CN-122001560-A - Trusted data space data interaction method based on blockchain predictor

CN122001560ACN 122001560 ACN122001560 ACN 122001560ACN-122001560-A

Abstract

The invention provides a reliable data space data interaction method based on a blockchain predictor, which relates to the technical field of blockchains and comprises the steps of receiving a data packet sent by a data provider, carrying out BLS aggregate signature verification on BLS signature data, recalculating a local promise value and a vector promise value to compare to confirm content integrity, judging data access only after double verification passes, responding to a data request of a data using party on a target data item, acquiring original data, a digital signature and Merkle member evidence corresponding to the target data item based on MERKLE DAG data structures, generating a verifiable object and returning to the data using party. The invention introduces the blockchain predictor as a trusted data space access data connector, and realizes the verifiable access and traceable circulation of data resources by constructing a trusted bridging link between the data resource-blockchain predictor data connector-blockchain ledger-trusted data space.

Inventors

GE CHUNPENG
JIANG YALI
LI YANBIN
JIANG HAN

Assignees

山东大学

Dates

Publication Date: 20260508
Application Date: 20260407

Claims (10)

1. A method of trusted data space data interaction based on a blockchain predictor, comprising: Receiving a data packet sent by a data provider, wherein the data packet comprises an original data block subjected to block processing, a vector commitment value generated based on KZG vector commitment algorithm and corresponding BLS signature data; Performing BLS aggregate signature verification on the BLS signature data to confirm identity authenticity, and recalculating a local promise value and a vector promise value based on a received original data block to compare to confirm content integrity, and judging data admission only after double verification is passed; Analyzing the data block passing the admission verification into independent data items and distributing a global unique index, constructing MERKLE DAG a data structure based on a forced position binding method, and submitting the generated Merkle root Ha Xiji signature to a blockchain network for evidence storage anchoring; and responding to a data request of a data using party for a target data item, acquiring original data, a digital signature and Merkle membership certification corresponding to the target data item based on the MERKLE DAG data structure, generating a verifiable object and returning to the data using party.
2. The method for trusted data space data interaction based on a blockchain predictor as in claim 1, wherein the method for enforcing position binding constructs MERKLE DAG a data structure based on the method for enforcing position binding, comprising: Performing cascade coding on the data item and the global unique index thereof, and then calculating a hash value to obtain forced position binding leaf node hash; and performing hash operation iteratively from bottom to top to construct MERKLE DAG data structures with position sensitive characteristics.
3. The method for trusted data space data interaction based on a blockchain predictor of claim 1, wherein the submitting the generated Merkle root Ha Xiji root signature to a blockchain network for forensic anchoring further comprises the blockchain predictor data connector signing the Merkle root hash with a local private key to generate the root signature.
4. The method for trusted data space data interaction based on a blockchain predictor as in claim 1, wherein the performing BLS aggregate signature verification on the BLS signature data specifically comprises: And carrying out batch verification on BLS signatures of a plurality of data blocks based on bilinear pairing operation, and confirming the source authenticity of batch data at one time.
5. The method for trusted data space data interaction based on a blockchain predictor of claim 1, wherein the recalculating the local commitment value based on the received original data block is compared with the vector commitment value, specifically comprising reconstructing the original data block into a polynomial using the same Lagrangian interpolation as the data provider, calculating the local commitment value based on the common parameter, and determining whether the local commitment value is equal to the received vector commitment value.
6. A method of trusted data space data interaction based on a blockchain predictor, for a data provider, comprising: The method comprises the steps of obtaining original data to be published, and performing block processing on the original data to obtain a plurality of data blocks; For each data block, generating a vector commitment value corresponding to the data block based on KZG vector commitment algorithm, and performing BLS signature on the vector commitment value by using a private key to obtain signature data; And sending the data packet containing the data block, the vector promise value and the signature data to a blockchain predictor data connector so that the blockchain predictor data connector performs double verification on the data packet, constructs MERKLE DAG a data structure and anchors the uplink.
7. The method for trusted data space data interaction based on a blockchain predictor as in claim 6, wherein the generating the vector commitment value corresponding to the data block based on KZG vector commitment algorithm specifically comprises: data block interpolation method using Lagrange Constructed as polynomials Satisfy at specific interpolation point There is at , Is the first in the data block A data item; Public parameters generated based on trusted settings Calculating global commitment value , wherein, Privacy door parameters generated and destroyed for the trusted setup stage.
8. The method for trusted data space data interaction based on a blockchain predictor as in claim 6, wherein the performing BLS signing on the vector commitment value with a private key to obtain signed data comprises: using a private key of a data provider Vector promise value BLS signature is performed to generate signature value ; The signature value and the vector promise value form a bilinear pairing verification relationship, and the two-way pairing verification relationship meets the following requirements Wherein Is a public key.
9. The method of claim 6, wherein the sending the data packet including the data block, the vector commitment value and the signature data to the blockchain predictor data connector comprises: Building data quads As a data packet; Uploading the data packet to a storage end, and triggering a blockchain predictor data connector to perform BLS aggregation signature verification and KZG vector promise consistency verification on the data packet.
10. The trusted data space data interaction method based on the blockchain predictor is characterized by comprising the following steps of: Sending a data access request to a blockchain predictor data connector, wherein the data access request comprises a global unique index of a target data item; receiving a verifiable object returned by the blockchain predictor data connector, wherein the verifiable object comprises a target data item, a corresponding Merkle membership certificate and a root signature; Verifying whether the target data item is consistent with the root hash anchored on the blockchain based on the Merkle membership certificate and the root signature, and synchronously verifying the validity of the root signature through the public key to confirm the source of the trust anchor point; And after passing the verification, performing local calculation or business processing by using the target data item.

Description

Trusted data space data interaction method based on blockchain predictor Technical Field The invention relates to the technical field of blockchain, in particular to a trusted data space data interaction method based on a blockchain predictor. Background In the technical architecture of the trusted data space, a data connector is a core technical component, and from the aspect of functional positioning, the data connector is deployed at the edge side of a data provider and a data consumer and is responsible for executing key tasks such as identity authentication, resource catalog release, use control strategy negotiation, data format conversion, data transmission encryption and the like, and is a necessary channel for connecting a private domain of a participant with a public data flow domain, and is also an execution carrier for realizing advanced data application scenes such as data availability invisible, use controllable metering and the like. However, the existing data connector still faces significant technical challenges in practical application, namely, firstly, the authenticity of a data source is difficult to guarantee, in an open network environment, a global authoritative traceability system is lacking, data nodes are easy to suffer identity forging and malicious displacement, so that access data is trapped in a source non-traceable dilemma, secondly, the integrity of a data transmission process is difficult to verify, the data is inevitably exposed to an un-trusted environment in cross-system long-chain transmission, security risks such as tampering, losing and replay attack are extremely easy to derive, and thirdly, a trusted evidence storage mechanism of interaction behavior is lost, while the traditional connector has policy execution capability, a means for carrying out non-tamperable evidence storage on key operations (such as data right, contract achievement and delivery evidence) is lacking, so that effective traceability is difficult in disputes. Therefore, the data interaction method based on the existing data connector cannot establish an end-to-end trusted chain from a data source end, so that a fundamental technical fault exists in the interaction process at the authenticity verification and behavior audit level, and the rigidity requirement of high-value data circulation scenes on verifiable trust is difficult to meet. Disclosure of Invention In order to solve the problems, the invention provides a reliable data space data interaction method based on a blockchain predictor, which introduces the blockchain predictor as a reliable data space access data connector, and realizes verifiable access and traceable circulation of data resources by constructing a reliable bridging link between a data resource-blockchain predictor data connector and a blockchain ledger-a reliable data space. According to some embodiments, the present invention employs the following technical solutions: a trusted data space data interaction method based on a blockchain predictor for a blockchain predictor data connector, comprising: Receiving a data packet sent by a data provider, wherein the data packet comprises an original data block subjected to block processing, a vector commitment value generated based on KZG vector commitment algorithm and corresponding BLS signature data; Performing BLS aggregate signature verification on the BLS signature data to confirm identity authenticity, and recalculating a local promise value and a vector promise value based on a received original data block to compare to confirm content integrity, and judging data admission only after double verification is passed; Analyzing the data block passing the admission verification into independent data items and distributing a global unique index, constructing MERKLE DAG a data structure based on a forced position binding method, and submitting the generated Merkle root Ha Xiji signature to a blockchain network for evidence storage anchoring; and responding to a data request of a data using party for a target data item, acquiring original data, a digital signature and Merkle membership certification corresponding to the target data item based on the MERKLE DAG data structure, generating a verifiable object and returning to the data using party. According to some embodiments, the present invention employs the following technical solutions: a trusted data space data interaction method based on a blockchain predictor for a data provider, comprising: The method comprises the steps of obtaining original data to be published, and performing block processing on the original data to obtain a plurality of data blocks; For each data block, generating a vector commitment value corresponding to the data block based on KZG vector commitment algorithm, and performing BLS signature on the vector commitment value by using a private key to obtain signature data; And sending the data packet containing the data block, the vector promise value and the s