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Zero-Knowledge Proof in NuLink

Pawn, Rookie, Zhuan Cheng

TL;DR

The paper addresses privacy and trust in NuLink's decentralized data services by leveraging zero-knowledge proofs across storage, computation, and trading. It surveys ZKP foundations, including NP-language proofs, completeness, soundness, and zero-knowledge, and discusses practical SNARK families (Groth16, PLONK) and polynomial commitments in CRS-based and universal CRS settings. The authors propose concrete ZKP-based mechanisms for proof of storage (PoRep/PoSt), computation verification, and transaction privacy, mapping them onto NuLink's IPFS/Filecoin storage, FHE-enabled computation, and privacy-preserving trading. The work outlines future directions toward faster prover performance, zk-rollups, and broader transaction capabilities to scale privacy-centric Web3 applications.

Abstract

NuLink provides privacy-preserving technology for decentralized applications via APIs. Users can securely store its valuable data, trade with others and so on. To ensure the privacy and security of service provided by NuLink, (zero-knowledge) proof systems are necessary. Zero-knowledge proof systems allow the prover to make the verifier believe that a certain conclusion is correct without providing any useful information to the verifier. In NuLink, we are going to use (zero-knowledge) proof system in the following three methods: 1. Users store their data through NuLink in a decentralized manner. To ensure that the storage clients are indeed storing the data, we employ proof of storage systems. In this system, users prepare certain challenges that can only be correctly answered by those who are actually storing the data. 2. Users have the option to outsource computations to NuLink. To verify the correctness of the computation results provided by the compute node, we require the node to provide a proof of correctness via SNARK systems. When sensitive parameters are used as inputs for computation, we utilize zk-SNARKs to prevent any potential leakage of these parameters. 3. Users may choose to trade their data through NuLink. To confirm that the buyer has sufficient digital funds and the seller possesses the desired data, both parties can provide a proof via zk-SNARKs. This builds confidence and prevents cheating during transactions. Using zero-knowledge proof systems, we can ensure that all nodes in NuLink behaves honestly and avoid cheating in the whole system.

Zero-Knowledge Proof in NuLink

TL;DR

The paper addresses privacy and trust in NuLink's decentralized data services by leveraging zero-knowledge proofs across storage, computation, and trading. It surveys ZKP foundations, including NP-language proofs, completeness, soundness, and zero-knowledge, and discusses practical SNARK families (Groth16, PLONK) and polynomial commitments in CRS-based and universal CRS settings. The authors propose concrete ZKP-based mechanisms for proof of storage (PoRep/PoSt), computation verification, and transaction privacy, mapping them onto NuLink's IPFS/Filecoin storage, FHE-enabled computation, and privacy-preserving trading. The work outlines future directions toward faster prover performance, zk-rollups, and broader transaction capabilities to scale privacy-centric Web3 applications.

Abstract

NuLink provides privacy-preserving technology for decentralized applications via APIs. Users can securely store its valuable data, trade with others and so on. To ensure the privacy and security of service provided by NuLink, (zero-knowledge) proof systems are necessary. Zero-knowledge proof systems allow the prover to make the verifier believe that a certain conclusion is correct without providing any useful information to the verifier. In NuLink, we are going to use (zero-knowledge) proof system in the following three methods: 1. Users store their data through NuLink in a decentralized manner. To ensure that the storage clients are indeed storing the data, we employ proof of storage systems. In this system, users prepare certain challenges that can only be correctly answered by those who are actually storing the data. 2. Users have the option to outsource computations to NuLink. To verify the correctness of the computation results provided by the compute node, we require the node to provide a proof of correctness via SNARK systems. When sensitive parameters are used as inputs for computation, we utilize zk-SNARKs to prevent any potential leakage of these parameters. 3. Users may choose to trade their data through NuLink. To confirm that the buyer has sufficient digital funds and the seller possesses the desired data, both parties can provide a proof via zk-SNARKs. This builds confidence and prevents cheating during transactions. Using zero-knowledge proof systems, we can ensure that all nodes in NuLink behaves honestly and avoid cheating in the whole system.
Paper Structure (8 sections, 1 equation)

This paper contains 8 sections, 1 equation.

Theorems & Definitions (3)

  • definition thmcounterdefinition: Proof Protocol
  • definition thmcounterdefinition: Zero-Knowledge
  • definition thmcounterdefinition: Non-Interactive Zero-Knowledge Argument Scheme