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

The infrastructure in the Web3 space is rapidly improving, but as a key module that supports trust and participation, the "identification layer" has long been absent. From data labeling and 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 composed of alphanumeric characters, lacking structured individual characteristics and behavior labels. In the absence of additional identification layer mechanisms, the crypto-native world can hardly establish trustworthy user profiles, making it even more difficult to achieve reputation accumulation and credit assessment.

The lack of identification layers directly gives rise to one of the most common and challenging issues in Web3 - the witch attack. In various incentive activities that rely on user participation, malicious users can easily forge multiple identities, allowing them to repeatedly claim rewards, manipulate votes, and pollute data, rendering mechanisms that should be driven by "real human participation" completely ineffective.

Although some projects attempt to introduce "anti-Sybil" mechanisms to screen for abnormal behavior, the reality is that such measures often inadvertently harm real users, while actual bots can easily circumvent the rules. Therefore, we see that, in the absence of a strong identification basis, on-chain incentive distribution has always struggled 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 forged data using fake addresses to obtain incentives is common, disrupting data authenticity and directly affecting the practicality and trust foundation of the network. In GameFi, the behavior of using multiple accounts to complete 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.

In the field of AI, the lack of an identification layer also has far-reaching impacts. Currently, large-scale AI model training increasingly relies on "human feedback" and data annotation platforms, and these tasks are often outsourced to open communities or on-chain platforms. In the absence of a guarantee of "human uniqueness," the phenomenon of scripted batch simulation behaviors and robotic forgery of inputs is becoming more severe, which not only contaminates the training data but also greatly weakens the model's expressiveness and generalization capabilities.

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 onto the blockchain in a native and trustworthy manner. This not only limits institutions from participating in Web3 while ensuring user privacy, but the financial system on the blockchain also remains in a state of identity vacuum.

Exploration of Web3 Identification Layer

Currently, there are dozens of Web3 identification layer solutions on the market, which can be roughly divided into four categories:

1. Biometric: Characterized by biometric technology, ensuring the uniqueness of identification. Representative projects include Worldcoin, Humanode, etc. This type of solution often infringes on user privacy due to the collection of biometric data, and is relatively weak in terms of privacy protection and compliance.

2. Social trust category: emphasizes social trust networks and open verification. Representative projects include Proof of Humanity, Circles, etc. This type of solution theoretically can achieve a high degree of decentralization, but it is difficult to ensure the uniqueness of identification.

3. DID Aggregation: By integrating Web2 identity/KYC data, Verifiable Credentials, and other external credentials, a composable on-chain identity structure is built. Representative projects include Civic, SpruceID, etc. This type of solution has a high compatibility with existing compliance systems, but the uniqueness of identification is relatively weak.

4. Behavioral Analysis: Based on on-chain address behavior, interaction trajectories, and other data, user profiles and reputation systems are constructed using graph algorithms. Representative projects include ReputeX, Krebit, and others. These solutions provide good privacy protection, but it is difficult to establish a connection with the user's real identification.

In summary, existing identification layer solutions are generally trapped in an impossible triangle dilemma: it is difficult to simultaneously balance privacy protection, identity uniqueness, and decentralized verifiability. Except for biometric solutions, other types of identification mechanisms generally struggle to effectively ensure "identity uniqueness."

Solo's Technical Solution

Solo chooses biometric identification as the unique means of user identification and, based on cryptography, proposes a relatively unique technical path around the balancing challenge of "privacy protection" and "decentralized verifiability."

The Solo solution is based on the zkHE architecture, incorporating Pedersen commitments, homomorphic encryption (HE), and zero-knowledge proofs (ZKP). Users' biometric features can be processed with multiple layers of encryption locally, and the system generates verifiable zero-knowledge proofs and submits them on-chain without exposing any raw data, thus achieving the non-repudiation of identification and verifiability under privacy protection.

In the zkHE architecture of Solo, the identification verification process consists of a dual encryption defense line formed by homomorphic encryption (HE) and zero-knowledge proofs (ZKP). The entire process is completed locally on the user's mobile device, ensuring that sensitive information is not leaked.

Homomorphic encryption allows for direct computation on data while keeping it in an encrypted state. The system inputs the committed biometric features into the circuit in the form of homomorphic encryption, performing logical operations such as matching and comparison without the need to decrypt at any stage. Subsequently, based on the comparison results, a zero-knowledge proof is generated to determine "whether the distance is less than the threshold," thus completing the judgment of "whether it is the same person" without exposing the original data or distance value.

After completing the cryptographic calculations, Solo will generate a zero-knowledge proof locally for on-chain submission and verification. This ZKP proves that "I am a unique and real human being" without revealing any original biometric information or intermediate computation details. Solo employs the efficient Groth16 zk-SNARK as the proof generation and verification framework, producing concise and robust ZKP with minimal computational overhead. Ultimately, this ZKP is submitted to the exclusive Layer2 network SoloChain, where it is verified by on-chain contracts.

Verification Efficiency

The Solo solution has a very high verification efficiency, which is mainly reflected in the following aspects:

1. Cryptographic Algorithm Optimization: Solo has chosen the highly efficient Groth16 zk-SNARK as its main framework. This system features an extremely small proof size (approximately 200 bytes) and can achieve millisecond-level verification on-chain, significantly reducing interaction latency and storage overhead.

2. High performance: Experiments show that when facing high-dimensional biological feature data, Solo's zkHE architecture significantly outperforms traditional ZKP solutions in terms of proof generation time and total verification time. Under the condition of 128-dimensional data, the verification time for traditional ZKP exceeds 600 seconds, while the Solo solution remains largely unaffected, consistently staying within a few seconds.

3. Client optimization: The zkHE verification process of Solo (including Pedersen commitment generation, homomorphic encryption processing, and ZKP construction) can all 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.

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

Solo provides a new path to break the "impossible triangle" of the Web3 identification layer, 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 throughout the process, thereby completely avoiding the risk of privacy leakage.

2. Identification Uniqueness: By confirming whether the current validator and historical registration records are the same person through a distance comparison mechanism of feature vectors in encrypted state, we establish the basic identity constraint that "behind each address is a real unique human."

3. Usability: By finely optimizing the zk proof process, it ensures that all computational tasks can be completed on ordinary mobile devices, with verification generation times typically controlled within 2-4 seconds, and on-chain verification processes can be completed within milliseconds.

Solo has reserved compliance docking interfaces in its system design, including an optional bridging module that supports integration with on-chain DID and KYC systems, as well as the ability to anchor verification status to a specified Layer 1 network in certain scenarios. This provides the possibility for future implementation in the compliance market.

From a more macro perspective, the path adopted by Solo, which is based on biometrics + zkHE, forms a natural complementarity with other solutions. Solo is more like the underlying consensus module in the identification stack, focusing on providing a privacy-protected human uniqueness proof infrastructure for Web3. Its zkHE architecture can not only serve as a plug-in module for various DID or application front ends but can also combine with existing VC, zkID, SBT, etc., to establish 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, GEODNET, etc., covering various verticals such as data labeling, DePIN networks, and SocialFi games. These collaborations are expected to further validate the feasibility of Solo's identification mechanism and provide a feedback mechanism for calibrating real-world demand 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 1P1A capabilities and is expected to become an important underlying facility for promoting the evolution of on-chain identification systems and the expansion of compliant applications.