CN114978531A - Deep learning-oriented data credible traceability marking method and system - Google Patents
Deep learning-oriented data credible traceability marking method and system Download PDFInfo
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- CN114978531A CN114978531A CN202210512826.0A CN202210512826A CN114978531A CN 114978531 A CN114978531 A CN 114978531A CN 202210512826 A CN202210512826 A CN 202210512826A CN 114978531 A CN114978531 A CN 114978531A
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- 238000000034 method Methods 0.000 title claims abstract description 22
- 238000013135 deep learning Methods 0.000 claims abstract description 26
- 238000012804 iterative process Methods 0.000 claims abstract description 13
- 238000012795 verification Methods 0.000 claims description 10
- 238000010276 construction Methods 0.000 claims description 2
- 238000005516 engineering process Methods 0.000 description 2
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
- H04L9/3247—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials involving digital signatures
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
- H04L9/3263—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials involving certificates, e.g. public key certificate [PKC] or attribute certificate [AC]; Public key infrastructure [PKI] arrangements
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L2463/00—Additional details relating to network architectures or network communication protocols for network security covered by H04L63/00
- H04L2463/146—Tracing the source of attacks
Abstract
The invention relates to a deep learning-oriented data credibility tracing marking method and system, wherein the method comprises the following steps: receiving data to be processed; performing iterative processing on the data to be processed and performing digital signature on the processing result data by using a digital certificate; and establishing a digital signature chain of an iterative process from the source data to the final processing result data based on the obtained plurality of digital signatures. The invention adopts the credible traceability chain formed by the digital signature to finish the credible traceability of the data processing iterative process, can avoid the performance loss caused by adopting the distributed block chain scheme, and is more suitable for the application scene of the rapid iterative processing of the data required by the deep learning.
Description
Technical Field
The invention relates to the technical field of big data, in particular to a deep learning-oriented data credible traceability marking method and system.
Background
With the maturity of the blockchain technology, the blockchain technology is used as a solution of a general digital evidence chain, which can be used for data credibility tracing of deep learning, and although registration of the blockchain can ensure credibility of data iteration, a drawback that a historical block needs to be traversed at a slow retrieval speed exists during tracing.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a data credible tracing marking method and system for deep learning, avoid performance loss caused by adopting a distributed block chain scheme, and are more suitable for an application scene of rapid iterative processing of data required by deep learning.
The technical scheme adopted by the invention for solving the technical problems is as follows: the deep learning-oriented data credibility tracing marking method comprises the following steps:
receiving data to be processed;
performing iterative processing on the data to be processed and performing digital signature on the processing result data by using a digital certificate;
and establishing a digital signature chain of an iterative process from the source data to the final processing result data based on the obtained plurality of digital signatures.
After receiving the data to be processed, the method also comprises the step of verifying the digital signature attached to the data to be processed so as to confirm the credibility of data input.
Before receiving the data to be processed, the method also comprises the step of receiving the digital certificate facing deep learning and issued by a central digital certificate authority.
The iterative processing of the data to be processed and the digital signature of the processing result data by using the digital certificate are specifically as follows:
carrying out iterative processing on the data to be processed to obtain processing result data;
merging the digital signature of the data to be processed and the processing result data into basic information;
digitally signing the base information using the digital certificate.
The data credibility tracing marking method facing the deep learning further comprises the following steps: and sequentially verifying through the digital signature chain to trace and confirm the credibility of the whole data processing iteration process.
The technical scheme adopted by the invention for solving the technical problems is as follows: the deep learning oriented data credibility tracing marking system comprises:
the first receiving module is used for receiving data to be processed;
the processing signature module is used for carrying out iterative processing on the data to be processed to obtain processing result data and carrying out digital signature on the processing result data by using a digital certificate;
and the digital signature chain construction module is used for establishing a digital signature chain of an iterative process from the source data to the final processing result data based on the obtained plurality of digital signatures.
The data credibility tracing marking system facing the deep learning further comprises: and the verification module is used for verifying the digital signature attached to the data to be processed so as to confirm the credibility of the data input.
The deep learning oriented data credible traceability marking system further comprises a second receiving module, wherein the second receiving module is used for receiving the deep learning oriented digital certificate issued by the central digital certificate authority.
The processing signature module comprises:
the processing unit is used for carrying out iterative processing on the data to be processed to obtain processing result data;
the merging unit is used for merging the digital signature of the data to be processed and the processing result data into basic information;
and the signature unit is used for digitally signing the basic information by using the digital certificate.
The data credibility tracing marking system facing the deep learning further comprises: and the verification module is used for sequentially verifying through the digital signature chain so as to trace and confirm the credibility of the whole data processing iteration process.
Advantageous effects
Due to the adoption of the technical scheme, compared with the prior art, the invention has the following advantages and positive effects: the invention adopts the credible traceability chain formed by the digital signature to finish the credible traceability of the data processing iterative process, can avoid the performance loss caused by adopting the distributed block chain scheme, and is more suitable for the application scene of the rapid iterative processing of the data required by the deep learning. According to the invention, the digital signature is carried out by attaching the digital signature of the input data and the content of the output data together, so that a complete digital signature chain from the input data to the output data can be formed, and the rapid verification can be completed by traversing the digital signature chain during the trusted traceability verification.
Drawings
Fig. 1 is a flowchart of a first embodiment of the present invention.
Detailed Description
The invention will be further illustrated with reference to the following specific examples. It should be understood that these examples are for illustrative purposes only and are not intended to limit the scope of the present invention. Further, it should be understood that various changes or modifications of the present invention may be made by those skilled in the art after reading the teaching of the present invention, and such equivalents may fall within the scope of the present invention as defined in the appended claims.
The first embodiment of the invention relates to a deep learning-oriented data credibility tracing marking method, which comprises the following steps: receiving data to be processed; performing iterative processing on the data to be processed and performing digital signature on the processing result data by using a digital certificate; and establishing a digital signature chain of an iterative process from the source data to the final processing result data based on the obtained plurality of digital signatures. As shown in fig. 1, specifically:
step 1, a central digital certificate authority issues digital certificates which are required to be used by all data processing modules facing deep learning. That is, after this step, each data processing module can obtain a respective dedicated digital certificate.
And 2, the data processing module receives the data to be processed and verifies the digital signature of the data to be processed after receiving the data to be processed so as to confirm the input credibility of the data to be processed.
And 3, the data processing module performs iterative processing on the input data and performs digital signature on the processing result data by using a digital certificate of the data processing module. In this step, first, iteration processing is performed on the data to be processed to obtain processing result data, and then, when digital signature is performed, the method includes step 3a, the digital signature of the data to be processed and the processing result data are attached together to obtain basic information needing digital signature; step 3b, the data processing module digitally signs using the digital certificate issued by the central digital certificate authority.
And 4, establishing a digital signature chain of an iterative process from the source data to the final processing result data through each data processing module based on the processing flow of the step 3.
And step 5, verifying the sequence of the digital signature chain to trace and confirm the credibility of the whole data processing iterative process.
As can be easily found, the invention adopts the credible tracing chain formed by the digital signature to complete the credible tracing of the data processing iterative process, can avoid the performance loss caused by adopting the distributed block chain scheme, and is more suitable for the application scene of the rapid iterative processing of the data required by the deep learning. According to the invention, the digital signature is carried out by attaching the digital signature of the input data and the content of the output data together, so that a complete digital signature chain from the input data to the output data can be formed, and the rapid verification can be completed by traversing the digital signature chain during the trusted traceability verification.
The second embodiment of the invention relates to a deep learning-oriented data credibility traceability marking system, which comprises: the first receiving module is used for receiving data to be processed; the processing signature module is used for carrying out iterative processing on the data to be processed to obtain processing result data and carrying out digital signature on the processing result data by using a digital certificate; and the digital signature chain building module is used for building a digital signature chain of an iterative process from the source data to the final processing result data based on the obtained plurality of digital signatures.
The data credibility tracing marking system facing the deep learning further comprises: and the verification module is used for verifying the digital signature attached to the data to be processed so as to confirm the credibility of the data input.
The deep learning oriented data credible traceability marking system further comprises a second receiving module, wherein the second receiving module is used for receiving the deep learning oriented digital certificate issued by the central digital certificate authority.
The processing signature module comprises: the processing unit is used for carrying out iterative processing on the data to be processed to obtain processing result data; the merging unit is used for merging the digital signature of the data to be processed and the processing result data into basic information; and the signature unit is used for digitally signing the basic information by using the digital certificate.
The data credibility tracing marking system facing the deep learning further comprises: and the verification module is used for sequentially verifying through the digital signature chain so as to trace and confirm the credibility of the whole data processing iterative process.
Claims (10)
1. A deep learning-oriented data credibility tracing marking method is characterized by comprising the following steps:
receiving data to be processed;
performing iterative processing on the data to be processed and performing digital signature on the processing result data by using a digital certificate;
and establishing a digital signature chain of an iterative process from the source data to the final processing result data based on the obtained plurality of digital signatures.
2. The deep learning-oriented data credibility traceability marking method as claimed in claim 1, wherein after receiving the data to be processed, the method further comprises checking a digital signature attached to the data to be processed to confirm the credibility of the data input.
3. The deep learning oriented data credibility traceability marking method as claimed in claim 1, further comprising receiving the deep learning oriented digital certificate issued by a central digital certificate authority before receiving the data to be processed.
4. The deep learning-oriented data credible traceability marking method according to claim 1, wherein the iterative processing of the data to be processed and the digital signature of the processing result data by using the digital certificate specifically comprise:
carrying out iterative processing on the data to be processed to obtain processing result data;
merging the digital signature of the data to be processed and the processing result data into basic information;
digitally signing the base information using the digital certificate.
5. The deep learning-oriented data credibility traceability marking method according to claim 1, further comprising:
and sequentially verifying through the digital signature chain to trace and confirm the credibility of the whole data processing iteration process.
6. A deep learning oriented data credible traceability marking system is characterized by comprising:
the first receiving module is used for receiving data to be processed;
the processing signature module is used for carrying out iterative processing on the data to be processed to obtain processing result data and carrying out digital signature on the processing result data by using a digital certificate;
and the digital signature chain construction module is used for establishing a digital signature chain of an iterative process from the source data to the final processing result data based on the obtained plurality of digital signatures.
7. The deep learning oriented data credible traceability marking system as claimed in claim 6, further comprising:
and the verification module is used for verifying the digital signature attached to the data to be processed so as to confirm the credibility of the data input.
8. The deep learning oriented data trust traceability marking system of claim 6, further comprising a second receiving module for receiving the deep learning oriented digital certificate issued by a central digital certificate authority.
9. The deep learning oriented data credible traceability marking system of claim 6, wherein the processing signature module comprises:
the processing unit is used for carrying out iterative processing on the data to be processed to obtain processing result data;
the merging unit is used for merging the digital signature of the data to be processed and the processing result data into basic information; and the signature unit is used for digitally signing the basic information by using the digital certificate.
10. The deep learning oriented data credible traceability marking system as claimed in claim 6, further comprising:
and the verification module is used for sequentially verifying through the digital signature chain so as to trace and confirm the credibility of the whole data processing iteration process.
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