Today we continue to look at a new project 'Homomorphic Encryption' - Mind Network (FHE), which launched on April 10. Although it is a VC project, it has not fallen below its initial value and has reached new highs. Currently, the price is $0.1, with an FDV of $100 million. To conclude, this project is definitely in demand and is a crucial infrastructure for the future of AI and encryption. This article will explain the fundamentals of the project and the most suitable price for bottom-fishing.
1. Introduction
Mind Network is a pioneering FHE (Fully Homomorphic Encryption) infrastructure aimed at achieving quantum-resistant, fully encrypted data and AI computation for an all-encrypted web. Mind Network is innovating FHE to empower various industries to realize universal end-to-end encryption, covering areas such as artificial intelligence, modular chains, gaming, asset management, and DePIN. Mind Network provides unique solutions to ensure data security, consensus security, and transaction security in critical areas. Mind Network is collaborating with Zama and others to build an all-encrypted infrastructure, dedicated to realizing the vision of the next-generation internet, HTTPZ.
2. Background Analysis - Analysis of HTTPS Protocol Limitations
Although HTTPS has become the standard protocol for secure internet transmission, it still has the following core flaws:
Limited Encryption Scope: HTTPS only encrypts data during transmission (TLS layer), but data remains in plaintext when processed on the server side, posing risks of server intrusion or internal leakage.
Reliance on Centralized Trust Systems: Relies on CA (Certificate Authority) systems to verify identities. If the CA is compromised or issues incorrect certificates, it may lead to man-in-the-middle attacks.
Quantum Computing Threats: Currently widely used asymmetric encryption algorithms, such as RSA and ECC, may be broken by quantum computers, threatening long-term security.
Insufficient Privacy Protection: Cannot support data computation in encrypted states; data must be decrypted for processing, leading to privacy leakage risks in sensitive scenarios such as healthcare and finance.
3. Characteristics of FHE
Homomorphic encryption is an encryption scheme that allows computations to be performed directly on ciphertext without first decrypting it. The computation result remains ciphertext, and when decrypted, it is identical to the result obtained by performing the same operation on plaintext. This means that even if the processing party does not possess the decryption key, it can perform various operations on the encrypted data, thus protecting the privacy and security of data throughout the 'storage-transmission-computation' process.
FHE has the following unique key features:
Computations on Encrypted Data
Fully Homomorphic Encryption (FHE) allows computations to be performed directly on encrypted data without first decrypting it. In blockchain, FHE can support confidential transactions, hiding transaction amounts while still ensuring transaction validity (as the essence of homomorphic encryption suggests); in artificial intelligence, FHE enables privacy-preserving machine learning, allowing AI to analyze encrypted data without accessing the original data, making it very suitable for secure federated learning scenarios.
End-to-End Privacy
Data owners do not need to share private keys; only data owners can decrypt the final results, and neither the computation party nor intermediary nodes can access the original data. In blockchain, FHE can prevent transaction details from being leaked and protect sensitive business logic; in AI, FHE supports secure 'AI as a Service' by ensuring that user data remains confidential for privacy-preserving AI inference.
Zero Trust Computing
FHE computations can be securely outsourced without trusting the computing entity. In blockchain, FHE supports secure off-chain computation, making Layer 2 networks (L2) more private and efficient; in AI scenarios, FHE supports trustless deployment of AI models, facilitating secure AI collaboration between untrusted parties.
Quantum Safety
FHE utilizes the complexity of lattice-based NP-hard problems (such as the Shortest Vector Problem, SVP) to provide strong quantum attack resilience. Since 2016, lattice cryptography methods have been widely evaluated and were formally accepted by the National Institute of Standards and Technology (NIST) as one of the mainstream post-quantum cryptography standards in 2024.
4. Potential Challenges and Future Prospects of HTTPZ
Challenges
Performance Bottleneck: The complexity of FHE computation is high, and even with hardware acceleration (such as the FHE-CGRA framework), it may still limit the practicality in high-concurrency scenarios. Early FHE bootstrapping operations were extremely expensive, with Gentry's initial scheme being up to 10⁶–10¹² times slower; recent optimizations have reduced costs to the millions.
Standardization and Compatibility: Existing internet protocol stacks need to be restructured, and compatibility with HTTP/3 and Web3 infrastructure remains to be validated.
User Acceptance: The 'continuous verification' mechanism of the zero-trust model may increase operational complexity for end users.
Prospects
Deep Integration with AI: Protecting AI data sovereignty through FHE (such as the World AI Health Hub collaboration between Mind Network and ZAMA) promotes privacy computing as the infrastructure for AI development.
Quantum-Safe Internet: HTTPZ is expected to become the security protocol standard in the post-quantum era, and its 'CitizenZ' concept may redefine digital identity and data ownership.
Policy Promotion: As various countries strengthen data privacy legislation (such as GDPR and China's Data Security Law), the zero-trust architecture of HTTPZ may become a compliance necessity.
5. Core Products of Mind Network
1. AgenticWorld
AgenticWorld is a decentralized AI ecosystem designed for secure and autonomous AI agents. It is based on Fully Homomorphic Encryption (FHE) technology, supports encrypted computation, and ensures data privacy in Multi-Agent Systems (MAS). AgenticWorld integrates a security layer and interoperability hub, supporting trustless AI collaboration across Web3 and DeFi, decentralized identity, and confidential machine learning.
2. MindChain
MindChain is the first public chain built on Fully Homomorphic Encryption (FHE), designed specifically for AI agents. It supports encrypted computation, secure collaboration, and an autonomous AI ecosystem, while integrating Zero-Knowledge Proofs (ZKP), Trusted Execution Environments (TEE), Multi-Party Computation (MPC), decentralized identity, and GPU computing frameworks to achieve scalability.
3. FHEBridge
MindBridge, developed by Chainlink, is a secure cross-chain protocol that utilizes FHE and the Stealth Address Protocol (SAP) for private, quantum-resistant transactions, ensuring seamless interoperability across blockchain ecosystems.
6. Ecosystem Cooperation and Implementation
DeepSeek: Integrates the FHE engine to provide computing power for privacy-preserving AI systems.
SingularityNET: Jointly launched ASI Hub to achieve trusted communication and random number services between encrypted AI agents.
Chainlink BUILD, Binance Labs, Consensys Scale: provide incubation and funding support to enhance technological research and community building.
DePIN Partners: Roam, PingPong, AIOZ, MyShell, etc., utilize FHE to protect the data security of IoT and storage networks.
7. Funding Situation
Since the mainnet launch on July 10, 2024, it has received $12.5 million in investments from institutions such as Binance Labs, Animoca Brands, and Hashkey.
8. Token Economics
The total token supply is 1 billion, with an initial circulation of 24.9%. The opening price was $0.05, currently $0.097. Token distribution: airdrop 11.7%, community 30%, public sale 5%, investors 20%, team 17%, advisors 1.3%, liquidity providers 5%, treasury 10%.
Token release is as follows: starting in May, the community will prioritize unlocking; after one year, investors, teams, and advisors will gradually unlock, pay attention to the time nodes.
Based on previous investment amounts, investors account for 20%, with an investor valuation of $62.5 million. Therefore, when it launched at $0.05, the overall FDV was only $50 million, resulting in losses for investors. However, investors are from BN, and it's unlikely they would let themselves incur losses, so prices below $0.62 can be considered for bottom-fishing.
In summary, this project is indeed in demand and is an essential infrastructure for transmission encryption in the future. Given the large-scale application of AI, key data (such as your address, information, and work details) may inevitably be leaked to AI during interaction. FHE can address this issue, and Deekseek has indeed collaborated with it, indicating a demand in this area. However, the concept of HttpZ is still very distant and requires significant costs. In the coming years, it may be challenging to shake the current HTTPS. Current commercial practices also show that overly advanced business actions may not be favorable, such as companies that focused on AI before ChatGPT's explosion, which all failed. The timing is wrong, making it difficult for commercial companies to survive until the day of MaaS adoption. We can only hope that Mind Network can hold on!
