Author: Xinwei, MT Capital
MT Capital has always been dedicated to investing in innovative companies with disruptive technological potential. We believe that the combination of Fully Homomorphic Encryption (FHE) and AI in a decentralized physical infrastructure network (DePIN) is a crucial track for the future. FHE technology allows for calculations to be performed while maintaining data encryption, ensuring privacy and security throughout the data processing process. The integration of AI with DePIN not only efficiently utilizes external computing resources but also enables complex data analysis and machine learning tasks without worrying about data leaks. Privasea’s leading position in this field and technological advantage align perfectly with MT Capital’s investment strategy. We believe that by supporting Privasea, we will drive the development of the FHE AI DePIN track, promoting the security and sustainable development of the global digital economy.
1. What is Fully Homomorphic Encryption (FHE)?
Fully Homomorphic Encryption (FHE) is an encryption technology that allows arithmetic or logical operations to be directly performed on ciphertext while maintaining the encryption of data. This means that complex operations can be carried out on encrypted data without the need to decrypt it into plaintext, revolutionizing data privacy and security.
In traditional data processing scenarios, data must be decrypted in order to perform calculations, exposing sensitive information and increasing the risk of data theft or misuse. The application of FHE technology completely changes this. With FHE, encrypted data can be input directly into the calculation process, and the calculation results remain encrypted until they need to be viewed. This feature is crucial for industries that deal with sensitive data, such as finance, healthcare, and government sectors. FHE also enables data processing outsourcing without sacrificing data confidentiality. Companies can send encrypted data to third-party service providers for complex data analysis or machine learning tasks without worrying about data leaks because the service provider cannot see the original data throughout the process.
2. Privasea: The First AI+DePIN Network to Use FHE
Privasea utilizes FHE technology to provide data privacy and security, utilizing AI and a distributed network architecture to allow for complex data processing and analysis while keeping data fully encrypted. This means that users can engage in machine learning and other advanced computing tasks without exposing the original data, a feat impossible in traditional cloud computing, disrupting privacy computation. Privasea’s platform incorporates advanced FHE schemes such as TFHE and CKKS, ensuring high data privacy protection while maintaining computational accuracy and efficiency. The TFHE scheme supports rapid bit operations within a single instruction cycle, while the CKKS scheme optimizes the processing of floating-point numbers, enabling Privasea to effectively support various complex research and business applications like financial analysis, healthcare data processing, and machine learning tasks. Additionally, Privasea has implemented a highly scalable distributed computing network, Privanetix, consisting of multiple computing nodes capable of executing FHE operations, providing the necessary computing resources. This distributed architecture not only enhances the platform’s processing capabilities but also increases system redundancy and fault tolerance, ensuring high availability and reliability of services. This integration of AI with distributed networks allows Privasea to handle advanced AI tasks like deep learning, pattern recognition, and machine learning, tasks that typically require substantial computing power and high data protection. For example, users in the healthcare industry can securely analyze sensitive patient data, predict diseases, and optimize treatment plans using Privasea without violating data protection regulations. Privasea also offers a unique smart contract suite that allows users to manage and automate data processing processes while maintaining data encryption, including data verification, result output, and the allocation and reward of computing tasks. These smart contracts are executed on a distributed ledger, ensuring process transparency and traceability while automating incentive distribution based on the computing resources provided by nodes. This blockchain-based incentive mechanism further enhances network participation and computing efficiency as each node is motivated to provide reliable services. This makes Privasea not just a data encryption and processing platform but also a complete encrypted data ecosystem. Through Privasea’s API, developers can easily access this complex system and utilize its powerful features to develop and deploy their AI applications. These applications can distribute computing loads using a distributed network while ensuring data integrity and security, which is especially important for blockchain applications that handle large amounts of sensitive data.
3. Collaboration with Solana Demonstrates Mass Adoption Potential
Privasea leverages FHE technology to introduce the ImHuman application, showcasing not only the application of FHE in anti-bot attacks but also its mass adoption potential in the encryption field. Bot attacks pose a significant threat to decentralized networks, particularly in airdrop domains, where attackers manipulate the network or gain unfair advantages by creating numerous fake identities. The ImHuman application effectively counters such attacks in a secure and privacy-protecting manner. Privasea plans to deploy its technology on the Solana network, becoming the first Proof of Human application on Solana. Solana’s high efficiency and low latency make it an ideal blockchain platform to support Privasea’s FHE technology and AI computing needs. This deployment will not only enhance the security of the Solana ecosystem but also showcase the potential of FHE in Web3 applications. By running on Solana, Privasea’s ImHuman application can more widely verify user identities, ensuring network security and reliability while protecting user privacy. The operation of the ImHuman application involves using user biometric data to create a unique digital identity. Users first scan their facial vectors through the application’s front camera, a process completed entirely on the user’s device to prevent sensitive data leakage. Subsequently, this data is encrypted and transformed into an NFT representing the user’s encrypted biometric vector. This utilizes the feature of FHE, allowing for complex calculations without decrypting the data, ensuring data security and privacy. During user authentication, the ImHuman application scans the user’s facial features again and compares the newly collected data with the encrypted data stored on the blockchain. This process also utilizes FHE technology to ensure that data is not decrypted during verification, effectively avoiding the risk of data leakage. Furthermore, since each user’s NFT is generated based on their unique biometric features, it is difficult to replicate or forge, significantly increasing the difficulty of executing bot attacks. Through the ImHuman application, Privasea not only provides a powerful tool to enhance the security of decentralized networks but also demonstrates the feasibility of FHE technology in real-world applications. This authentication method based on biometric features and FHE provides a secure and privacy-protecting solution for decentralized networks, making Privasea’s ImHuman the first FHE application with mass adoption potential. Additionally, by distributing airdrop rewards to participants, ImHuman can incentivize user participation and continuous use, further driving its widespread application. This innovative solution offers a new strategy for defending against bot attacks.
4. Comparison between Privasea and Existing Proof of Human Solutions
In current Proof of Human solutions, projects like Worldcoin and Human Protocol face compliance risks and privacy issues. For example, a recent investigation by the Privacy Commissioner for Personal Data in Hong Kong found that Worldcoin’s operations in Hong Kong violated the Personal Data (Privacy) Ordinance. The investigation revealed that individuals participating in the Worldcoin project needed to provide facial images and iris scans to verify their human identity, posing serious risks to personal data privacy. As a result, the Privacy Commissioner in Hong Kong requested Worldcoin to cease collecting iris and facial images from Hong Kong residents. Human Protocol verifies user identities by collecting task response data, interaction data, device and browser information, geolocation, and user behavior data. While this data is anonymized before use and transmitted encrypted, it still involves significant collection of personal data, posing privacy and compliance risks. In contrast, Privasea places a stronger emphasis on user privacy protection in its design. Privasea’s DApp “ImHuman” uses FHE technology for user authentication, eliminating the need to collect sensitive information such as facial or iris images from users. The verification process occurs entirely on the user’s mobile device, facial vector data is encrypted, and not transmitted to any servers. This approach ensures secure verification while maximizing user privacy and avoiding the risk of data leakage.
Privasea not only leads in privacy protection but also provides a robust data privacy and security solution through the integration of FHE, DePIN, and ZK technologies. These technologies enable Privasea to conduct complex data processing and analysis without exposing user data, further lowering compliance risks. This unparalleled privacy protection and data security capability set Privasea apart in the competitive landscape, making it a leading Proof of Human solution in the industry.
5. Accseal and Privasea Partner to Deepen Privacy Computation
With its outstanding FHE, DePIN, and ZK technological capabilities, Privasea has set a new standard in the field of privacy computation. As a pioneer in the AI DePIN field, Privasea establishes a new benchmark for data privacy and security with its innovative FHE Machine Learning (FHEML) solution, seamlessly integrating distributed computing networks with advanced security measures to enhance data privacy and security. Privasea’s introduction of the DApp “ImHuman” utilizes FHE technology to securely execute “Proof of Humanity” (PoH) by directly encrypting facial vector data on users’ mobile devices, without transmitting it through servers, greatly enhancing privacy protection and the security of user data.
In this context, Privasea has entered into a strategic partnership with Accseal to further strengthen its technological advantage. As a leading enterprise in hardware-accelerated privacy computing, Accseal will provide hardware acceleration support to Privasea, enhancing the efficiency and performance of its FHE operations. Both parties will explore the possibilities of integrating ZK and FHE technologies to improve the efficiency of privacy computation and expand its application scope. Through this collaboration, Privasea not only demonstrates its leadership in the FHE field but also elevates its DePIN project to new heights. Accseal will develop new hardware acceleration products to provide computing acceleration support to upper-layer applications like Privasea, further driving the development of privacy computing technology. The collaboration between the two parties heralds new breakthroughs in the field of privacy computing, especially in the widespread and in-depth application of the DePIN project.
