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

The infrastructure in the Web3 field is continuously improving, but the "identification layer" has long been absent as a key module. From data labeling and behavior scoring to protocol interaction and community governance, many critical 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 composed of alphanumeric characters, lacking structured individual characteristics and behavior tags. Without additional identification layer mechanisms to support it, the crypto-native world is almost unable to establish trustworthy user profiles, let alone achieve reputation accumulation and credit evaluation.

The lack of identification directly gives rise to one of the most common and troublesome issues in Web3 - the witch attack. In various incentive activities that rely on user participation, malicious users can easily forge multiple identities, 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 behavior, the reality is that these methods often inadvertently harm real users, while actual manipulators can easily circumvent the rules. In the absence of a strong identification foundation, on-chain incentive distribution has always struggled to achieve fairness, efficiency, and sustainability.

In other vertical scenarios of Web3, the issues caused by the lack of identification are also significant. For example, in the DePIN field, the phenomenon of submitting forged data with fake addresses to cheat incentives is common, 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 farm tasks and claim rewards in bulk severely disrupts 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 layers. 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 batch simulation behavior and robot forgery of inputs has become more severe, which not only pollutes the training data but also greatly weakens the model's expressive power and generalization ability.

In addition, 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 to the blockchain in a native and trustworthy manner. This not only limits institutions' ability to participate in Web3 while safeguarding user privacy, but the financial system on the blockchain remains in a state of identity vacuum. A typical example is that DeFi lending models have long relied on over-collateralization mechanisms, making it difficult to reach broader scenarios of unsecured credit lending, severely restricting user coverage and capital efficiency.

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

Exploration of Web3 Identification Layer

Currently, there are many Web3 identification layer solutions on the market, all of which are trying to fill the gap of the Web3 identification layer, which can be roughly divided into four categories:

1. Biometric: Characterized by biometric technology, ensuring unique identification, possessing strong resistance to Sybil attacks, but may have privacy protection and compliance issues.

2. Social Trust: Emphasizes user sovereignty, establishing a trusted identity network through social relationship graphs and community mutual certification. However, the uniqueness of identity is difficult to guarantee and is susceptible to witch attacks.

3. DID Aggregation: Integrates Web2 identification/KYC data, Verifiable Credentials, and other external credentials to build a composable on-chain identity structure, but the uniqueness of the identification is relatively weak and the degree of decentralization is limited.

4. Behavioral Analysis: Construct user profiles and reputation systems based on on-chain address behavior, interaction trajectories, and other data. Privacy protection is good, but it is difficult to establish connections with real identification, and it is easily affected by witch behavior.

Current identity layer solutions generally fall into 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 types of identity mechanisms 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 around the balancing dilemma of "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). Users' biometric features undergo multiple encryption processes locally, and the system generates verifiable zero-knowledge proofs without exposing the original data, submitting them to the blockchain to achieve non-repudiation of identification and verifiability under privacy protection.

In the zkHE architecture, the authentication process consists of a dual encryption defense formed by homomorphic encryption and zero-knowledge proof:

1. Homomorphic encryption: The system inputs the biometric features after commitment into the circuit in the form of homomorphic encryption, performing logical operations such as matching and comparison without the need for decryption throughout the process.

2. Zero-Knowledge Proof: After completing the cryptographic computation, Solo generates a zero-knowledge proof locally to prove "I am a unique and real human being" without revealing any original biological 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 identification validity, and the entire process does not require access to any sensitive data.

Breaking the "Impossible Triangle" of Web3 Identification Layer: A New Attempt

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

1. Privacy aspect: The zkHE architecture allows all users' biometric features to be homomorphically encrypted and ZKP constructed locally, without the need to upload or decrypt the original data, thus avoiding the risk of privacy leakage.

2. Identification Uniqueness: Through the distance comparison mechanism of feature vectors in an encrypted state, confirm whether the current validator is the same person as in historical registration records, establishing the basic identity constraint of "behind each address is a real unique individual."

3. Availability: The zk proof process is finely optimized to ensure that all computational tasks can be completed on ordinary mobile devices, with verification generation times typically controlled within 2-4 seconds, and the on-chain verification process can be completed in milliseconds while being fully decentralized.

Solo has reserved compliance docking interfaces in the 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 specified Layer 1 network in specific scenarios. This provides the possibility for future deployment in the compliance market.

Summary

Solo is building a trusted and anonymous identification layer system for the Web3 world, laying the foundational capabilities for 1P1A (One Person, One Account). As the underlying consensus module in the identity stack, Solo focuses on providing a unique proof of human identity infrastructure with privacy protection capabilities for Web3. Its zkHE architecture can not only be integrated as a plugin module for various DID or application front-ends, but also form a combination with existing VC, zkID, SBT, etc., to establish a verifiable and composable real identity foundation for the on-chain ecosystem.

Currently, Solo has collaborated with multiple protocols and platforms, covering various verticals such as data labeling, DePIN networks, and SocialFi gaming. These collaborations are expected to further validate the feasibility of Solo's identification verification mechanism, providing a feedback mechanism for real-world demand calibration for its zkHE model, helping Solo continuously optimize user experience and system performance.