Author: Zypher Network

With the rapid development of artificial intelligence, especially the widespread application of large language models (LLM), prompts have become key guiding information for AI-generated responses. These prompts are divided into user prompts and system prompts:

• User prompts: Queries provided by users.
• System prompts: Predefined by developers to establish the model's behavioral guidelines, tone, and contextual output.

The "Black Box Problem" of Prompts

However, in traditional LLM architectures, prompts—especially system prompts—are often hidden in a "black box." Users cannot see whether system prompts remain consistent across different interactions or if they are altered during the process. This black box nature leads to two main issues:

• Consistency Issue: If system prompts are modified during interactions, the model's output may deviate from expected behavior. Developers cannot guarantee that every call adheres to the expected prompts, and users cannot verify the consistency of the model's behavior.
• Privacy Issue: System prompts may contain highly sensitive business information, such as pricing strategies, risk control strategies, or proprietary algorithm logic. While developers do not wish to disclose this information, they still need a way to prove to users that this information has not been tampered with.

Proof of Prompt: A Zero-Knowledge Solution for Ensuring Reliability

Zypher's "Proof of Prompt" technology aims to address this challenge. By leveraging zero-knowledge proof (ZKP) technology, "Proof of Prompt" can verify whether system prompts remain consistent in each call without revealing their actual content. In other words, it provides developers and users with a mechanism to ensure that prompts have not been tampered with, significantly enhancing the reliability of LLM interactions while fully protecting privacy.

Technical Architecture of Proof of Prompt

The core implementation of "Proof of Prompt" is based on cryptographic commitments, serving as the foundation for verification:

1. Cryptographic Commitment: Developers generate a commitment value for the system prompts and publish it on-chain.
2. Zero-Knowledge Verification: Each time a user interacts with the LLM, the model generates a response along with a zero-knowledge proof to verify that the prompts used are consistent with the original commitment value.
3. On-Chain Verification: Smart contracts on the blockchain verify whether the zkProof and commitment value match, ensuring that the prompts have not been altered.

Recent Technological Advances of Proof of Prompt

In the implementation of "Proof of Prompt," the Transport Layer Security (TLS) protocol plays a crucial role. TLS is a standard protocol used to ensure the security of internet data transmission and supports various encryption algorithms. Understanding the characteristics of these algorithms helps to better comprehend Zypher's innovations in this field.

More detailed explanations have been provided regarding the application of ChaCha20 and AES in TLS. TLS typically uses authenticated encryption with associated data (AEAD) algorithms to ensure the integrity and authenticity of encrypted data. This means that ChaCha20 and AES are often used in conjunction with other authenticated encryption mechanisms, such as ChaCha20-Poly1305 or AES-GCM.

Technical Advantages of ChaCha20-Poly1305 and AES-GCM

ChaCha20-Poly1305: As an AEAD mode, ChaCha20-Poly1305 combines the stream encryption efficiency of ChaCha20 with the message authentication capability of Poly1305. It not only provides fast encryption processing but also effectively prevents data tampering. This makes it particularly suitable for environments with limited hardware acceleration capabilities, such as embedded devices or mobile platforms.

AES-GCM: AES-GCM (Galois/Counter Mode) is an authenticated encryption mode based on block encryption. By combining efficient block encryption with the Galois authentication mechanism, AES-GCM achieves high performance in hardware-accelerated environments, making it an ideal choice for server-side applications and data centers.

Technological Innovations of Proof of Prompt

In the "Proof of Prompt" framework, Zypher not only supports the two mainstream encryption algorithms, ChaCha20 and AES, but also fully leverages their respective advantages in zkCircuits. The circuit footprint of ChaCha20 is smaller, making it more suitable for applications that require reduced circuit complexity. On the other hand, AES benefits from hardware acceleration and widespread industry adoption, making it a reliable choice for high-performance environments.

By integrating these mainstream TLS encryption algorithms into the zero-knowledge proof (ZKP) environment, Zypher has achieved several key breakthroughs:

1. Circuit Size Reduction: Zypher's zkCircuit design reduces circuit size by an order of magnitude, significantly lowering computational costs and resource consumption compared to traditional ZKP methods.
2. Improved Verification Efficiency: By combining the authenticated encryption modes of AES and ChaCha20, "Proof of Prompt" enhances the efficiency of the verification process, ensuring faster response times and improved user experience.
3. Enhanced Encryption Flexibility: Whether using AES-GCM on server-side applications or ChaCha20-Poly1305 on mobile and embedded devices, "Proof of Prompt" can flexibly adapt to different hardware conditions and performance requirements.

Zypher's innovation lies in integrating AES and ChaCha20 into zero-knowledge circuits (zkCircuits). Since ChaCha20 requires fewer circuit resources than AES, Zypher effectively supports both algorithms. This technological breakthrough significantly reduces the complexity of zkCircuits while maintaining the efficiency and reliability of the TLS environment. By optimizing circuit design, Zypher has successfully elevated the status of these encryption algorithms within the ZKP framework, making them a core driving force behind the practical implementation of "Proof of Prompt."

Industry Applications of Proof of Prompt

1. On-Chain Finance

In the decentralized finance (DeFi) space, many protocols rely on complex algorithms to ensure liquidity, collateral security, and overall market stability. "Proof of Prompt" provides a powerful verification mechanism, bringing transparency and credibility to various on-chain financial scenarios:

• Decentralized Exchanges (DEX): Many DEXs use automated market maker (AMM) models to provide liquidity. "Proof of Prompt" can verify whether AMM price curves, fee distributions, and revenue-sharing calculations are consistent with predefined algorithms. This can prevent potential risks such as price manipulation due to code changes or external attacks.
• Synthetic Asset and Stablecoin Protocols: Protocols issuing synthetic assets and stablecoins often rely on collateral-based mechanisms. "Proof of Prompt" ensures that collateral ratio calculations and liquidation rules strictly adhere to the originally defined models. This increases user trust and helps reduce market volatility.
• Lending and Liquidation Platforms: On-chain lending protocols maintain system stability through strict liquidation rules and interest rate adjustments. "Proof of Prompt" verifies that these rules remain unchanged, ensuring a secure environment for both users and institutions to safely engage in lending activities.

2. Off-Chain Finance (Traditional Finance)

In traditional financial institutions, "Proof of Prompt" offers a new way to enhance transparency and build customer trust:

• Enhanced Trust in Pricing Models: Pricing strategies in traditional finance (e.g., loan rates, foreign exchange rates) often rely on internal models. Since the transparency of these models directly affects customer trust, "Proof of Prompt" can verify that pricing models consistently adhere to predefined rules, ensuring they have not been altered due to internal operations or external interference.
• Verification of Risk Control Models: Risk management models—including credit scoring and stress testing—are crucial for financial decision-making. "Proof of Prompt" enables institutions to demonstrate to customers, partners, and regulators that their risk assessment algorithms remain unchanged and have not been manipulated or bypassed.
• Transparency in Payments and Settlements: In cross-border payments and complex settlement processes, "Proof of Prompt" can verify the transparency and consistency of transaction fees and commission calculations. This reduces uncertainty for international clients and enhances the competitiveness of financial institutions.

3. Web3 Gaming and NFT Ecosystems

"Proof of Prompt" can also serve as a security mechanism for blockchain games and digital collectibles platforms:

• On-Chain Game Rules Verification: In blockchain-based games, "Proof of Prompt" can verify the consistency of in-game reward distribution rules, economic model stability, and smart contract logic. This ensures fairness and transparency within the gaming ecosystem.
• NFT Minting and Distribution: On NFT platforms, developers can use "Proof of Prompt" to verify that the original metadata and minting logic of NFTs have not been tampered with, thereby increasing buyer confidence in the platform.
• Cross-Game Economic Interaction: For ecosystems supporting cross-game assets, "Proof of Prompt" ensures that asset conversion rules and usage conditions remain unchanged, fostering trust and stability in the cross-game economy.

4. DAO Governance and Community Management

“Proof of Prompt” is also applicable to decentralized autonomous organization (DAO) governance:

• Verification of Governance Proposals: DAOs can use “Proof of Prompt” to ensure that approved proposals adhere to predefined rules during execution, preventing disputes arising from tampering with governance code.
• Transparency in Fund Allocation: By verifying fund allocation rules and incentive mechanisms, “Proof of Prompt” ensures that DAO fund distribution remains fair and transparent, thereby increasing community trust.
• Cross-Chain Governance Interoperability: In multi-chain ecosystems, “Proof of Prompt” can verify the logical consistency of governance mechanisms across different chains, facilitating transparent cross-chain collaboration and community governance.

5. Decentralized Storage and Content Verification

In the field of decentralized storage and content distribution, “Proof of Prompt” offers the following applications:

• Integrity Verification of Stored Data: “Proof of Prompt” ensures that data stored on decentralized networks has not been tampered with and remains consistent with the developer's original specifications.
• Transparency of Content Access Rules: For content that requires specific access conditions (e.g., paid subscriptions or permission-based documents), “Proof of Prompt” can verify that access rules remain unchanged.
• Trustworthy Decentralized CDN Verification: In distributed content delivery networks (CDN), “Proof of Prompt” verifies that the content provided by CDN nodes matches the original commitment value, thereby enhancing user trust in the quality of content distribution.

Milestones in Promoting Industry Trust

Zypher's “Proof of Prompt” technology combines AES and ChaCha20 (two mature TLS encryption algorithms) with zero-knowledge proofs (ZKP) to create an efficient and reliable verification framework. This innovation not only enhances technical performance but also reduces development costs and lowers the adoption threshold. “Proof of Prompt” not only addresses trust issues in existing LLM systems but also sets a new benchmark for trust in broader industry applications.

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