MT Capital Research Report: Will Privasea bring fully homomorphic encryption to Mass Adoption?

MT Capital has always been committed to investing in innovative companies with disruptive technological potential. We believe that the decentralized physical infrastructure network (DePIN) that combines fully homomorphic encryption (FHE) with AI is an important track in the future. FHE technology can perform calculations while maintaining data encryption, ensuring privacy and security during the entire data processing process. The combination of AI and DePIN can not only efficiently utilize external computing resources, but also perform complex data analysis and machine learning tasks without worrying about data leakage. Privasea's leading position and technological advantages in this field are highly consistent 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 safe 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 performed directly on ciphertext while maintaining the encrypted state of the data. This means that complex processing can be performed on encrypted data without the need to decrypt it into clear text, which is revolutionary in maintaining data privacy and security.

In traditional data processing scenarios, in order to perform calculations, the data must first be decrypted. This process exposes sensitive information and increases the risk of data theft or misuse. The application of FHE technology has completely changed all this. With FHE, encrypted data can be fed directly into the calculation process, while the calculation results remain in encrypted form until they are decrypted until the results need to be viewed. This feature is important for industries that need to handle sensitive data, such as the financial, medical and government sectors.

FHE also makes it possible to outsource data processing without sacrificing data confidentiality. Enterprises 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 provider cannot see the original data during the entire process.

2.Privasea: The first AI+DePIN network using FHE

Privasea uses FHE technology to provide data privacy and security, leveraging AI and distributed network architecture to allow data integrity while maintaining Perform complex data processing and analysis in an encrypted state. This means that users can perform machine learning and other advanced calculations without exposing original data, which is impossible in traditional cloud computing, subverting privacy computing.

The Privasea platform adopts several advanced FHE schemes, such as TFHE and CKKS, which provide a high degree of data privacy protection while ensuring calculation accuracy and efficiency. Among them, the TFHE solution supports fast bit operations within a single instruction cycle, while the CKKS solution optimizes the ability to process floating point numbers, allowing Privasea to effectively support various complex scientific research and commercial applications, such as financial analysis and medical data. processing and machine learning tasks.

In addition, Privasea also implements Privanetix, a highly scalable distributed computing network. This network consists of multiple computing nodes, each node can perform FHE operations and provide necessary computing resources. This distributed architecture not only enhances the platform's processing capabilities, but also improves the system's redundancy and fault tolerance, ensuring high availability and reliability of services. This integration of AI and distributed networks allows Privasea to handle advanced AI tasks such as deep learning, pattern recognition and machine learning, which usually require huge computing power and a high degree of data protection. For example, users in the medical and health industry can use Privasea to safely analyze sensitive patient data, predict diseases and optimize treatment plans without worrying about violating data protection regulations.

Privasea also provides a unique smart contract suite that allows users to manage and automate data processing processes, including data verification, through smart contracts while maintaining data encryption. , result output, and allocation and reward of computing tasks. These smart contracts are executed on a distributed ledger, which not only ensures the transparency and traceability of the process, but also enables automated incentive distribution based on the computing resources provided by the nodes. This blockchain-based incentive mechanism further improves network participation and computational 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 use its powerful functions to develop and deploy their own AI applications. These applications are able to leverage distributed networks to spread computing load while ensuring data integrity and security, which is especially important for blockchain applications that need to handle large amounts of sensitive data.

3. Cooperation with Solana demonstrates the potential of Mass Adoption

Privasea uses FHE technology to groundbreakingly launch the ImHuman application, which not only demonstrates the application of FHE in anti-witch attacks, but also marks its application in anti-witch attacks. Mass Adoption Potential in Crypto. Sybil attacks are a major threat in decentralized networks, especially in the airdrop space, where attackers create a large number of fake identities to manipulate the network or gain unfair advantages. The ImHuman app effectively combats such attacks in a secure and privacy-preserving manner.

Privasea plans to deploy its technology to the Solana network and become the first Proof of Human application on Solana. Solana’s high performance 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 will also demonstrate the potential of FHE in Web3 applications. By running on Solana, Privasea's ImHuman application is able to more broadly verify user identities, ensuring the security and reliability of the network while protecting user privacy.

#The ImHuman app works by using a user’s biometric data to create a unique digital identity. First, users need to scan their facial vectors through the app's front-facing camera. This process is completed entirely on the user's device, ensuring that sensitive data will not be leaked. This data is then encrypted and converted into an NFT that represents the user’s encrypted biometric vector. This takes advantage of the characteristics of FHE, which is to perform complex calculations without decrypting the data, ensuring the security and privacy of the data.

During user authentication, the ImHuman app 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 to ensure that the data will not be decrypted during the verification process, thus effectively avoiding the risk of data leakage. In addition, because each user's NFT is generated based on their unique biometrics, it is difficult to copy or forge, greatly increasing the difficulty of performing a Sybil attack.

With the ImHuman app, 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 biometrics and FHE provides a secure and privacy-preserving solution for decentralized networks, making Privasea's ImHuman the first application in the FHE field with Mass Adoption potential. In addition, by issuing airdrop rewards to participants, ImHuman can also encourage user participation and continued use, further promoting its widespread application. This innovative solution provides a new defense strategy against Sybil attacks.

4. Comparison between Privasea and existing Proof of Human solutions

In the current Proof of Human solutions, such as Worldcoin and Human Protocol are facing compliance risks and privacy issues. Taking Worldcoin as an example, the recently completed investigation results of the Office of the Privacy Commissioner of Hong Kong showed that Worldcoin’s operations in Hong Kong violated the Privacy Ordinance. The investigation found that people participating in the Worldcoin project need to collect facial and iris images through iris scanning to verify human identity. This practice involves serious personal data privacy risks. Therefore, the Hong Kong Privacy Commissioner requested Worldcoin to stop collecting citizens’ iris and facial images in Hong Kong.

Human Protocol conducts verification by collecting the user's task response data, interaction data, device and browser information, geographical location and user behavior data. Although this data is anonymized and encrypted before use, it still involves the collection of a large amount of personal data and poses certain privacy and compliance risks.

In contrast, Privasea pays more attention to user privacy protection in design. Privasea's DApp "ImHuman" uses FHE technology for user identity verification and does not need to collect sensitive information such as the user's face or iris image. The verification process takes place entirely on the user's mobile device, and facial vector data is encrypted and not transmitted to any server. In this way, while ensuring verification security, Privasea also protects user privacy to the greatest extent and avoids the risk of data leakage.

Privasea not only leads in privacy protection, but also provides powerful 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 capabilities set Privasea apart from the competition and become the industry's leading Proof of Human solution.

5.Accseal and Privasea join hands to delve into privacy computing

Privasea has set a new standard in the field of privacy computing with its excellent FHE, DePIN and ZK technical capabilities. As a pioneer in the field of AI DePIN, Privasea sets a new benchmark for data privacy and security through its innovative FHE Machine Learning (FHEML) solution that seamlessly combines distributed computing networks with advanced security measures. The DApp "ImHuman" introduced by Privasea uses FHE technology to securely perform "Proof of Humanity" (PoH) and directly encrypts facial vector data on the user's mobile device without transmitting it through the server, thereby greatly enhancing privacy protection and the security of user data. .

In this context, Privasea has reached a strategic cooperation with Accseal to further strengthen its technological advantages. As a leader in privacy computing hardware acceleration, Accseal will provide hardware acceleration support for Privasea to improve the efficiency and performance of its FHE operations. The two parties will jointly explore the possibility of integrating ZK and FHE technologies, aiming to improve the efficiency of privacy computing and expand its application scope.

Through this cooperation, Privasea not only demonstrates its leadership in the FHE field, but also takes its DePIN project to new heights. Accseal will develop new hardware acceleration products to provide computing acceleration support for upper-layer applications such as Privasea, further promoting the development of privacy computing technology. The cooperation between the two parties heralds a new breakthrough in the field of privacy computing, especially the application in the DePIN project will be more extensive and in-depth.

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