Solo: A New Attempt to Build a Trusted Anonymous Identity Layer for Web3

The infrastructure in the Web3 space is rapidly improving, but the "identification layer" as a key module supporting trust and participation has been lacking. From data labeling to protocol interaction and community governance, a large number of critical tasks in Web3 rely on "human input" as an effective data source. However, from the perspective of on-chain systems, users are often just a string of wallet addresses, lacking individual characteristics and behavioral labels. Without an additional identification layer mechanism, it is difficult for the crypto-native world to establish trustworthy user profiles, let alone achieve reputation accumulation and credit assessment.

The lack of identification layers has directly given rise to one of the most common and challenging problems in Web3 - Sybil attacks. In incentive activities that rely on user participation, malicious users can easily forge multiple identities to repeatedly claim rewards, manipulate votes, and pollute data, rendering mechanisms that should be driven by "real human participation" ineffective. In the 2023 Celestia airdrop, as much as 65% of the 60 million $TIA was acquired by bots or Sybil accounts, and similar phenomena are widely observed in the distribution processes of other projects.

Despite some projects attempting to introduce "anti-Sybil" mechanisms to screen for abnormal behavior, they often mistakenly harm real users, while actual bots can easily circumvent the rules. The airdrop anti-witch rule of EigenLayer has sparked controversy, with some normal users being misjudged as witch attackers and excluded. In the absence of a strong identification foundation, on-chain incentive distribution struggles to achieve fairness, efficiency, and sustainability.

In the DePIN field, the phenomenon of submitting forged data using fake addresses to obtain incentives is not uncommon, disrupting the authenticity of data and directly affecting the practicality and trust foundation of the network. In GameFi, the behavior of using multiple accounts to complete tasks and receive rewards in bulk severely undermines the balance of the in-game economic system, leading to the loss of real players and the failure of project incentive mechanisms.

The AI field is also profoundly affected by the lack of identification layer. Currently, the training of large-scale AI models increasingly relies on "human feedback" and data labeling platforms, which are typically outsourced to open communities or on-chain platforms. In the absence of a guarantee of "human uniqueness", the phenomenon of scripts simulating behaviors in bulk and robots faking inputs has become increasingly severe, not only contaminating the training data but also greatly weakening the model's expressiveness and generalization ability.

In the absence of an effective identification layer, the KYC mechanisms, credit scoring systems, and behavioral profiles widely used in the Web2 world can hardly be mapped onto the blockchain in a native and trustworthy manner. This limits the ability of institutions to participate in Web3 while ensuring user privacy, and the on-chain financial system remains in an identity vacuum. DeFi lending models have long relied on over-collateralization mechanisms, making it difficult to reach broader unsecured credit lending scenarios, severely restricting user coverage and capital efficiency.

Web3 advertising, social media, and other fields face similar issues. Due to the lack of verifiable user identification and behavioral preferences, mechanisms for precise recommendations and personalized incentives are difficult to establish, further limiting the depth of operational capabilities and commercialization space for on-chain applications.

Currently, there are dozens of Web3 identification layer solutions on the market, such as Worldcoin, Humanode, Proof of Humanity, Circles, idOS, ReputeX, Krebit, etc., which can be roughly divided into four categories:

1. Biometric: Ensures identity uniqueness through biometric technology, has strong resistance to Sybil attacks, but can easily infringe on user privacy, relatively weak in privacy protection and compliance.

2. Social Trust Type: Emphasizes user sovereignty, establishing a trusted identity network based on social relationship graphs, community mutual authentication, etc. Although it theoretically achieves a high degree of decentralization, the uniqueness of identification is difficult to guarantee and is susceptible to witch attacks.

3. DID Aggregation: Integrate Web2 identification/KYC data, Verifiable Credentials, and other external credentials to build a composable on-chain identity structure. It has a high compatibility with existing compliance systems, but weaker uniqueness of identification and limited decentralization.

4. Behavioral Analysis: Based on on-chain address behaviors, interaction trajectories, and other data, utilize graph algorithms to construct user profiles and reputation systems. Privacy protection is good, but it is difficult to establish a connection with the user's true identification, and it is susceptible to witchcraft behavior interference.

These solutions generally fall into the "impossible triangle" dilemma: it is difficult to simultaneously ensure privacy protection, identification uniqueness, and decentralized verifiability. Apart from biometric solutions, other schemes generally struggle to effectively guarantee "identification uniqueness."

Solo chooses to use biometric identification as the unique basis for identity and proposes a unique technical path based on cryptography that addresses the balance challenge between "privacy protection" and "decentralized verifiability."

The Solo solution is based on the zkHE architecture, integrating Pedersen commitments, homomorphic encryption (HE), and zero-knowledge proofs (ZKP). User biometrics undergo multiple encryption processes locally, and the system generates verifiable zero-knowledge proofs and submits them on-chain without exposing the original data, achieving non-falsifiability of identification and verifiability under privacy protection.

In the zkHE architecture, the authentication process consists of a dual encryption defense using homomorphic encryption (HE) and zero-knowledge proof (ZKP), completed entirely on the user's mobile device locally, ensuring that sensitive information in plaintext will not be leaked. Homomorphic encryption allows computations to be performed directly while the data remains encrypted; the system inputs the committed biometric features in the form of homomorphic encryption into the circuit to execute matching and comparison operations without the need for decryption.

The comparison process essentially calculates the distance between the biometric feature vectors of the registered data and the current verification data to determine if they come from the same person. The distance calculation is completed in an encrypted state, and the system generates a zero-knowledge proof based on the comparison result, indicating whether "the distance is less than the threshold," completing the identification without exposing the original data or the distance value.

After completing the cryptographic computation, Solo generates a zero-knowledge proof locally for on-chain submission and verification. This ZKP proves "I am a unique and real human being" without disclosing any original biometric information or intermediate computation details. Solo adopts the efficient Groth16 zk-SNARK as the proof generation and verification framework, generating concise and robust ZKP with minimal computational overhead. The verifier only needs to check this proof to confirm the validity of the identification without accessing any sensitive data. Finally, the ZKP is submitted to the dedicated Layer2 network SoloChain, where it is verified by on-chain contracts.

Solo excels in verification efficiency. Thanks to the streamlined design of the cryptographic process and the introduction of high-performance primitives, Solo can achieve low-latency and high-throughput identification experiences on mobile devices, providing strong technical support for large-scale user usage and on-chain integration.

A substantial optimization has been made in client performance by Solo. The zkHE verification process (including Pedersen commitment generation, homomorphic encryption processing, and ZKP construction) can be completed locally on a regular smartphone. The actual test results show that the overall computation time on mid-range devices is 2-4 seconds, which is sufficient to support smooth interactions for most Web3 applications without relying on proprietary hardware or trusted execution environments, greatly reducing the threshold for large-scale deployment.

Solo provides a new path to break the "impossible triangle" of Web3 identification, achieving a technological balance and breakthrough among privacy protection, identity uniqueness, and usability. The zkHE architecture allows users' biometric features to be homomorphically encrypted and ZKP constructed locally, with the entire process not requiring the uploading or decryption of original data, thus avoiding the risk of privacy leakage and freeing users from reliance on centralized identification providers.

Through the feature vector distance comparison mechanism in encrypted state, Solo confirms whether the current validator is the same person as the historical registration record without disclosing the data structure, establishing the foundational identity constraint of "behind each address is a real unique human," that is, one person one account (1P1A).

In terms of usability, Solo ensures that all computing tasks can be completed on regular mobile devices through fine optimization of the zk proof process. Practical tests have shown that the verification generation time is typically controlled within 2-4 seconds, while the on-chain verification process can be completed within milliseconds and is fully decentralized, meeting the real-time requirements of applications such as blockchain games, DeFi, and L2 logins.

Solo has reserved compliance interface connections in system design, including optional bridging modules that support integration with on-chain DID and KYC systems, as well as the ability to anchor verification status to a specific Layer 1 network under certain scenarios. In the future, when targeting the compliant market, Solo is expected to meet the requirements for identification, data traceability, and regulatory cooperation in various locations while maintaining privacy and decentralization.

Solo adopts a biometric + zkHE path, forming a natural complement to other solutions. Compared to solutions that focus on upper-level identification labels or behavioral credentials, Solo builds a foundational identity network that can achieve "human uniqueness confirmation" at the lowest level, with characteristics such as privacy protection, trustlessness, embeddability, and sustainable verification, providing basic "human experience verification" for higher-level VC, SBT, social graphs, and more.

Solo is more like the underlying consensus module in the identification stack, focusing on providing a privacy-preserving infrastructure for human uniqueness proofs in Web3. Its zkHE architecture can not only serve as a plug-in module for various DIDs or application front-ends but can also form a combination with existing VCs, zkIDs, SBTs, etc., establishing a verifiable and composable real identity foundation for the on-chain ecosystem.

Currently, Solo has established partnerships with multiple protocols and platforms, including Kiva.ai, Sapien, PublicAI, Synesis One, Hive3, and GEODNET, covering various verticals such as data labeling, DePIN networks, and SocialFi games. These collaborations are expected to further validate the feasibility of the Solo identification mechanism, providing a feedback mechanism for real-world demand calibration for its zkHE model, helping Solo continuously optimize user experience and system performance.

By building a trustworthy and anonymous identification layer system, Solo is laying the foundational capability for 1P1A in the Web3 world, with the potential to become an important underlying facility for promoting the evolution of on-chain identification systems and the expansion of compliant applications.