Author: Xinwei, MT Capital
MT Capital is dedicated to investing in innovative companies with disruptive technological potential. We believe that the combination of Fully Homomorphic Encryption (FHE) and Artificial Intelligence (AI) in a decentralized physical infrastructure network (DePIN) is the future’s crucial track. FHE technology allows for computation 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 the worry of data leakage. Privasea’s leading position in this field and technological advantages 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 a cryptographic technique that allows arithmetic or logical operations to be performed directly on ciphertext while maintaining data encryption. This means that encrypted data can undergo complex processing without needing to decrypt it, revolutionizing data privacy and security.
In traditional data processing scenarios, data must be decrypted before computation, exposing sensitive information and increasing the risk of data theft or misuse. However, the application of FHE completely changes this. With FHE, encrypted data can be input directly into the computation process, and the computation results remain encrypted until decryption is required to view the results. 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 compromising data confidentiality. Companies can send encrypted data to third-party service providers for complex data analysis or machine learning tasks without worrying about data leakage because the service providers cannot see the original data throughout the process.
2. Privasea: The First AI+DePIN Network Using FHE
Privasea utilizes FHE technology to provide data privacy and security, utilizing AI and a distributed network architecture to allow complex data processing and analysis while keeping data fully encrypted. This means that users can engage in machine learning and other advanced computations without exposing the original data, a feat impossible in traditional cloud computing, disrupting privacy computation.
The Privasea platform employs several advanced FHE schemes such as TFHE and CKKS, ensuring high data privacy protection while maintaining computation 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 scientific and commercial applications like financial analysis, medical data processing, and machine learning tasks.
Additionally, Privasea has implemented a highly scalable distributed computing network, Privanetix. This network consists of multiple computing nodes, each capable of executing FHE operations and providing necessary computing resources. This distributed architecture not only enhances the platform’s processing capabilities but also improves 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 using Privasea for disease prediction and treatment optimization without violating data protection regulations.
Privasea also offers a unique smart contract suite, allowing users to manage and automate data processing processes while keeping data encrypted through smart contracts, including data verification, result output, and task allocation and rewards. These smart contracts execute on a distributed ledger, ensuring process transparency and traceability, and automatically allocating incentives based on the computing resources provided by nodes. This blockchain-based incentive mechanism further enhances network participation and computational efficiency as each node is incentivized to provide reliable services. This makes Privasea not just a data encryption and processing platform but a complete encrypted data ecosystem.
Through Privasea’s API, developers can easily access this complex system, leveraging its powerful capabilities to develop and deploy their AI applications. These applications can utilize distributed networks to distribute computing loads while ensuring data integrity and security, particularly crucial for blockchain applications that deal with large amounts of sensitive data.
3. Collaboration with Solana Highlights Mass Adoption Potential
Privasea leverages FHE technology to introduce the ImHuman application, showcasing FHE’s application in anti-bot attacks and signaling its mass adoption potential in the encryption field. Bot attacks pose a significant threat to decentralized networks, especially in airdrop scenarios, where attackers manipulate networks or gain unfair advantages by creating numerous fake identities. The ImHuman application effectively combats such attacks in a secure and privacy-preserving 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 characteristics make it an ideal blockchain platform to support Privasea’s FHE technology and AI computing needs. This deployment not only enhances the security of the Solana ecosystem but also showcases FHE’s potential in Web3 applications. By running on Solana, Privasea’s ImHuman application can more widely verify user identities, ensure network security and reliability, and protect user privacy.
The working principle of the ImHuman application involves using a user’s biometric data to create a unique digital identity. Firstly, users need to scan their facial vectors through the application’s front-facing camera, a process completed entirely on the user’s device to ensure sensitive data remains secure. Subsequently, this data is encrypted and transformed into an NFT representing the user’s encrypted biometric vector. This utilization of FHE’s feature of complex computation without decryption ensures data security and privacy.
During user authentication, the ImHuman application rescans the user’s facial features and compares the newly collected data with the encrypted data stored on the blockchain. This process also utilizes FHE technology to ensure data remains encrypted during verification, effectively mitigating the risk of data leakage. Additionally, since each user’s NFT is generated based on their unique biometric features, it is challenging 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 Fully Homomorphic Encryption technology in real-world applications. This authentication method based on biometric features and FHE offers a secure and privacy-preserving solution for decentralized networks, making Privasea’s ImHuman the first FHE application with mass adoption potential. Furthermore, by issuing airdrop rewards to participants, ImHuman can incentivize user participation and continuous usage, further driving its widespread application. This innovative solution provides a new strategy for defending against bot attacks.
4. Comparison of 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 Hong Kong Privacy Commissioner’s Office found that Worldcoin’s operations in Hong Kong violated the Privacy Ordinance. The investigation revealed that individuals participating in the Worldcoin project needed to provide facial and iris images for identity verification, posing severe risks to personal data privacy. As a result, the Hong Kong Privacy Commissioner requested Worldcoin to cease collecting iris and facial images of Hong Kong residents.
Human Protocol verifies user identity by collecting task response data, interaction data, device and browser information, geographic location, and user behavioral data. Although this data is anonymized and encrypted before usage, it still involves substantial collection of personal data, posing privacy and compliance risks.
In contrast, Privasea prioritizes user privacy protection in its design. Privasea’s DApp “ImHuman” uses FHE technology for user authentication without requiring the collection of sensitive information like facial or iris images. The verification process takes place entirely on the user’s mobile device, with facial vector data being encrypted and not transmitted to any servers. This approach ensures verification security 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 perform complex data processing and analysis without exposing user data, further reducing compliance risks. This unparalleled privacy protection and data security capability set Privasea apart in the competition, making it a leading Proof of Human solution in the industry.
5. Accseal Partners with Privasea to Deepen Privacy Computation
Privasea, with its exceptional FHE, DePIN, and ZK technological capabilities, has set a new standard in the field of privacy computation. As a pioneer in the AI DePIN field, Privasea, through its innovative FHE Machine Learning (FHEML) solution, seamlessly integrates distributed computing networks with advanced security measures, setting a new benchmark for data privacy and security. The introduction of the DApp “ImHuman” by Privasea leverages FHE technology to securely execute “Proof of Humanity” (PoH), encrypting facial vector data directly on users’ mobile devices without transmitting through servers, greatly enhancing privacy protection and user data security.
In this context, Privasea has strategically partnered with Accseal to strengthen its technological advantages. Accseal, a leading enterprise in hardware-accelerated privacy computing, will provide hardware acceleration support to Privasea, enhancing the efficiency and performance of its FHE operations. The two parties will explore the integration possibilities of ZK and FHE technologies, aiming 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 computational acceleration support for upper-layer applications like Privasea, further driving the development of privacy computing technology. The partnership between the two parties heralds new breakthroughs in the field of privacy computation, especially in the broader and deeper applications within the DePIN project.