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

The infrastructure in the Web3 field is rapidly improving, but the "identification layer" as a key module supporting trust and participation has been in a state of long-term absence. From data labeling, behavior scoring to protocol interaction and community governance, a large number of key tasks in Web3 rely on "human input" as an effective data source. However, from the perspective of on-chain systems, users are usually just a wallet address, lacking structured individual characteristics and behavioral labels. Without additional identification layer mechanisms in place, 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 tricky problems in Web3: witch attacks. In various incentive activities that rely on user participation, malicious users can easily fabricate multiple identifications, thereby repeatedly claiming rewards, manipulating votes, and polluting data, rendering mechanisms that should be driven by "real human participation" completely ineffective.

Although some projects attempt to introduce "anti-Sybil" mechanisms to filter out abnormal behaviors, the reality is that such measures often inadvertently harm real users, while actual bots can easily bypass the rules. In the absence of a strong identification foundation, on-chain incentive distribution always struggles to achieve fairness, efficiency, and sustainability.

In other vertical scenarios of Web3, the problems caused by the lack of identification are equally significant. In the DePIN field, the phenomenon of submitting fake address data to fraudulently obtain incentives is common, disrupting the authenticity of the data and directly affecting the practicality and trust foundation of the network. In GameFi, the behavior of multi-account task brushing and bulk reward claiming severely undermines the balance of the in-game economic system, leading to the loss of real players and the failure of project incentive mechanisms.

In the field of AI, the absence of the identification layer also has far-reaching effects. Currently, large-scale AI model training increasingly relies on "human feedback" and data labeling platforms, and these tasks are often outsourced to open communities or on-chain platforms. In the absence of guarantees for "human uniqueness," the phenomenon of script-based batch simulation behavior and robot-generated inputs is becoming more severe, which not only pollutes the training data but also greatly weakens the model's expressiveness and generalization ability.

In addition, without 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 way. This not only limits institutions' ability to participate in Web3 while protecting user privacy, but also keeps the on-chain financial system in a state of identity vacuum. DeFi lending models have long relied on over-collateralization mechanisms, making it difficult to reach a broader range of unsecured credit lending scenarios, severely restricting user coverage and capital efficiency.

The same problem also arises in the fields of Web3 advertising, social media, etc. Due to the lack of verifiable user identification and behavioral preferences, mechanisms such as precise recommendations and personalized incentives are difficult to establish, further restricting the depth of operation and commercialization space of on-chain applications.

Exploration of Web3 Identification Layer

Currently, there are numerous Web3 identification layer solutions on the market, which can be broadly divided into four categories:

1. Biometric: Characterized by biometric technology, ensuring unique identification and possessing strong resistance against witch attacks. However, it is prone to infringing on user privacy and is relatively weak in privacy protection and compliance.

2. Social Trust Category: Emphasizes user sovereignty, with social trust networks and open verification at its core. Theoretically, it can achieve a high degree of decentralization, but the uniqueness of identification is difficult to ensure, making it susceptible to witch attacks.

3. DID Aggregation: By integrating Web2 identity/KYC data, Verifiable Credentials, and other external credentials, a composable on-chain identity structure is constructed. It has a high compatibility with the existing compliance system, but the uniqueness of identity is relatively weak and the degree of decentralization is limited.

4. Behavioral Analysis: Based on on-chain address behavior, interaction trajectories, and other data, user profiles and reputation systems are constructed using graph algorithms. Privacy protection is good, but it is difficult to establish a connection with the user's true identification, and it is easily affected by witchcraft behavior.

The existing identification layer schemes are generally trapped in the "impossible triangle" dilemma: it is difficult to balance privacy protection, identity uniqueness, and decentralized verifiability at the same time. Except for biometric solutions, other schemes generally struggle to effectively ensure "identity uniqueness."

Solo's technical solution

Solo chooses biometric identification as the unique basis for user identification, and proposes a unique technical path based on cryptography to balance "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 biometric features undergo multiple encryption processes locally, and the system generates verifiable zero-knowledge proofs and submits them to the chain without exposing the original data, achieving non-falsifiability of identification and verifiability under privacy protection.

In the zkHE architecture, the authentication process is composed of a dual encryption defense line formed by homomorphic encryption (HE) and zero-knowledge proof (ZKP), completed locally on the user's mobile device, ensuring that sensitive information will not be leaked.

Homomorphic encryption allows computations to be performed directly on data while it remains encrypted. The system inputs the committed biometric features into the circuit in the form of homomorphic encryption, performing operations such as matching and comparison 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 whether they come from the same person. This computation is also completed in an encrypted state, and the system subsequently generates a zero-knowledge proof based on the result of "whether the distance is less than the threshold."

After completing the cryptographic computation, Solo generates a zero-knowledge proof locally for on-chain submission and verification. This ZKP proof "I am a unique and real human being" does not disclose any original biometric information or intermediate computational details. Solo uses 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, and the entire process does not require access to sensitive data. Ultimately, the ZKP is submitted to the dedicated Layer2 network SoloChain, where it is verified by on-chain contracts.

Solo performs exceptionally well in verification efficiency. Thanks to the streamlined design of the encryption 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 adoption and on-chain integration.

In terms of client performance, Solo has undergone extensive optimization. The zkHE verification process can be completed locally on ordinary smartphones. 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 any proprietary hardware or trusted execution environments, greatly lowering the threshold for large-scale deployment.

A New Attempt to Break the "Impossible Triangle" of Web3 Identification Layer

Solo provides a new path to break the "impossible triangle" of Web3 identification, achieving a technological balance and breakthrough among privacy protection, identification uniqueness, and usability.

On the privacy level, the zkHE architecture allows all users' biometric features to be homomorphically encrypted and constructed with ZKP locally, without the need to upload or decrypt the original data throughout the process, thereby avoiding the risk of privacy leakage and freeing itself from reliance on centralized identity providers.

In terms of identification uniqueness, Solo confirms whether the current validator is the same person as the historical registration record through a feature vector distance comparison mechanism in an encrypted state, without leaking the data structure, establishing the basic identity constraint of "each address corresponds to a real unique individual."

In terms of usability, Solo ensures that all computational tasks can be completed on ordinary mobile devices through fine optimization of the zk proof process. The verification generation time is typically controlled within 2-4 seconds, and the on-chain verification process can be completed in milliseconds while remaining fully decentralized, meeting the real-time requirements of highly demanding application scenarios such as blockchain games, DeFi, and L2 logins.

Solo has reserved compliance docking interfaces in system design, including optional bridging modules that support integration with on-chain DID and KYC systems, as well as the capability to anchor verification status to a specified Layer 1 network in certain scenarios. In the future, when landing in compliance markets, Solo is expected to meet the requirements for identification, data traceability, and regulatory cooperation in various regions while maintaining privacy and decentralization features.

From a more macro perspective, the path of Solo based on biometric features + zkHE forms a natural complementarity with other solutions. Compared to solutions that focus on upper-layer identification labels or behavioral credentials, Solo has constructed a foundational identity network that can complete "human uniqueness confirmation" at the lowest level, and possesses characteristics such as privacy protection, trustlessness, embeddability, and sustainable verification, providing foundational "human authenticity verification" for higher-level VC, SBT, social graphs, etc.

Solo can be seen as the "trusted anonymous layer" infrastructure at the bottom of the identification system, filling the long-standing capability gap in the industry of "1P1A( One Person, One Account )", supporting higher-level applications and providing a foundation for compliance.

Currently, Solo has partnered with multiple protocols and platforms, 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 and provide a feedback mechanism for real-world demand calibration for its zkHE model, helping Solo continuously optimize user experience and system performance.

By building a trusted and anonymous identification layer system for the Web3 world, Solo is laying the foundation for the capability of 1P1A and is expected to become an important underlying infrastructure to promote the evolution of on-chain identification systems and the expansion of compliant applications.