Data privacy and security are essential in the fast growing Web3 world, where blockchain technology is king. Enter Fully Homomorphic Encryption (FHE). This is where Fully Homomorphic Encryption (FHE) steps in, a potentially breakthrough solution that enables users to process computations on encrypted data without revealing its privacy.
To help you out, our comprehensive guide will teach you the nuts and bolts of how to adopt FHE on blockchain — shedding light into what might seem like a convoluted world with fragmented use cases.
Step 1: Grasping the Fundamentals of FHE and Blockchain
Understanding FHE
Fully Homomorphic Encryption (FHE) is an advanced encryption method that allows for operations over encrypted data ie., ciphertext — without having to decrypt first. Think of it as a box that holds some secret information, and with FHE you can open and close the box without accessing what is inside.
Deciphering Blockchain Technology
Blockchain: a decentralized, immutable ledger or schedule of transactions that are shared across a network of computers. While its transparency and security features make it suitable for a number of use cases, data privacy is still an ongoing issue that needs to be addressed.
The Synergy of FHE and Blockchain
The FHE based application works well with blockchain. FHE protects private data on the blockchain, and using the longevity of the blockchain, guarantees that any computations conducted on encrypted work out correctly.
Step 2: Selecting the Right FHE Scheme for your Compiler
Exploring Different FHE Schemes
There are many FHE schemes, each of which has its own trade offs. Popular choices include:
BFV (Brakerski-Fan-Vercauteren): Best described as efficient and well-suited for large integer arithmetic.
CKKS (Cheon-Kim-Kim-Song): Suitable for real numbers and approximate computations.
TFHE (Fast Fully Homomorphic Encryption over the Torus): Tuned for specific operations like Boolean circuits.
The optimal FHE scheme depends on your specific use case. Key considerations include:
Computational Efficiency: Certain schemes are faster than the other.
TypeSintaxData TypeI Choose a pattern that allows the types of data you use: integers, real numbers, etc
Security Level: Security is the minimum level of protection your application needs
Step 3: Setting Up Your Blockchain Environment
Choosing a Blockchain Platform
Select a blockchain platform that supports smart contracts, the self-executing code that will interact with your FHE implementation. Popular options include:
Ethereum: A widely-used platform with a large developer community.
Hyperledger Fabric: A permissioned blockchain suitable for enterprise applications.
Polkadot: A multi-chain network enabling interoperability between blockchains.
Installing Necessary Tools
Install the following tools:
Blockchain Node: Set up a node for your chosen blockchain platform.
Smart Contract Development Environment: Install tools like Remix IDE or hardhat or Foundry to develop and deploy smart contracts.
FHE Library: Integrate an FHE library (e.g., ZAMA, HElib, PALISADE) into your development environment.
Step 4: Crafting Your FHE Smart Contract
This chapter dives into the heart of implementing Fully Homomorphic Encryption (FHE) on the blockchain. We'll explore the crucial steps involved in crafting a secure and functional FHE smart contract, enabling you to perform computations on encrypted data without compromising confidentiality.
Key Generation and Encryption
Think of this as creating a secure lockbox for your sensitive data.
Generating FHE Keys:
FHE relies on a pair of keys:
* **Public Key:** Used for encrypting data. Think of it like the key to lock the box. Anyone can use this key to encrypt data and send it to you.
* **Secret Key:** Used for decrypting data. This is like your personal key to unlock the box. Only you possess this key, ensuring only you can access the decrypted data.
Encrypting Sensitive Data:
Before storing data on the blockchain, you use the public key to encrypt it. This transforms the data into an unreadable format, protecting it from unauthorized access.
Storing Encrypted Data on the Blockchain
Now that your data is securely encrypted, it's time to store it on the blockchain.
Smart Contract Storage:
Smart contracts have their own storage space on the blockchain. You can store the encrypted data directly within the contract's storage. This is suitable for smaller datasets.
Decentralized Storage Solutions (IPFS):
For larger datasets, consider using decentralized storage solutions like IPFS (InterPlanetary File System). IPFS stores data across a network of computers, making it more resilient and efficient for handling large files. You can store the encrypted data on IPFS and store the link to the data within your smart contract.
Implementing FHE Operations in Smart Contracts
This is where the magic of FHE happens.
Smart Contract Functions:
You write functions within your smart contract to perform computations directly on the encrypted data.
FHE Operations:
These functions can perform various operations, such as:
* **Addition:** Adding two encrypted numbers together.
* **Multiplication:** Multiplying two encrypted numbers.
* **Comparison:** Comparing two encrypted values (e.g., is one greater than the other?).
* **More Complex Computations:** Depending on the FHE scheme used, you can perform more complex operations like statistical analysis or machine learning algorithms.
Example:
Imagine you want to calculate the average salary of employees without revealing individual salaries. You can encrypt each salary using FHE, store the encrypted data on the blockchain, and then use a smart contract function to calculate the average directly on the encrypted data.
Decrypting and Retrieving Results
Once the computations are complete, the results are still in encrypted form.
Authorized Decryption:
Only the party with the secret key can decrypt the results, revealing the outcome of the computations. This ensures that sensitive data remains confidential throughout the process.
Create a Simple ERC-20 Token using ZAMA’s FHE Library
Installation
To get started with fhEVM Solidity Library, you need to install it as a dependency in your JavaScript project. You can do this using npm (Node Package Manager) or Yarn. Open your terminal and navigate to your project's directory, then run one of the following commands:
# Using npm
npm install fhevm
# Using Yarn
yarn add fhevm
# Using pnpm
pnpm add fhevm
Writing SC
Import Required Libraries
We're using two main libraries:
OpenZeppelin's ERC20 contract
FHE library for Fully Homomorphic Encryption operations
import "fhevm/lib/TFHE.sol";
import "@openzeppelin/contracts/token/ERC20/ERC20.sol";
The contract ZamaFHEToken is defined as ERC20
contract ZamaFHEToken is
ERC20 {
Declare State Variables
We declare encrypted mappings for balances and allowances using euint32, which is Zama's encrypted unsigned integer type.
// Mapping from address to encrypted balance mapping(address => euint32) private _balances;
// Mapping from owner to spender to encrypted allowance mapping(address => mapping(address => euint32)) private _allowances;
Implement Minting Function
The mint and _mint functions allow creating new tokens and assigning them to a specified address. We use TFHE operations to update the encrypted balance.
function _mint(address account, uint256 amount) internal virtual override {
require(account != address(0), "ERC20: mint to the zero address");
_totalSupply += amount;
_balances[account] = TFHE.add(_balances[account], TFHE.asEuint32(uint32(amount))); emit Transfer(address(0), account, amount);
}
In short, the complete contract with the implementation of ERC 20 using ZAMA library looks like this:
// SPDX-License-Identifier: MIT
pragma solidity ^0.8.0;
import "fhevm/lib/TFHE.sol";
import "@openzeppelin/contracts/token/ERC20/ERC20.sol";
contract ZamaFHEToken is ERC20 {
// Mapping from address to encrypted balance
mapping(address => euint32) private _balances;
// Mapping from owner to spender to encrypted allowance
mapping(address => mapping(address => euint32)) private _allowances;
// Total supply of tokens
uint256 private _totalSupply;
constructor(string memory name, string memory symbol, uint256 initialSupply) ERC20(name, symbol) {
_mint(msg.sender, initialSupply);
}
function mint(address to, uint256 amount) public {
_mint(to, amount);
}
function _mint(address account, uint256 amount) internal virtual override {
require(account != address(0), "ERC20: mint to the zero address");
_totalSupply += amount;
_balances[account] = TFHE.add(_balances[account], TFHE.asEuint32(uint32(amount)));
emit Transfer(address(0), account, amount);
}
function _transfer(address from, address to, uint256 amount) internal virtual override {
require(from != address(0), "ERC20: transfer from the zero address");
require(to != address(0), "ERC20: transfer to the zero address");
euint32 encryptedAmount = TFHE.asEuint32(uint32(amount));
euint32 fromBalance = _balances[from];
_balances[from] = TFHE.sub(fromBalance, encryptedAmount);
_balances[to] = TFHE.add(_balances[to], encryptedAmount);
emit Transfer(from, to, amount);
}
function _approve(address owner, address spender, uint256 amount) internal virtual override {
require(owner != address(0), "ERC20: approve from the zero address");
require(spender != address(0), "ERC20: approve to the zero address");
_allowances[owner][spender] = TFHE.asEuint32(uint32(amount));
emit Approval(owner, spender, amount);
}
function allowance(address owner, address spender) public view virtual override returns (uint256) {
return TFHE.decrypt(_allowances[owner][spender]);
}
function balanceOf(address account) public view virtual override returns (uint256) {
return TFHE.decrypt(_balances[account]);
}
function totalSupply() public view virtual override returns (uint256) {
return _totalSupply;
}
}
Step 5: Optimizing Your FHE Implementation
Performance Optimization
FHE computations can be computationally intensive. Optimize your implementation by:
Choosing efficient FHE schemes.
Leveraging hardware acceleration (e.g., GPUs).
Minimizing the number of FHE operations.
Security Considerations
Ensure the security of your FHE implementation by:
Protecting the secret key.
Using secure key management practices.
Regularly updating your FHE library to address vulnerabilities.
Real-World Applications of FHE on the Blockchain
Privacy-Preserving Data Sharing
Share sensitive data (e.g., medical records, financial information) securely on the blockchain while enabling authorized parties to perform computations without compromising privacy.
Secure Voting
Implement secure and transparent voting systems where votes are encrypted and tallied using FHE, ensuring the integrity of the election while protecting voter privacy.
Supply Chain Management
Track the movement of goods through the supply chain while keeping sensitive business information confidential using FHE on the blockchain.
Conclusion
Implementing Fully Homomorphic Encryption on the blockchain unlocks a new era of data privacy and security in the Web3 ecosystem. By following this step-by-step guide and optimizing your content for Web3-specific keywords, voice search, and tracking its performance with analytics tools, you can harness the power of FHE to build innovative and secure decentralized applications.
