Oracles

Oracle technology evolution and paradigm breakthrough

Trust bounds for traditional oracle

Traditional oracle architectures (such as Chainlink) achieve data trustworthiness through multi-node signature mechanisms but face two core challenges:

• Data Transparency Paradox: On-chain disclosure of raw data may lead to sensitive information leaks (such as financial trading strategies and corporate operation data).

• Single-Dimensional Verification: Relies solely on the number of signatures to verify data authenticity, lacking verifiability of the data generation process.

ENI introduces an innovative four-layer trust verification system by incorporating Zero-Knowledge Proofs (ZKP) and cross-chain verification frameworks:

• Privacy Layer: Uses zk-SNARK for anonymizing input data.

• Verification Layer: Combines Tendermint BFT consensus with threshold signatures for dual-layer verification.

• Proof Layer: Utilizes the IBC protocol to achieve compressed zero-knowledge proofs for cross-chain state verification.

• Incentive Layer: Implements a Proof of Contribution (PoC)-based reputation system for nodes.

Matrix of zero-knowledge oracle technologies

Technical Dimension	Traditional Solution	ENI’s Solution
Data Privacy	Plaintext Transmission	Verifiable Encrypted Data Flow
Verification Efficiency	Multi-round Mutual Verification	Single Effective Proof
MEV Resistance Capability	Transactions Easily Front-Run	Zero-Knowledge Encapsulation of the Entire Process
Cross-Chain Verification	Relies on Third-Party Bridges	Native IBC Proof Verification

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Core Architecture of ENI Zero-Knowledge Oracles

System Layering Model

Privacy Data Flow Pipeline: (Data Collection → zk Preprocessing → Multi-Chain Verification → Proof Aggregation → Smart Contract Interface)

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Key Technological Innovations

Dual Privacy Protection Mechanism:

• Input Privacy: Uses the Paillier homomorphic encryption algorithm to enable aggregation of encrypted data.

• Leverages the Groth16 protocol to generate validity proofs. Verifier nodes only need to validate the proof’s correctness without accessing raw data.

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Cross-Chain Verification Network

• IBC Light Client Verification: Compresses external chain state proofs into zk-SNARK circuits.

• State Snapshot Signatures: Generates verifiable cross-chain state snapshots every 30 blocks.

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MEV-Resistant Design

• Request Obfuscation Pool: Uses ring signature technology to hide the identity of requestors.

• Delayed Proof Mechanism: Executes data responses and proof generation asynchronously to mitigate MEV risks.

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ICore Functions of Zero-Knowledge Oracles

Privacy Data Verification

• Compliance Proofs: Enterprises can submit proofs for compliance with carbon emissions standards without revealing exact data.

• Credit Assessment: Financial institutions can verify user credit scores without accessing full credit records.

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Cross-Chain State Proofs

• Cross-Chain Asset Verification: Verifies asset states on other chains via the IBC channel, generating compressed proofs.

• Smart Contract Interoperability: Supports cross-chain contract calls under zero-knowledge conditions.

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IoT Data On-Chain

• Encrypted Device Fingerprinting: Processes industrial sensor data through zk circuits to generate unique device fingerprints.

• End-to-End Verification: Ensures verifiable and confidential data flows from collection to on-chain storage.

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Developer Integration Guide

Basic Integration Process

Initialize Oracle Contracts:

interface IZKOracle {
    function request(
        bytes32 circuitID,
        bytes calldata encryptedParams
    ) external returns (uint256 requestId);
}

Build Zero-Knowledge Circuits:

• Define data verification logic using Circom language.

• Deploy verification keys to the on-chain registry.

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Typical Application Scenarios

Scenario 1: Privacy Financial Contracts

• Anonymous Lending: Borrowers can prove their asset holdings without exposing details.

• Dark Pool Trading: Executes large-scale trade orders under zero-knowledge conditions.

Scenario 2: Compliance Data On-Chain

• Medical Data Sharing: Hospitals can verify that patient test results meet treatment standards without exposing data.

• Supply Chain Traceability: Suppliers can prove raw material compliance while protecting trade secrets.

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Security Enhancement Mechanisms

Five-Layer Protection System

• Circuit Security Audit: Conducts formal verification of zk circuits.

• Node Reputation Pruning: Dynamically adjusts validator node weights based on reputation.

• Anomaly Circuit Breaker: Automatically suspends services if data deviation exceeds a threshold.

• Proof Retrospective System: Permanently stores all proofs for audit purposes.

• Quantum Resistance: Adopts STARK-based quantum-resistant algorithms for disaster recovery.

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Performance Optimization Solutions

Proof Generation Acceleration

• GPU Acceleration: Supports CUDA-accelerated zk proof generation.

• Batch Proofing: Merges multiple requests into a single proof to enhance efficiency.

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Resource Graded Scheduling

Implements tiered scheduling for optimal resource utilization.

Service Level	Response Time	Proof Complexity	Applicable Scenarios
Platinum	<1s	Million-gate Circuit	High-Frequency Trading
Gold	3s	Hundred-thousand-gate Circuit	IoT Data
Standard	10s	Ten-thousand-gate Circuit	Regular Commercial Applications

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Conclusion

By deeply integrating zero-knowledge proofs with the Cosmos ecosystem, this system establishes the first oracle infrastructure supporting full privacy and cross-chain verification. Developers can retain their familiar EVM development paradigms while benefiting from quantum-safe privacy protection capabilities.

This innovation opens up new frontiers for Web3 applications in finance, healthcare, IoT, and other sensitive domains.