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Zero-Knowledge Technology vs Fully Homomorphic Encryption (FHE): An Analysis of Two Encryption Solutions

Zero-Knowledge Technology vs Fully Homomorphic Encryption (FHE)

There’s more than one way to encrypt – and subsequently decrypt – data onchain. The most popular solution, zero-knowledge proofs (ZKPs) can be seen in action on a string of EVM layer2s including Starknet, Optimism, Polygon zkEVM, and zkSync, where it has proven to be as versatile as it is secure.

Billions of dollars in assets are now protected by crypto networks that are reliant on ZK proofs. But for all their ubiquity and relative maturity, ZKPs are by no means the only encryption solution for handling onchain data. Another contender has recently begun capturing attention and it has the potential to give ZKPs a run for their money. Enter fully homomorphic encryption (FHE), a technology that provides similar benefits to ZKPs – but which is designed very differently.

The Case for Zero-Knowledge Proofs

Zero-knowledge proofs are essentially a tool for privacy preservation, even if their application extends far beyond simply concealing the contents of sensitive data. At its core, the tech allows one party, known as the prover, to demonstrate to another party – the verifier –  that they possess certain data without disclosing the actual data itself.

On the surface, this sounds like a useful but niche capability with a narrow range of use cases, but in fact ZKPs play a pivotal role in securing financial data, supporting efficient blockchain transaction verification, and creating trustless systems that have no central point of control. From supply chain management to healthcare, zero-knowledge technology can be applied across various platforms and industries, supporting the interchange of information without data leakage.

The Problem With Proofs

ZKPs are one of the most versatile cryptographic tools that blockchain developers have at their disposal. They’re particularly valuable in the design of scalable networks that rely on a parent chain for security, since ZKPs allow transactions to be batched with only a lightweight proof required to demonstrate that the data referenced is accurate and hasn’t been tampered with. This supports the creation of layer2 and 3 networks that are much more efficient than their predecessors.

That said, it’s not all plain sailing with zero-knowledge proofs. ZKPs can require intensive computational processes, resulting in increased overheads, and testing resource-constrained environments such as blockchains to their limits. Because networks that utilize ZKPs are more complex than conventional blockchain networks, when things do go wrong, troubleshooting the issue can be challenging, as the likes of Polygon have discovered with their zkEVM.

Networks such as Starknet are also notoriously complex, making it much harder for developers to design and deploy a smart contract than on a non-ZK EVM such as Ethereum. Developers accept these trade-offs as part of the deal, reasoning that the upsides to ZKPs justify taking on the burden that working with them necessitates. Nevertheless, there are alternative encryption and privacy technologies that can achieve similar outcomes to ZKPs. One of them is FHE.

The Case for FHE

Fully Homomorphic Encryption (FHE) is a technology that enables computation to be performed on encrypted data without it having to be decrypted first. The results are delivered in encrypted form, which can then be decrypted to reveal the correct results.

Because computations can be performed directly on the encrypted data, FHE delivers significant improvements in terms of data privacy and security. This means that even the entity performing computations on the data cannot access its plaintext data, ensuring privacy is maintained at all times. This is a major breakthrough, particularly when it comes to blockchain design, providing a capability that ZK proofs cannot match.

Blockchain-based use cases for FHE include confidential DeFi, blind auctions, private asset management, and confidential AMMs. The tech can also be utilized by DAOs which can implement confidential voting, reducing bias, and to increase trust in digital voting systems.

Fully Homomorphic Encryption in Action

As a comparatively new technology, particularly in the context of blockchain, FHE is less widely adopted than ZKPs, and thus has less tooling and developer frameworks available at this time. Nevertheless, it’s presently being pioneered by a handful of projects, chief among them being Fhenix. Its fhEVM, currently on testnet, enables developers to create applications that boast full end-to-end encryption.

The concept of fully encrypted smart contracts has the potential to unlock a host of new blockchain use cases. From DeFi to GameFi and NFTs to SocialFi, FHE’s provision of native, base-layer confidentiality could be a genuine game-changer. Blockchains, more than any other data transmission system, are required to handle resources efficiently to reduce computational demand. If FHE can prove its ability to operate at scale, it has the potential to reduce costs and confirmation times while driving greater privacy through every level of the developer stack.

ZKPs vs FHE: The Verdict

If ZKPs and FHE were to be likened to prize fighters, the former is the veteran of the ring with more KOs to its name and a stack of impressive victories. The latter, meanwhile, is the leaner, hungrier up-and-coming fighter: unproven but representing a new breed of pugilist. For developers seeking to get started in the shortest time possible, the extensive zero-knowledge tooling and documentation available makes it easier to dive in.

But for devs willing to look beyond the tried-and-tested formula of ZKPs, the F in FHE might well stand for Future. Its ability to verify data without decryption is a massive improvement over existing solutions that could transform smart contracts into fast, confidential, and highly efficient computational machines. As adoption of FHE increases and the tech matures, it will be fascinating to see whether it can triumph over ZKPs and become the champion of blockchain data encryption.

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