This increasing pressure to incorporate privacy into these new, decentralized systems has driven creativity in advanced cryptographic techniques. Fully Homomorphic Encryption (FHE) is on the rise as a possible game-changer. FHE allows arbitrary computations on encrypted data to be performed without ever decrypting the data. This needs to enable a trusted single server or blockchain node to do computation without having it learn anything about the data itself. FHE is very much at a stage which is currently slower than plaintext operations. Continued research is quickly making it more efficient and applicable – especially in the burgeoning field of threshold FHE.

FHE’s functionality goes well beyond AI model inference on user-provided encrypted data. This means that the network couldn’t under any realistic circumstances learn the inputs or the outputs, giving users strong guarantees of privacy. Now you can threshold the FHE private key among several parties. This decentralized version of the process employs Multi-Party Computation (MPC), or secret sharing, further increasing decentralization and security. This technology unlocks entirely new types of encrypted transactions and programmable smart contracts on blockchains.

FHE isn’t the only cryptographic approach to improving privacy. Zero-Knowledge Proofs (ZKPs), Multi-Party Computation (MPC), and Garbled Circuits (GC) come in as fundamental pieces of the puzzle. These technologies use cryptographic techniques to guarantee both privacy and correctness properties of computations.

Commencing with the garbled circuits first introduced by Andrew Yao in 1982, these solutions collectively stand as the first general mechanism for computing on pre-encrypted data. FHE, based on Yao’s original work, tackles this problem by allowing complex computations to be performed on encrypted data, representing a revolutionary step forward in privacy-preserving technology.

ZKPs let one party prove to another that they know the answer to a math problem without actually disclosing anything else. This is especially powerful in blockchain when you want to prove something has happened without revealing any private information.

Real-World Implementations and Projects

A number of other projects are building privacy into blockchain applications with cutting-edge cryptographic techniques. Partisia Blockchain, which uses secure multi-party computation (MPC) in conjunction with blockchain infrastructure, raised $50 million in 2021. This shows the increasing demand and resources flowing into privacy-enhanced blockchain technologies.

Secret Network was the first to implement general smart contracts, generalized private state on a blockchain. It succeeded in doing this innovative thing by using Trusted Execution Environments (TEEs) – notably Intel SGX. In late 2023, TEN protocol closed a $9 million round as an Ethereum-based Layer-2 protocol that uses TEEs. This funding further indicates a broader, accelerating implementation of TEEs for increased privacy. Aleo, a Layer-1 network using zero-knowledge proofs for private applications, has raised approximately $228 million, reflecting substantial investor confidence in ZKP-based privacy solutions.

To satisfy this requirement, Fhenix is building an EVM-compatible Layer-2 solution that natively integrates FHE to enable it for all of its computations. This ambitious project aims to bring the full potential of FHE to the Ethereum ecosystem, enabling a new level of privacy for decentralized applications.

Challenges and the Future of FHE

Despite its great promise, FHE has a number of challenges that must be addressed, most notably the computational overhead. As it turns out, FHE operations are painfully slow. They are typically between a thousand and a million times slower than their plaintext counterparts, depending on the underlying computation and scheme. Even with the advancement of these technologies, this performance bottleneck is a key barrier to universal adoption.

FHE is currently a vibrant research field, with improvements being developed continuously that are making it more efficient. The evolution of threshold FHE, specifically, has great potential for fortifying the security and decentralization of FHE-based systems.

As the Penumbra team aptly notes, the importance of privacy in blockchain cannot be overstated:

"as users interact onchain, leaks of information become leaks of value" - Penumbra team.

This underlines the urgent need for privacy-preserving technologies such as FHE to protect user data and mitigate against abuse and exploitation.

Furthermore, the Penumbra team cautions users about the inherent risks of exposing data on public blockchains:

"Don't put anything onchain that you wouldn’t want made public” - Penumbra team.

This highlights the need to leverage privacy-enhancing tools to protect sensitive information in permissionless, decentralized ecosystems.