Recently, Binance Wallet launched an IDO project called Mind Network, which also received investment from Binance Labs. This project is not simple; it has found a new solution to the security problems of AI Agents using FHE technology, enabling safe collaboration between agents without exposing data. This is simply amazing!

In the past year, AI Agents have definitely been the hottest topic in the tech circle, with star projects like Virutual and ai16z emerging. NVidia's CEO Jensen Huang has publicly stated that AI Agents may be the next trillion-dollar potential track, similar to the robotics industry. OpenAI recently released a new toolkit specifically to simplify the application development of AI Agents, making the development of complex AI Agents much easier. It can be expected that by 2025, AI Agents will continue to shine, with more intelligent agents capable of making decisions and collaborating entering reality.

However, the stronger the AI Agent's capabilities, the greater the threat to user privacy and data security. To genuinely reassure users about AI Agents, the tech community has begun to focus on cryptographic solutions, with technologies like ZK, MPC, and FHE being highly anticipated. Previously, ZK technology caused the valuations of many projects to soar, but FHE technology, despite its huge potential, has not received enough attention in the market. In scenarios where AI Agents need to process massive amounts of sensitive data, FHE technology can definitely shine and open new horizons for privacy computing.

Mind Network was born in this context as the first project to apply FHE technology to AI infrastructure. It is incubated by Binance and backed by Binance Labs, making it hard not to succeed. The core team members of this project are experts in cryptography, blockchain, and artificial intelligence. With the rise of Web3 and artificial intelligence, data security and privacy issues have become increasingly prominent. Mind Network has created a secure and efficient network platform based on FHE technology, providing unique solutions for data sovereignty protection, fair consensus, private voting, secure cross-chain transmission, and trusted AI. Its goal is not just to make AI safer, but to build a trustworthy AI infrastructure that can coexist harmoniously with human society, allowing data to be computed while encrypted via the FHE network, fundamentally addressing the four major security challenges faced by Agents.

Four major security challenges, tackled one by one by Mind Network

Consensus security

In a decentralized environment, it is necessary to ensure that Agents can reach consensus. However, existing blockchains are mainly based on 'transactions' for accounting, which cannot meet the complex dynamic collaboration needs. Mind Network has created a trusted collaboration mechanism based on FHE technology, like putting a 'security lock' on the collaboration between Agents, allowing them to work together with confidence.

Data security

When AI Agents process sensitive data such as health and finance, the biggest fear is privacy leakage. Mind Network uses FHE technology to keep data encrypted throughout, like giving data an 'invisibility cloak', ensuring that no matter how computations are performed, the data will not be exposed, making it very secure.

Computational security

The previous 'black box model' posed significant risks due to its lack of transparency in the computation process, making it challenging to identify issues when they arose. Mind Network achieves a transparent and auditable computation process through FHE technology, like installing a 'surveillance camera' on the computation process, allowing each step to be clearly visible.

Communication security

Data security is also crucial when Agents communicate or collaborate. Mind Network implements end-to-end secure communication using zero-trust encryption protocols, ensuring that no matter where the data is sent, it remains encrypted, like putting data on a 'secure encrypted car', ensuring absolute security.

Mind Network has also shown strong development momentum, completing $2.5 million in seed round financing in 2023 and $10 million in Pre-A round financing in 2024, raising a total of $12.5 million, with well-known institutions like Animoca Brands participating in the investment. It was also selected for Binance Labs' fifth incubation program and Chainlink BUILD program, collaborating with organizations like Zama and Chainlink on technical cooperation, and releasing technical standards and products like HTTPZ and MindV Hubs to build a secure, encrypted, and sustainable ecosystem. Its mainnet officially launched in November 2024, and it completed TGE in 2025.

FHE technology: The 'guardian' of AI Agents

FHE technology, also known as fully homomorphic encryption technology, allows for various computations on encrypted data, with the computation results also remaining encrypted, eliminating the need for decryption throughout the process. This is simply a 'guardian' of privacy and security. Traditional encrypted computing requires decryption first, which poses a security risk. In scenarios of multi-party data collaboration, traditional encryption cannot guarantee privacy, whereas FHE technology allows for computations on encrypted data, with only authorized parties holding the keys being able to see the plaintext, which is remarkable!

The working mechanism of FHE technology involves three steps: encryption, computation, and decryption. During encryption, the sender uses a specific encryption algorithm and public key to turn plaintext into ciphertext; during computation, computing nodes can perform operations like addition and multiplication on the ciphertext, thanks to the homomorphic property, where the results of computations on ciphertext match the results of computations on plaintext after encryption; during decryption, only the receiver with the private key can restore the ciphertext to plaintext.

The advantages of FHE technology are significant, effectively preventing data leaks in scenarios such as medical data sharing and joint risk assessment among financial institutions. It is now widely applied in fields like finance, cloud computing, artificial intelligence, and the Internet of Things.

Compared to technologies like ZK and MPC, FHE has more obvious advantages in AI. ZK technology proves correctness without revealing information and is commonly used for identity and permission verification; MPC technology allows multiple parties to compute together while keeping data confidential, which is useful in cross-institution data analysis and financial auditing. FHE technology keeps AI data encrypted throughout the entire processing and model training process, so even if encrypted data is given to a third party for auxiliary computation, there is no concern about data leakage, greatly enhancing the security and privacy of AI data and allowing AI technology to be smoothly promoted in areas with high data security requirements.

Mind Network fully leverages the advantages of FHE technology, allowing Agents to complete collaborative tasks without exposing raw data, perfectly addressing the four core security needs: consensus security, data security, computational security, and communication security.

HTTPZ: The 'leader' of the next-generation internet protocol

HTTPZ is the next-generation internet protocol proposed by Mind Network and ZAMA, which implements end-to-end encryption of network data using FHE technology. The current internet environment is not very safe, as evidenced by the fact that after Telegram founder and CEO Pavel Durov was arrested in 2024, the platform modified its terms of service, submitting more user information to the U.S. government. This shows that even platforms like Telegram, known for encryption and high confidentiality, find it difficult to fully protect user information in the face of external pressure.

HTTPZ is different; it uses FHE technology to add a 'security lock' to data during transmission, storage, and computation. For example, in the medical data scenario, hospitals upload encrypted genetic data for analysis using HTTPZ, and the data remains encrypted throughout, meaning cloud providers cannot see the original data, ensuring privacy protection.

Compared to traditional HTTP and HTTPS, the advantages of HTTPZ are obvious. HTTP has no encryption mechanism, and data is transmitted in plaintext, making it easy to steal and tamper; HTTPS only encrypts during transmission, requiring decryption during data processing and storage, which still poses a risk of data exposure. HTTPZ can achieve encryption throughout the entire lifecycle of data during transmission, storage, and computation.

In terms of architecture, HTTP and HTTPS are based on traditional trust models, relying on the trustworthiness of servers and intermediaries. HTTPZ adopts a zero-trust architecture, making no assumptions about trust, and conducts strict verification and authorization for every request and data interaction, as if assigning a 'personal bodyguard' to each piece of data.

In terms of application support, HTTP and HTTPS struggle to meet the security needs of decentralized applications (dApps), AI-driven solutions, or quantum-resilient systems. HTTPZ can achieve secure, decentralized applications and quantum-safe encryption, effectively supporting emerging technologies like blockchain, AI, and quantum computing.

With the continuous development of network environments and AI technology, the zero-trust architecture and advanced encryption technology of HTTPZ will undoubtedly become key supporting protocols for emerging technologies like Web3, AI, blockchain, and quantum computing, providing a secure operating environment and promoting the internet towards a safer, privacy-focused, and efficient direction.

The multi-agent consensus issue of AI Agents: Mind Network has a clever solution

The competition between Single Agent and Multi Agent

Previously, single agents (Single Agent) had limited capabilities when dealing with complex tasks, making it easy to produce judgment biases. As the task volume increased, performance would decline, and they could only work independently without external assistance. Thus, multi-agents (Multi Agent) emerged. By collaborating through multiple Agents, complex tasks can be decomposed, leveraging their strengths to solve problems from different angles while achieving information sharing and collaborative work, significantly enhancing the ability to handle complex issues and making the system more flexible and adaptable. Projects like Questflow, MetaGPT, ai16z, and Swarms now utilize multi-agent technology.

The consensus problem of Multi Agent

However, the consensus issue among various Agents in a multi-agent system is crucial. Take autonomous driving as an example; the perception Agents, decision Agents, and control Agents must quickly reach a consensus. If an unexpected situation arises, such as the sudden appearance of a pedestrian, and the Agents cannot promptly agree on emergency braking, it could easily lead to an accident and threaten lives.

Data security and privacy issues cannot be ignored. In the healthcare industry, AI Agent systems will encounter a large amount of sensitive information from patients, such as medical histories and diagnostic results. If data security protections are inadequate, privacy data may leak, which not only harms patient rights but also hinders the promotion and application of AI Agents in the medical field.

Decision consistency and efficiency is also a big issue. In intelligent investment decision-making systems, different AI Agents may provide contradictory investment advice based on different algorithms and data, leaving investors unsure whom to trust.

Mind Network's solution based on FHE technology: Comprehensive protection

Mind Network has created a fully encrypted Web3 using FHE technology, providing innovative solutions to the challenges faced by Multi Agent or AI Agents, primarily in the following aspects.

Data sovereignty protection

The data processed by AI Agents includes a lot of personal data, sensor data, transaction data, and other high-value information, making both input and output data very sensitive. Mind Network uses FHE technology to encrypt the entire data processing workflow, allowing computations and processing to be completed without decryption, ensuring data security during transmission, storage, and usage, keeping data sovereignty firmly in the hands of users and avoiding the risk of data leaks.

Fair consensus mechanism

In the consensus mechanism between AI networks and AI Agents, traditional voting methods can easily be manipulated and cheated in networks with few nodes. Mind Network leverages FHE technology to allow Agents to perform consensus verification based on encrypted data, improving consensus efficiency and reliability, reducing cheating behavior, and ensuring the network can achieve a fair and just consensus.

Communication interaction security

In multi-party or cross-chain collaborations, it is difficult for different agents to trust each other. For example, if Binance's Agent and OKX's Agent were to collaborate, neither side would be willing to share data. FHE technology allows them to exchange and process information without exposing data, protecting privacy while ensuring security, laying a foundation of trust for their collaboration.

Support for trusted AI

Mind Network empowers AI Agents through FHE technology, ensuring that data remains encrypted during processing and model training, preventing data leakage, allowing AI Agents to efficiently process sensitive data in a secure environment, enhancing the security and privacy of AI data, and promoting the development of trusted AI.

Case study: A testament to Mind Network's strength

Collaboration with io.net

In April 2024, io.net and Mind Network announced a collaboration to innovate solutions for enhancing the security and efficiency of artificial intelligence. io.net introduced Mind Network's FHE solutions into its distributed computing platform, strengthening product security and better addressing the global GPU shortage.

In May 2024, Chainlink and Mind Network established a strategic alliance to build an FHE interface on top of Chainlink's Cross-Chain Interoperability Protocol (CCIP), applicable to various platforms such as Arbitrum, Ethereum Foundation, and Polygon, making cross-chain collaboration safer and more efficient.

Collaboration with Phala

In January 2025, Phala Network and Mind Network reached a strategic cooperation to combine TEE (Trusted Execution Environment) and FHE to create the next generation of secure zero-trust AI Agent solutions. Phala Network's TEE enables AI Agents to process data and models safely and at low cost, then load Mind Network's FHE SDK to encrypt inference results before sending them to Mind Network's FHE Hub for consensus verification. The integration of TEE, FHE, and blockchain achieves end-to-end security services and autonomous consensus capabilities, effectively addressing key challenges such as data security, quantum resistance, and decentralized consensus.

Swarms collaboration

In January 2025, Mind Network and Swarms announced deep cooperation. In Agent development, the two sides optimized Swarms using the Rust language, transforming it into Swarms - rust, enhancing programming security and concurrency efficiency, and stabilizing system performance. In Multi Agent collaboration, a secure consensus mechanism was built using fully homomorphic encryption technology to protect data privacy and intellectual property, reducing the risk of information leakage and achieving efficient collaboration. The results have been very significant, with the Multi Agent system's ability to handle complex tasks in financial analysis and medical diagnosis greatly improved, providing strong support for related work. Swarms is an important AI project developed by the talented young Kye Gomez, focusing on the research and innovation of Agent and swarm technology, achieving significant results in Multi Agent orchestration architecture, providing a foundation for Agent interactions.

Advantages and challenges: Opportunities and risks coexist

Advantages

Mind Network has many advantages. It is the first project to apply FHE technology to consensus management, setting a precedent in the industry. In traditional AI Agent consensus schemes, data transmission and computation require decryption, which easily leads to leakage, while Mind Network uses FHE to keep data encrypted throughout, effectively preventing leaks in scenarios of financial data processing. Traditional consensus algorithms lose efficiency as the number of nodes increases, while Mind Network combines FHE technology to quickly verify and achieve consensus on encrypted data in large-scale AI Agent collaborations, such as smart city traffic management. Traditional trust establishment relies on identity authentication and reputation mechanisms, which are easily attacked. Mind Network based on FHE allows nodes to verify only encrypted data without needing to know real identities and contents, solving the trust problem in cross-organizational supply chains. It has a diverse distributed network of nodes, which can scale on demand in the DePIN and AI Agent fields. Moreover, it has a well-developed incentive mechanism to encourage nodes to participate in consensus through native tokens, transaction fee sharing, honor rewards, etc., promoting ecological prosperity.

Challenges

However, Mind Network also faces some challenges. The computations with FHE technology are complex, and when handling large-scale data and complex tasks, the speed can be slow, and the volume of ciphertext is large, posing challenges for data transmission and storage. FHE technology is relatively new, and many enterprises and developers are not very familiar with it, with some enterprises being cautious. Currently, Mind Network's application scenarios are limited, and ecosystem development still needs to be further enhanced.

Epilogue: The future of Mind Network looks promising

On April 6, 2024, Mind Network launched airdrop queries, allowing active participants in the testnet, mainnet, invite activities, and community contributors to receive airdrops. Although FHE technology currently faces some technical bottlenecks, its future potential is enormous as technology continues to innovate. The ecosystem built by Mind Network is sure to drive the overall development of the AI Agent field. For developers and ecosystem participants, opportunities and challenges coexist, and it is hoped that more projects like Mind Network, which solidly focus on infrastructure construction, will emerge to build a better AI ecosystem together.

@Mind Network

#MindNetwork用全同态加密FHE重塑AI和数字未来

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