MindChats EP07 Recap: FHEllow Warriors with Fhenix and Inco

Mind Network
5 min readMar 27, 2024

In the 7th episode of MindChats, streamed on March 21st, Mind Network is excited to have two special speakers joining us: Guy Itzhaki, Co-Founder of Fhenix, and Remi Gai, Founder of Inco! We’re calling this episode the ‘FHEllow Warriors’ because we truly feel like we’re in the trenches, building real, applicable use cases with FHE. With 17K tuned in participants in an hour, we’re glad to let more people get more familiar with FHE.

Time Stamp

Check out the recording of the AMA:https://twitter.com/i/spaces/1mnGepVLwenKX?s=20

03:10Introduction of Fhenix and Inco

04:55 The importance of an end-to-end encrypted web

09:26 — How does ZK work with FHE

18:45 Speaking about what Zama has done in space

23:13 What does TFHE bring to the table

30:21 The Vision of HTTPZ: Zero Trust and Data Confidentiality

33:08 Unlocking the Potential of FHE EVM

38:55 Expanding FHE Applications: Insights and Implementation

44:10 Exploring FHE Use Cases in Traditional Finance and Web2

45:50 Key Points on the Future of FHE in the Next 2–3 Years

53:45 Advancing UI/UX in New Blockchain Chains

Key Highlights of the Episode

The importance of an end-to-end encrypted web

  • Fully Homomorphic Encryption (FHE) is timely and mature, addressing data privacy concerns.
  • FHE offers a promising solution for blockchain’s data confidentiality issues, surpassing current efforts like zero-knowledge proofs.
  • FHE aligns with the privacy-focused vision of the Cipherpunk Manifesto in the digital age.
  • In the Web3 era, privacy protection is crucial for both enterprises and individual users, especially in blockchain transactions.
  • Maintaining privacy in financial transactions is vital, and FHE is expected to play a key role in ensuring confidentiality, similar to the role of banks in Web2.

How does ZK work with FHE?

  • ZK proofs are effective for scaling but fall short in ensuring data confidentiality, unlike FHE.
  • FHE specializes in running computations on encrypted data, offering robust confidentiality features.
  • Combining ZK’s proving capabilities with FHE’s confidentiality focus may provide comprehensive solutions for complex scenarios.
  • Without FHE, ZK’s reliance on plaintext for state transitions can lead to information leakage and composability issues.
  • While ZK has found success in blockchain, FHE’s broader trajectory and potential applicability across industries are evident through major tech companies’ investments in research and development.

Speaking about what Zama has done in space

  • Zama has simplified FHE adoption by providing accessible tools and libraries for developers, streamlining the development process.
  • They’ve addressed complexity and speed concerns associated with FHE, introducing tools like FHE EVM to abstract away technical intricacies.
  • Zama’s integration of FHE into blockchain applications has been transformative, significantly improving performance and accessibility.
  • Their contributions extend beyond blockchain, paving the way for broader adoption of FHE across various industries.
  • Zama’s efforts are crucial for the widespread adoption and integration of FHE technology, laying the groundwork for its future utilization across different domains.

What does TFHE bring to the table

  • TFHE offers programmable bootstrapping, enabling general computation and simplifying smart contract development.
  • It provides quantum resistance, crucial for future-proofing cryptographic systems against advances in quantum computing.
  • TFHE allows for infinite depth of computation without requiring prior knowledge, enhancing flexibility in smart contract scenarios.
  • Complex operations such as division and modular operations are supported, ensuring deterministic computation in smart contracts.
  • Challenges remain in protecting private keys, but TFHE’s capabilities make it a valuable tool for developers leveraging FHE in blockchain and smart contract applications.

The Vision of HTTPZ: Zero Trust and Data Confidentiality

  • 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.

Unlocking the Potential of FHE EVM

  • FHE EVM enhances privacy and security by enabling encrypted data storage and computation on-chain.
  • FHE EVM expands computational capabilities, allowing various operations on encrypted data, opening doors for new applications in DeFi, gaming, and enterprises.
  • Innovative applications like confidential DeFi, private gaming, and secure voting systems emerge with FHE EVM.
  • FHE EVM seamlessly integrates with existing EVM frameworks, simplifying development of privacy-preserving applications without complex decryption.
  • FHE EVM offers quantum resistance by operating entirely in ciphertext, safeguarding data against potential future quantum attacks.

Expanding FHE Applications: Insights and Implementation

  • FHE is crucial for ensuring confidentiality in financial applications, particularly in areas like lending securities, where privacy is paramount.
  • Immediate use cases for FHE include voting, auctions, bidding, and gaming, providing privacy and security in decentralized environments.
  • DeFi presents a significant opportunity for FHE integration, enabling novel applications and breakthroughs in the financial sector.
  • FHE infrastructure opens the door to innovative applications such as compliant confidential transactions and decentralized identity, with Layer 2 implementation offering scalability benefits.

Exploring FHE Use Cases in Traditional Finance and Web2

  • TradFi Exploration: Efforts for FHE in traditional finance, particularly for AML, are underway, but adoption and performance are still in early stages.
  • Anticipated Surge: Expect significant progress in FHE over the next 12–18 months, driven by rising awareness, new use cases, and hardware advancements.
  • Rapid Expansion: FHE adoption is expected to follow a hockey stick growth curve, driven by expanding use cases and improved hardware, leading to broader utilization and innovation in both traditional finance and Web2 sectors.

Key Points on the Future of FHE in the Next 2–3 Years

  • Hardware advancements, including ASICs, will enhance FHE performance in the next 12–18 months, broadening its application scope.
  • Tools like those from Zama simplify FHE for developers, although information leakage concerns require careful logic design.
  • 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.

Advancing UI/UX in New Blockchain Chains: Insights from Fhenix and Inco

  • Fhenix and Inco prioritize seamless onboarding for developers by leveraging EVM compatibility and offering familiar tools, reducing the learning curve.
  • Both projects emphasize open source examples and R&D to foster innovation and explore unique DeFi primitives and game mechanics on FHE-based chains.
  • Affordable gas fees and robust technical infrastructure are key focuses for Fhenix and Inco, aiming to optimize costs and address technical challenges to enhance the user experience and attract developers.

About Mind Network

Mind Network is the first FHE Restaking Layer for POS and AI Networks. Our framework operates as an FHE validation network, bringing secure computation and consensus to AI, DePIN, EigenLayer AVS, Bittensor Subnet, and many critical POS networks. Mind Network’s solution has found initial product-market-fit with projects such as IO.Net, MyShell, Bittensor, AIOZ, Nimble AI, ChainLink, Connext and more adopting its solution. It has achieved 650k+ 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