a short expiration time (e.g., 5 minutes) by including a timestamp in the signed message, mitigating the risk of using an old grade in a proof.

Finally, the ZK circuit logic must mirror this verification. The circuit's public inputs will include the nonce and the signature, while the grade remains a private input. The circuit verifies the signature against the known backend public key and the hash of the (grade, nonce) pair. Only if this check passes will it proceed to the core business logic, such as proving grade > threshold. This two-step verification—off-chain signature check and on-chain proof verification—ensures the integrity and privacy of the entire system.

Client-side proof generation is the core privacy mechanism. Using a ZK-SNARK library like SnarkJS with Circom, the student's browser generates a cryptographic proof that their grade satisfies the verification logic defined in the circuit. The process requires two key inputs: the private witness (the actual grade and student ID) and the public signal (the hash of the grade commitment stored on-chain). The proof attests to the statement: "I know a grade g and ID id such that hash(g, id) = publicCommitment and g >= passingThreshold", without revealing g or id.

To implement this, you first compile the Circom circuit (grading.circom) into an intermediate format. Then, using a trusted setup ceremony (like the Powers of Tau), you generate the proving key and verification key. The proving key is used client-side, while the verification key is used by the verifier contract. In JavaScript, the generation looks like this:

javascriptCopy
const { proof, publicSignals } = await snarkjs.groth16.fullProve(
  { grade: 85, studentId: 12345, threshold: 70 },
  "circuit.wasm",
  "proving_key.zkey"
);

This proof object and the publicSignals (containing the public commitment hash) are the outputs sent to the verifier.

The security of this step relies on the zero-knowledge and succinctness properties of the proof system. The generated proof is small (a few kilobytes) and can be verified in milliseconds on-chain, but it is computationally intensive to create, taking several seconds client-side. This asymmetry is intentional, placing the workload on the prover (student) to preserve blockchain efficiency. The proof cryptographically binds to the specific public inputs, making it impossible to reuse or forge for a different grade or student.

The verifier is a smart contract deployed to a blockchain like Ethereum or a Layer 2 (e.g., Arbitrum, Optimism). Its sole function is to verify a zero-knowledge proof submitted by a student. We typically generate this contract using a ZK toolkit like Circom and snarkjs. After writing the circuit (grades.circom), we run snarkjs zkey export solidityverifier to produce a Solidity file containing the verification logic and the required cryptographic parameters.

The generated Verifier.sol contract contains a core function, often named verifyProof, which accepts the proof and public signals as arguments. The public signals are the non-sensitive outputs of the circuit that are revealed on-chain—in our case, this is the computed gradeHash. The contract uses elliptic curve pairing operations (pre-compiled contracts on Ethereum at addresses 0x06, 0x07, 0x08) to cryptographically check if the proof corresponds to the public signals without revealing the private inputs (the actual grades).

To integrate it, you deploy the Verifier contract. Your main application contract, say TranscriptRegistry, would then store a reference to it. When a student wants to prove a claim, their client-side code generates the proof and calls a function on TranscriptRegistry, which internally calls verifier.verifyProof(...). A return value of true means the proof is valid, and the contract can execute associated logic, like minting an SBT (Soulbound Token) or updating a registry entry. This on-chain verification is trustless and decentralized.

Key considerations for the verifier include gas optimization and security. The verification cost is fixed per circuit but can be high on Mainnet; using a ZK-optimized L2 like zkSync Era or Polygon zkEVM is advisable for production. Security depends entirely on the initial trusted setup (the Powers of Tau ceremony) and the correctness of the circuit logic. Any bug in the circuit compromises the entire system, making formal verification tools like ECne for Circom circuits highly recommended.

This guide walked through the core components: designing a Circom circuit to prove knowledge of a grade above a threshold without revealing it, generating a trusted setup with SnarkJS, and creating a proof verification system. The circuit logic, using the GreaterThan template, is the heart of the application, ensuring the cryptographic guarantee that a student's grade is valid. The zKey and verification_key.json files generated during the ceremony are essential for creating and verifying proofs in a production environment.

To move from this prototype to a deployable application, consider these next steps. First, integrate the proving and verification logic into a backend service, such as a Node.js API using the snarkjs JavaScript library. Second, develop a frontend interface for students to generate proofs and for verifiers (like employers) to check them. For on-chain verification, you can generate a Solidity verifier contract with snarkjs zkey export solidityverifier, which can be deployed to an EVM-compatible blockchain like Ethereum or a Layer 2 like Arbitrum, enabling trustless verification.

Explore advanced circuit design to increase utility. You could prove membership in a list of honor roll students, verify a grade is within a specific range, or aggregate multiple grades into a single proof for a transcript. For production, a robust trusted setup ceremony with multiple participants is critical to maintain security. Frameworks like zkkit can simplify Circom development, and platforms like zkSync Era or Polygon zkEVM offer tooling for deploying zk-powered applications. Always audit your circuits and keep dependencies like circomlib updated to mitigate risks.