Blockchain Privacy Technologies

The Challenge

Privacy is essential for ensuring the confidentiality, integrity, and security of data and transactions on the blockchain. Without adequate privacy protections, sensitive information such as financial transactions, personal data, and business contracts may be exposed to malicious actors, leading to privacy breaches, identity theft, or financial fraud. Privacy-enhancing technologies address these concerns by providing secure and confidential execution of transactions while still leveraging the transparency and immutability of the blockchain.

Fully Homomorphic Encryption (FHE) represents a breakthrough approach to blockchain privacy, enabling computations directly on encrypted data without ever decrypting it. This article explores FHE’s application in blockchain privacy protection, with Zama’s fhEVM protocol as a leading example, followed by a brief overview of alternative technologies.

Zama’s fhEVM Protocol

Zama’s fhEVM (Fully Homomorphic Encryption Virtual Machine) is a framework that integrates Fully Homomorphic Encryption (FHE) into Ethereum Virtual Machine (EVM)-compatible blockchains. It enables confidential smart contracts, where computations occur on encrypted data without decryption, preserving privacy while maintaining blockchain composability and verifiability.

Key guarantees include:

• End-to-end encryption of transaction inputs and contract states.
• No exposure of sensitive data to nodes, validators, or observers.
• Seamless integration with existing Solidity tools and EVM ecosystems.

fhEVM forms the core of Zama’s Confidential Blockchain Protocol, a layer that adds privacy to public blockchains without requiring chain modifications.

Technical Architecture

The fhEVM protocol is built on TFHE-rs, Zama’s open-source Rust implementation of Torus Fully Homomorphic Encryption, and supports the heavy encrypted data computation in off-chain coprocessors.

Symbolic Execution

The fhEVM protocol adopt the Coprocessor Model — Designed for Ethereum and Layer 2 networks:

• Symbolic Execution — The host chain handles logic but defers FHE operations, emitting events with encrypted handles instead of performing heavy computations.
• Off-Chain Computation — Specialized coprocessor nodes process FHE operations off-chain and return encrypted results via a Gateway contract.
• On-Chain Verification — Results are posted back to the host chain using a defense-in-depth approach combining threshold MPC and optimistic security (fraud proofs).
• Hardware Security — Coprocessor nodes utilize AWS Nitro Enclaves (Trusted Execution Environments) to ensure node operators cannot access key shares in memory.

Key Management System (KMS)

The network private key is split among multiple validators using Threshold MPC—no single entity holds the complete key. Decryption requires supermajority consensus (e.g., 2/3 of nodes), ensuring no single party can decrypt user data unilaterally. Private (user-only) decryption re-encrypts results under the user’s key.

Encrypted Types and Operations

Supported encrypted types include ebool, euint8, euint16, euint32, euint64, euint128, euint160, and euint256. Available operations on ciphertexts include:

• Arithmetic: Addition, subtraction, multiplication, division (experimental)
• Bitwise: AND, OR, XOR
• Comparison: Equal, greater than, less than
• Transfer: FHE.transfer for moving encrypted token balances

Developers write contracts in standard Solidity, importing the pre-compiled and deployed fhEVM library (formerly TFHE, now rebranded to FHE)—no cryptography expertise needed.

Recent Updates

The protocol has seen rapid iteration with key updates from v0.7 (July 2025) through v0.9 (October 2025):

• Library Rebranding — The Solidity library was renamed from TFHE to FHE to standardize the developer experience across the ecosystem.
• Input Re-randomization — To prevent tracking users via ciphertext metadata, all transaction inputs are now automatically re-randomized before execution.
• Gas Optimizations — Significant reductions in gas costs for FHE operations, making confidential contracts economically viable on public testnets.
• Access Control Logic — Introduction of granular permissions (FHE.allow and FHE.allowTransient) to strictly control who can view (decrypt) specific data fields, preventing unauthorized data leakage.

Project Timeline and Milestones

Development and Ecosystem Activity

• GitHub Repositories — Highly active (e.g., zama-ai/fhevm with thousands of stars/forks). Includes Solidity libraries, Go integrations for EVM chains, Hardhat templates, and coprocessor backends.
• Community and Developer Engagement — Strong momentum. Developers actively build and test confidential DeFi, voting, gaming, and identity apps. Recent X discussions highlight smooth developer experiences, low latency, and real-world demos (e.g., confidential transfers, blind auctions).
• Use Cases Demonstrated — Confidential lending/borrowing, private token swaps, blind auctions, on-chain gaming strategies, and encrypted governance voting.
• Strategic Partnerships — OpenZeppelin collaboration produced the Confidential Token Standard, a privacy-preserving equivalent of ERC-20, audited for institutional-grade security in dark pools and private assets. Google Cloud partnership accelerates FHE operations using specialized hardware support.

Developer Experience

Zama’s primary competitive advantage is ease of use. Unlike Zero-Knowledge (ZK) applications that require complex circuit generation and asynchronous proving, fhEVM enables developers to write synchronous code using standard tools:

• Tooling — Fully compatible with Hardhat and MetaMask. Developers can use standard Solidity tools. A Foundry template is scheduled for Q1 2025.
• Mental Model — Write code that looks like standard Solidity:

function add(euint32 a, euint32 b) public view returns (euint32) {
    return FHE.add(a, b); // Computed on encrypted data
}

The gas cost is comparatively much higher than the plaintext type. For example, a euint256 typically cost 32000 gas.

Future Outlook

fhEVM positions Zama as a leading “confidentiality layer” for blockchains, enabling privacy-preserving DeFi, AI, and identity without sacrificing composability. Mainnet and token launch in late 2025/early 2026 are major catalysts. Community programs (e.g., Creator Program Season 5) and testnet participation drive pre-mainnet adoption.

In summary, fhEVM is production-ready on testnet, with rapid progress toward a transformative mainnet deployment that could redefine blockchain privacy.

Other FHE-Based Solutions

Zama’s fhEVM has successfully positioned itself as the underlying engine for the confidential blockchain sector. The FHE ecosystem is growing rapidly in 2025, driven by hardware advances and demand for encrypted computation:

Alternative Privacy Technologies

While FHE offers powerful capabilities for programmable privacy, other cryptographic approaches also play important roles in blockchain privacy:

Comparing FHE vs. ZKP vs. MPC in Blockchain Privacy

Zero-Knowledge Proofs (ZKP)

ZKP proves statements (e.g., transaction validity) without revealing underlying data, ideal for selective disclosure and verifiability. ZKP dominates privacy and scaling, powering private transactions and confidential contracts through mature implementations. Notable projects include Aztec Network (Ethereum ZK-Rollup for private smart contracts), Aleo (Layer-1 with ZKP-native smart contracts via Leo language, partnering with Circle for private USDCx stablecoin), Mina Protocol (lightweight Layer-1 using recursive zk-SNARKs), and established privacy coins like Zcash (shielded transactions, 2025 market surge) and Monero (ring signatures + ZKP elements). ZKP projects lead in adoption due to maturity and scalability integration (e.g., zk-Rollups).

Multi-Party Computation (MPC)

MPC allows multiple parties to jointly compute functions over private inputs without exposing them, excelling in threshold cryptography and collaborative privacy. MPC is widely used for key management and threshold operations. Key implementations include Secret Network (Cosmos-based chain with secret contracts using TEEs + MPC elements for confidential DeFi/voting), ARPA Network (permissionless MPC network for verifiable RNG, secure wallets, and bridges), Partisia Blockchain (native MPC for general-purpose secure computation, combining with FHE), and threshold applications in wallets (e.g., TSS in multi-sig). MPC often augments other technologies, such as threshold decryption in FHE systems like Zama’s.

Trusted Execution Environments (TEE)

TEE provides hardware-based isolated execution environments for confidential computation. While not purely cryptographic, TEEs complement cryptographic approaches in privacy solutions. Secret Network notably combines TEEs with MPC elements to enable customizable privacy via secret contracts.

Current Landscape and Trends

Privacy is crypto’s hottest narrative in December 2025: Institutional adoption surges (e.g., tokenized assets need confidentiality), regulatory clarity emerges (e.g., U.S. acts supporting compliant privacy), and market performance reflects growing demand (Zcash +1172% YTD).

Hybrid approaches dominate the landscape, with protocols combining ZKP (verifiability), MPC (key management), and FHE (computation) to balance trade-offs. While regulatory pressure on “absolute” privacy causes some delistings, focus shifts to compliant tools that can be audited by authorities when necessary.

Looking forward, privacy technologies enable mainstream use cases including private DeFi, identity management, and AI on-chain. ZKP leads in scaling solutions, FHE pioneers programmable privacy, and MPC provides secure collaboration infrastructure. The space is converging on hybrid solutions for balanced privacy, composability, and compliance.