FHE Founders’ Views: Building the Master Plan

Mind Network
6 min readApr 5, 2024

The Holy Grail

The significance Fully Homomorphic Encryption (FHE), the ‘Holy Grail’ of cryptography cannot be overstated. This technology is the key to preserving privacy and meeting security demands in our current time. Its origins trace back to a concept first proposed by Rivest, Adleman, and Dertouzos in 1978. However, it wasn’t until 2009 that Craig Gentry, a Stanford University Ph.D. candidate, realized this vision through a groundbreaking dissertation that provided the first feasible scheme for FHE.

This technology allows complex computations to be performed on encrypted data without the need for decryption, thus offering a solution where data can remain secure and private even during analysis. We call this process ‘creating a shared private state’ for data.

The Master Plan

Four years since its founding, Zama, the leader in the FHE industry, has progressed FHE from theoretical math to practical code, enhancing accessibility for developers and broadening FHE’s application. Zama’s introduction of the fhEVM, a confidential smart contract solution, addresses privacy in blockchain transactions. It also highlights potential blockchain applications for FHE, including confidential tokens and decentralized identity, and the role of FHE in AI, foreseeing broader future impacts.

There are a handful of FHE builders in Web3 who believe in Zama’s goal and are pushing to make it a reality.

In this article, you will read the founders of Mind Network, Fhenix, and Inco state how they are helping to realize an end-to-end encrypted web specifically in Web3, and why these projects will fundamentally change the way users interact with the web. They have extensively discussed these topics during a previous MindChats episode on X, hosted by Mind Network.

Dawn of the Era of HTTPZ

Zama recently published its Master Plan article. This article announced its successful raise of $73M (undisclosed valuation) as well as outlined its ambition of creating an end-to-end encrypted web, called HTTPZ (Z for Zero Trust). The following paragraphs feature founders from the aforementioned articles explaining existing problems in Web3 and how they are using FHE to solve those problems.

From Guy Itzhaki of Fhenix.io

Zama’s vision for HTTPZ involves rebranding HTTP to HTTPZ, emphasizing zero trust and data confidentiality. The goal is to make operations over encrypted data seamless and transparent for users, requiring overcoming challenges like performance optimization. Success in this vision will establish encrypted data as the standard for all computations, necessitating collaboration among entities to promote FHE technology adoption.

From its inception, Ethereum has traded data integrity for confidentiality. On the one hand, we can trust Ethereum when it comes to following the rules of the system; for example, keeping an honest account of a financial ledger. On the other hand, we can’t trust them at all with sensitive information.

This dichotomy greatly limits the kind of use cases that Ethereum can handle. In fact, for Ethereum to actually evolve into “Web3”, we need to make sure that they can do what the web does today — but better. Consider for example a game of poker — while Ethereum can be trusted not to cheat, it cannot keep each player’s cards hidden from each other, and without that capability — the game cannot be played at all.”

From Remi Gai of Inco.org

Inco is an EVM-based Layer-1 blockchain, secured by Ethereum through EigenLayer, and abstracts away the complexity of FHE, enabling developers to build confidential DApps in 20 minutes by using the most adopted smart contract language, Solidity, and toolings from the Ethereum ecosystem, such as Metamask, Remix, and Hardhat.

In addition, similarly to how Celestia provides Data Availability (DA) to Ethereum and other blockchains, Inco, as a modular confidential computing network, extends confidentiality to Ethereum and other public L1s and L2s by providing confidential storage, computing, and access control. For instance, a trustless on-chain game can be developed on Arbitrum, with most of its core logic hosted there, while utilizing Inco exclusively for storing concealed information (e.g., cards, player stats, or resources) or performing private computations (e.g., payments, voting, or hidden attacks). Inco aims to bring confidentiality to the value layer of the internet, and push for the next frontier of mass adoption

From Christian Pusateri of MindNetwork.xyz

The recent boom in large language models (LLMs) has raised user expectations for more intelligent, blockchain-native decentralized applications. However, building crypto-native AI infrastructure presents significant challenges. AI requires vast computational power, which is often centralized. Making this power usable, affordable, and decentralized is a complex undertaking. But from the outset, decentralizing AI computational power has an advantage over centralized counterparts, allowing for broader GPU access as well as the ability for a larger swath of the economy to participate in financial rewards of AI networks.

Crypto AI has two specific challenges to solve in order to grab signicant share from Web2 AI. The first is the copy problem. If other miners can copy the predictions of other miners, there is a systemic incentive to cheat, and reduce one’s computational energy while still earning token rewards for contributing to the network. The clear result of this activity is a reduction in accuracy of predictions. Encrypting outputs with FHE disables miners from copying other miners and is key to AI network security.

Lastly, on the issue of the burgeoning restaking sector within Web3, we have the challenge to overcome of bootstrapping a decentralized validator network. EigenLayer has brought a key service to this market by allowing for shared security through ETH. Bringing an FHE AVS to the network further extends security by allowing for FHE-protected consensus. In this solution, FHE is used to encrypt consensus data, thereby disabling the ability for validators to copy other validators. This leads to less trust being required for new validators and so lowers the barrier to building a broader, more decentralized validator network.

Next Milestones for HTTPZ

Both Guy Itzhaki from Fhenix and Remi Gai from Inco predicted that with improved hardware and developer accessibility, FHE adoption is set to grow significantly, unlocking new use cases across various sectors such as finance, gaming, and enterprise.

“Hardware advancements, including ASICs, will enhance FHE performance in the next 12–18 months, broadening its application scope.” — Guy Itzhaki

“Tools like those from Zama simplify FHE for developers, although information leakage concerns require careful logic design.” — Remi Gai

“An end-to-end encrypted web is the only potential future of the web that solves its most critical problems. Zero trust infrastructure, enabled by FHE, brings a reasonable and mandatory level of privacy to transactions and data, helps bring DePIN to the masses, and helps decentralized AI eventually beat centralized AI. I suspect one of the ‘killer apps’ from Web3 over the next 18 months will emerge from the crypto AI/DePin vertical and will bring non trivial competition to Web2 AI incumbents.” — Christian Pusateri


Guy Itzhaki and Mak from Fhenix
Remi Gai from Inco
Christian Pusateri from Mind Network

About Mind Network

Mind Network is the first Fully Homomorphic Encryption (FHE) based general-purpose Restaking Rollup solution, bringing secure computation and consensus to the EigenLayer and Ethereum ecosystems. Mind Network’s solution enables verifiable decentralized compute over encrypted data, which solves significant challenges for use cases such as decentralized GPU networks processing AI workloads as well as Decentralized Physical Infrastructure Networks that manage sensitive user data, among others. Mind Network’s solution has found initial product-market-fit with projects such as IO.Net, AIOZ, Nimble AI, ChainLink, etc. adopting its solution, and has 600k+ active users and 3.2M+ transactions processed on its testnet.

Mind Network is backed by Binance Labs, Hashkey, Big Brain, Chainlink, Comma3, SevenX, and received an Ethereum grant to conduct research on practical implementations for FHE technology on Ethereum.

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An FHE (Fully Homomorphic Encryption) Restaking Layer for POS and AI Networks. https://linktr.ee/mindnetwork_xyz