MT Capital Research Report: Privasea, Bringing Fully Homomorphic Encryption to Mass Adoption

Author: Xinwei, MT Capital

MT Capital has consistently focused on investing in innovative companies with disruptive technology potential. We believe that the combination of Fully Homomorphic Encryption (FHE) and Decentralized Physical Infrastructure Networks (DePIN) with AI is an important track for the future. FHE technology allows computations to be performed while keeping data encrypted, ensuring privacy and security throughout the data processing lifecycle. The integration of AI and DePIN not only efficiently utilizes external computing resources but also enables complex data analysis and machine learning tasks without the concern of data leakage. Privasea's leading position and technological advantages in this field align closely with MT Capital's investment strategy. We believe that by supporting Privasea, we will promote the development of the FHE AI DePIN track and contribute to the secure and sustainable growth 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 performed directly on ciphertext while keeping the data encrypted. This means that complex processing can be done on encrypted data without needing to decrypt it into plaintext, which is revolutionary for maintaining data privacy and security.

In traditional data processing scenarios, data must first be decrypted for computation, exposing sensitive information and increasing the risk of data theft or misuse. The application of FHE technology changes all of this. With FHE, encrypted data can be directly input into the computation process, and the computation results remain encrypted until decryption is needed to view the results. This feature is crucial for industries that handle sensitive data, such as finance, healthcare, and government sectors.

FHE also makes it possible to outsource data processing 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 leakage, as 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, leveraging AI and a distributed network architecture that allows for complex data processing and analysis while keeping data fully encrypted. This means users can perform machine learning and other advanced computations without exposing original data, which is impossible in traditional cloud computing, thus revolutionizing privacy computing.

The Privasea platform employs several advanced FHE schemes, such as TFHE and CKKS, which provide high data privacy protection while ensuring computational accuracy and efficiency. The TFHE scheme supports fast bit operations within a single instruction cycle, while the CKKS scheme optimizes the handling of floating-point numbers, enabling Privasea to effectively support various complex scientific and commercial applications, such as financial analysis, healthcare data processing, and machine learning tasks.

Additionally, Privasea has implemented a highly scalable distributed computing network called Privanetix. This network consists of multiple computing nodes, each capable of performing FHE operations and providing 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. The integration of AI and distributed networks allows Privasea to handle advanced AI tasks such as deep learning, pattern recognition, and machine learning, which typically require substantial computing power and high data protection. For instance, users in the healthcare industry can securely analyze sensitive patient data using Privasea for disease prediction and treatment optimization without worrying about violating data protection regulations.

Privasea also offers a unique suite of smart contracts that allows users to manage and automate data processing workflows while keeping data encrypted, including data validation, result output, and the allocation and rewards of computational tasks. These smart contracts execute on a distributed ledger, ensuring transparency and traceability of the process while also enabling automated 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 a complete ecosystem for encrypted data.

Through Privasea's API, developers can easily access this complex system and leverage its powerful features to develop and deploy their own AI applications. These applications can utilize the distributed network to offload computing tasks while ensuring data integrity and security, which is especially important for blockchain applications that handle large amounts of sensitive data.

3. Collaboration with Solana Highlights Mass Adoption Potential

Privasea has innovatively launched the ImHuman application using FHE technology, showcasing its application in countering Sybil attacks and marking its mass adoption potential in the encryption field. Sybil attacks are a significant threat in decentralized networks, particularly in the airdrop space, where attackers create numerous fake identities to manipulate the network or gain unfair advantages. 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. The high performance and low latency characteristics of Solana 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 demonstrate the potential of FHE in Web3 applications. By running on Solana, Privasea's ImHuman application can validate user identities more broadly, ensuring the security and reliability of the network while protecting user privacy.

The ImHuman application works by using users' biometric data to create a unique digital identity. First, users need to scan their facial vectors using the app's front camera, a process that is entirely completed on the user's device, ensuring that sensitive data does not leak. Subsequently, this data is encrypted and transformed into an NFT representing the user's encrypted biometric vector. This utilizes the feature of FHE, which allows complex computations to be performed 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 uses FHE technology, ensuring 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 Sybil 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 biometric and FHE-based authentication method offers a secure and privacy-preserving solution for decentralized networks, making Privasea's ImHuman the first application in the FHE field with mass adoption potential. Additionally, by distributing airdrop rewards to participants, ImHuman can incentivize user participation and continued use, further promoting its widespread application. This innovative solution provides a new strategy for defending against Sybil attacks.

4. Comparison of Privasea with Existing Proof of Human Solutions

In current Proof of Human solutions, projects like Worldcoin and Human Protocol face compliance risks and privacy issues. For instance, a recent investigation by the Hong Kong Privacy Commissioner found that Worldcoin's operations in Hong Kong violated the Personal Data (Privacy) Ordinance. The investigation revealed that individuals participating in the Worldcoin project were required to collect facial and iris images through iris scanning to verify human identity, which poses serious personal data privacy risks. As a result, the Hong Kong Privacy Commissioner has demanded that Worldcoin cease collecting citizens' iris and facial images in Hong Kong.

Human Protocol verifies users by collecting task response data, interaction data, device and browser information, geographic location, and user behavior data. Although this data is anonymized and encrypted before use, it still involves significant personal data collection, posing certain privacy and compliance risks.

In contrast, Privasea is designed with a stronger focus on user privacy protection. Privasea's DApp "ImHuman" employs FHE technology for user identity verification without needing to collect sensitive information such as facial or iris images. The verification process is entirely conducted on the user's mobile device, with facial vector data being encrypted and not transmitted to any servers. This way, Privasea maximizes user privacy protection while ensuring verification security, avoiding the risk of data leakage.

Privasea not only leads in privacy protection but also provides robust data privacy and security solutions 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 allows Privasea to stand out in the competition, becoming an industry-leading Proof of Human solution.

5. Accseal and Privasea Collaborate to Deepen Privacy Computing

Privasea has set a new standard in privacy computing with its exceptional capabilities in FHE, DePIN, and ZK technologies. As a pioneer in the AI DePIN field, Privasea seamlessly integrates distributed computing networks with advanced security measures through its innovative FHE Machine Learning (FHEML) solution, establishing a new benchmark for data privacy and security. The DApp "ImHuman" introduced by Privasea utilizes FHE technology to securely execute "Proof of Humanity" (PoH), directly encrypting facial vector data on users' mobile devices without server transmission, greatly enhancing privacy protection and user data security.

In this context, Privasea has formed a strategic partnership with Accseal to further strengthen its technological advantages. Accseal, a leading company in privacy computing hardware acceleration, 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, aiming to improve the efficiency of privacy computing and expand its application scope.

Through this collaboration, Privasea not only showcases 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 promoting the development of privacy computing technology. The partnership signals that the privacy computing field is poised for new breakthroughs, especially in the broader and deeper application of DePIN projects.