zkcloud - Cloud-based service that allows you to create zero knowledge proofs on the cloud.

ANNEX B - Zero Knowledge Proofs for the Age Verification Solution - European Age Verification Solution

Zero-knowledge proofs (ZKPs) are cryptographic techniques that enable one party (the User) to prove to another party (the Relying Party) that a statement is true without disclosing any additional information beyond the statement’s validity. This allows the User to demonstrate knowledge without revealing the knowledge itself.

Decentralized Identity Verification using Zero-Knowledge Proofs: A Privacy-Preserving Authentication Framework

In the contemporary online interaction, digital iden- tity is central, but most systems follow a centralized provider like Google or Facebook. Although convenient, these models pose ma- jor risks to data breach, surveillance, and single point of failure. The proposed paper proposes a privacy-sensitive decentralized identity verification system that uses Zero-Knowledge Proofs (ZKPs) to allow users to make it through claims (e.g., age, citizen- ship, or enrollment) without any personal data being provided, thereby solving the challenges outlined in the paper. Our architecture integrates verifiable credentials, zero-knowledge-SNARKs and an issuer trust registry that is maintained on blockchain smart contracts to guarantee trustless verification and eliminate dependence on centralized authorities. Its system gives its users full control over credentials, allows reuse across applications, and does not expose data.A proof-of-concept implementation has shown the approach to be feasible with Circom and SnarkJS to generate proof, Solidity smart contracts to verify them, and a user interface implemented in React. Results of the evaluations showed that determination of the verification latency is low, the overhead to generate proofs is moderate, and no privacy leakage occurs. It can be used in potential applications such as education, e-governance, healthcare, finance, and online voting.

google/longfellow-zk

Implementation of the Google Zero-Knowledge library for Identity Protocols.

The limits of zero-knowledge for age-verification | Brave

ZKPs are often advanced as a technical remedy, promising privacy-preserving attestations of age or eligibility. Yet their deployment in practice exposes both conceptual and practical limits.

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ZKPROV: A Zero-Knowledge Approach to Dataset Provenance for Large Language Models

As large language models (LLMs) are used in sensitive fields, accurately verifying their computational provenance without disclosing their training datasets poses a significant challenge, particularly in regulated sectors such as healthcare, which have strict requirements for dataset use. Traditional approaches either incur substantial computational cost to fully verify the entire training process or leak unauthorized information to the verifier. Therefore, we introduce ZKPROV, a novel cryptographic framework allowing users to verify that the LLM's responses to their prompts are trained on datasets certified by the authorities that own them. Additionally, it ensures that the dataset's content is relevant to the users' queries without revealing sensitive information about the datasets or the model parameters. ZKPROV offers a unique balance between privacy and efficiency by binding training datasets, model parameters, and responses, while also attaching zero-knowledge proofs to the responses generated by the LLM to validate these claims. Our experimental results demonstrate sublinear scaling for generating and verifying these proofs, with end-to-end overhead under 3.3 seconds for models up to 8B parameters, presenting a practical solution for real-world applications. We also provide formal security guarantees, proving that our approach preserves dataset confidentiality while ensuring trustworthy dataset provenance.

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