CN108881204A - Secret protection cluster data mining method, electronic equipment, storage medium and system - Google Patents
Secret protection cluster data mining method, electronic equipment, storage medium and system Download PDFInfo
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- CN108881204A CN108881204A CN201810589541.0A CN201810589541A CN108881204A CN 108881204 A CN108881204 A CN 108881204A CN 201810589541 A CN201810589541 A CN 201810589541A CN 108881204 A CN108881204 A CN 108881204A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
- H04L63/0407—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the identity of one or more communicating identities is hidden
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
- H04L63/0428—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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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
- H04L9/008—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols involving homomorphic encryption
-
- 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
- H04L9/08—Key distribution or management, e.g. generation, sharing or updating, of cryptographic keys or passwords
- H04L9/0861—Generation of secret information including derivation or calculation of cryptographic keys or passwords
- H04L9/0869—Generation of secret information including derivation or calculation of cryptographic keys or passwords involving random numbers or seeds
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- Engineering & Computer Science (AREA)
- Computer Security & Cryptography (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Computer Hardware Design (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The present invention provides secret protection cluster data mining method, including step：Key is generated, high-quality base, random integers matrix, open parameter is generated, elementary transformation is carried out to high-quality base and random integers matrix, generate base inferior, be stored in local using high-quality base as private key, be committed to cloud service provider using base inferior as public key；Encryption data generates ciphertext by public key encryption plaintext multidimensional data, and ciphertext and open parameter are sent to cloud service provider；Mining data, cloud service provider call ciphertext central point computational algorithm and ciphertext to carry out data mining, returned data Result to ciphertext apart from computational algorithm；Ciphertext data is decrypted data mining results using public key and private key, generates plaintext Result.The invention further relates to a kind of electronic equipment, storage medium, secret protection cluster data mining systems.The present invention has very high safety, effectively maintains the accuracy of distance between ciphertext data.
Description
Technical field
The present invention relates to data mining technology field more particularly to secret protection cluster data mining method, electronic equipment,
Storage medium and system.
Background technique
With the development of cloud computing and universal, user increasingly tends to store data on cloud, rents cloud computing clothes
The abundant calculating and storage resource that business center provides can provide data analysis service more efficiently, professional for user.So
And cloud service provider is often not fully credible, user is while enjoying cloud computing High-effective Service, privacy of user data
It is directly exposed to cloud service center, therefore, data-privacy safety problem just becomes the head that user is had to take into account that using cloud computing
Want problem.Available data mining algorithm does not account for the incredible situation of cloud service provider under cloud environment and is therefore badly in need of one kind
The secret protection cluster data mining method of Result accuracy can be improved under the precondition for guaranteeing privacy of user.
Summary of the invention
For overcome the deficiencies in the prior art, one of the objects of the present invention is to provide secret protection cluster data mining sides
Method solves available data mining algorithm and does not account for the incredible situation of cloud service provider under cloud environment, not can guarantee use
The problem of family privacy.
The present invention provides secret protection cluster data mining method, includes the following steps：
Key is generated, high-quality base, random integers matrix, open parameter are generated, to the high-quality base and the random integers
Matrix carries out elementary transformation, generates base inferior, is stored in local using the high-quality base as private key, using the base inferior as public affairs
Key is committed to cloud service provider；
Encryption data generates ciphertext by the public key encryption plaintext multidimensional data, by the ciphertext and the open ginseng
Number is sent to the cloud service provider；
Mining data, the cloud service provider call ciphertext central point computational algorithm and ciphertext apart from computational algorithm to institute
It states ciphertext and carries out data mining, returned data Result；
Ciphertext data is decrypted the data mining results using the public key and the private key, generates and digs in plain text
Dig result.
Further, the step encryption data further includes being added by homomorphic cryptography to the plaintext multidimensional data
It is close.
Further, the step mining data further includes the cloud service provider according to the cryptogram computation ciphertext number
The distance at strong point and cluster centre point, the distance of the ciphertext data point to the cluster centre point, distance is nearest
Ciphertext data point is divided into corresponding cluster.
Further, the step ciphertext data include using Babai algorithm calculate closest to the ciphertext most proximad
Amount generates the plaintext Result by public key described in the nearest vector sum.
A kind of electronic equipment, including：Processor；
Memory；And program, wherein described program is stored in the memory, and is configured to by processor
It executes, described program includes for executing above-mentioned secret protection cluster data mining method.
A kind of computer readable storage medium, is stored thereon with computer program, and the computer program is held by processor
The above-mentioned secret protection cluster data mining method of row.
Secret protection cluster data mining system, including：
Generate cipher key module：For generating high-quality base, random integers matrix, open parameter, to the high-quality base and described
Random integers matrix carries out elementary transformation, generates base inferior, local is stored in using the high-quality base as private key, by the poor quality
Base is committed to cloud service provider as public key；
Encryption data module：For ciphertext being generated, by the ciphertext and institute by the public key encryption plaintext multidimensional data
It states open parameter and is sent to the cloud service provider；
Mining data module：Ciphertext central point computational algorithm and ciphertext distance is called to calculate for the cloud service provider
Algorithm carries out data mining, returned data Result to the ciphertext；
Ciphertext data module：It is raw for the data mining results to be decrypted using the public key and the private key
At plaintext Result.
Further, the encryption data module further includes being added by homomorphic cryptography to the plaintext multidimensional data
It is close.
Further, the mining data module further includes the cloud service provider according to the cryptogram computation ciphertext number
The distance at strong point and cluster centre point, the distance of the ciphertext data point to the cluster centre point, distance is nearest
Ciphertext data point is divided into corresponding cluster.
Further, the ciphertext data module include using Babai algorithm calculate closest to the ciphertext most proximad
Amount generates the plaintext Result by public key described in the nearest vector sum.
Compared with prior art, the beneficial effects of the present invention are：
The present invention provides secret protection cluster data mining method, includes the following steps：Generate key, generate high-quality base,
Random integers matrix, open parameter, carry out elementary transformation to high-quality base and random integers matrix, base inferior are generated, by high-quality base
It is stored in local as private key, is committed to cloud service provider using base inferior as public key；Encryption data, it is bright by public key encryption
Literary multidimensional data generates ciphertext, and ciphertext and open parameter are sent to cloud service provider；Mining data, cloud service provider
Ciphertext central point computational algorithm and ciphertext is called to carry out data mining, returned data Result to ciphertext apart from computational algorithm；
Ciphertext data is decrypted data mining results using public key and private key, generates plaintext Result.The invention further relates to one
Kind electronic equipment, storage medium, secret protection cluster data mining system.The safe homomorphism that the present invention passes through building private data
Operation method, and the cloud ciphertext data clusters analysis data mining service for supporting secret protection is realized on this basis；
To protect user data privacy, user will be distributed to cloud service provider after data encryption, cloud service provider utilizes homomorphism
Encryption Algorithm realizes secret protection, but cloud service provider can not directly access user data and destroy privacy of user；The present invention
With very high safety, the accuracy of distance between ciphertext data is effectively maintained.
The above description is only an overview of the technical scheme of the present invention, in order to better understand the technical means of the present invention,
And can be implemented in accordance with the contents of the specification, the following is a detailed description of the preferred embodiments of the present invention and the accompanying drawings.
A specific embodiment of the invention is shown in detail by following embodiment and its attached drawing.
Detailed description of the invention
The drawings described herein are used to provide a further understanding of the present invention, constitutes part of this application, this hair
Bright illustrative embodiments and their description are used to explain the present invention, and are not constituted improper limitations of the present invention.In the accompanying drawings：
Fig. 1 is secret protection cluster data mining method flow diagram of the invention；
Fig. 2 is secret protection cluster data mining system structure diagram of the invention.
Specific embodiment
In the following, being described further in conjunction with attached drawing and specific embodiment to the present invention, it should be noted that not
Under the premise of conflicting, new implementation can be formed between various embodiments described below or between each technical characteristic in any combination
Example.
Secret protection cluster data mining method, as shown in Figure 1, including the following steps：
Key is generated, high-quality base K is generatedpri, random integers matrix U, open parameter p, to high-quality base and random integers matrix
Elementary transformation is carried out, base K inferior is generatedpub, it is stored in local using high-quality base as private key, is committed to using base inferior as public key
Cloud service provider；In the present embodiment, base K inferiorpubCalculation formula is as follows：
Kpub=UKpri=w1,w2..., wn
Encryption data generates ciphertext by public key encryption plaintext multidimensional data, and ciphertext and open parameter are sent to cloud clothes
Be engaged in provider；Preferably, step encryption data further includes being encrypted by homomorphic cryptography to plaintext multidimensional data.The present embodiment
In, plaintext multidimensional data stores in vector form, and for plaintext high dimension vector m, user uses KpubEncrypt m, the ciphertext of generation
Binary group (si,ti) consist of two parts, siClear data is restored for decrypting process；tiFor KpubThe cryptographic Hash of m is used for ciphertext
Auxiliary homomorphism calculating process under state.
Mining data, cloud service provider call ciphertext central point computational algorithm and ciphertext apart from computational algorithm to ciphertext into
Row data mining, returned data Result；Preferably, step mining data further includes cloud service provider according to cryptogram computation
The distance of ciphertext data point and cluster centre point, compares ciphertext data point to the distance of cluster centre point, will nearest close of distance
Literary data point is divided into corresponding cluster.In the present embodiment, for a pair of of cyphertext vector (s1,t1) and (s2,t2), ciphertext
Calculating process is as follows：
Ciphertext data is decrypted data mining results using public key and private key, generates plaintext Result.It is preferred that
, step ciphertext data includes the nearest vector calculated using Babai algorithm closest to ciphertext, raw by nearest vector sum public key
At plaintext Result.In the present embodiment, plaintext Result calculation formula is as follows：
V=round (SiKpri -1)·Kpri
Code=vKpub -1
A kind of electronic equipment, including：Processor；
Memory；And program, wherein program is stored in memory, and is configured to be executed by processor, journey
Sequence includes for executing above-mentioned secret protection cluster data mining method.
A kind of computer readable storage medium, is stored thereon with computer program, and computer program is executed by processor
State secret protection cluster data mining method.
Secret protection cluster data mining system, as shown in Fig. 2, including：
Generate cipher key module：For generating high-quality base Kpri, random integers matrix U, open parameter p, to high-quality base and random
INTEGER MATRICES carries out elementary transformation, generates base K inferiorpub, it is stored in local using high-quality base as private key, using base inferior as public affairs
Key is committed to cloud service provider；In the present embodiment, base K inferiorpubCalculation formula is as follows：
Kpub=UKpri=w1, w2..., wn
Encryption data module：For generating ciphertext by public key encryption plaintext multidimensional data, by ciphertext and open parameter hair
It send to cloud service provider；Preferably, encryption data module further includes being encrypted by homomorphic cryptography to plaintext multidimensional data.
In the present embodiment, plaintext multidimensional data stores in vector form, and for plaintext high dimension vector m, user uses KpubM is encrypted, it is raw
At ciphertext binary group (si,ti) consist of two parts, siClear data is restored for decrypting process；tiFor KpubThe cryptographic Hash of m,
For the auxiliary homomorphism calculating process under ciphertext state.
Mining data module：Call ciphertext central point computational algorithm and ciphertext apart from computational algorithm for cloud service provider
Data mining, returned data Result are carried out to ciphertext；Preferably, mining data module further include cloud service provider according to
The distance of cryptogram computation ciphertext data point and cluster centre point, compare ciphertext data point to cluster centre point distance, by distance
Nearest ciphertext data point is divided into corresponding cluster.In the present embodiment, for a pair of of cyphertext vector (s1,t1) and (s2,
t2), the calculating process of ciphertext is as follows：
Ciphertext data module：For data mining results to be decrypted using public key and private key, generates and excavate knot in plain text
Fruit.Preferably, ciphertext data module includes the nearest vector calculated using Babai algorithm closest to ciphertext, passes through nearest vector
Plaintext Result is generated with public key.In the present embodiment, plaintext Result calculation formula is as follows：
V=round (SiKpri -1)·Kpri
Code=vKpub -1
The present invention provides secret protection cluster data mining method, includes the following steps：Generate key, generate high-quality base,
Random integers matrix, open parameter, carry out elementary transformation to high-quality base and random integers matrix, base inferior are generated, by high-quality base
It is stored in local as private key, is committed to cloud service provider using base inferior as public key；Encryption data, it is bright by public key encryption
Literary multidimensional data generates ciphertext, and ciphertext and open parameter are sent to cloud service provider；Mining data, cloud service provider
Ciphertext central point computational algorithm and ciphertext is called to carry out data mining, returned data Result to ciphertext apart from computational algorithm；
Ciphertext data is decrypted data mining results using public key and private key, generates plaintext Result.The invention further relates to one
Kind electronic equipment, storage medium, secret protection cluster data mining system.The safe homomorphism that the present invention passes through building private data
Operation method, and the cloud ciphertext data clusters analysis data mining service for supporting secret protection is realized on this basis；
To protect user data privacy, user will be distributed to cloud service provider after data encryption, cloud service provider utilizes homomorphism
Encryption Algorithm realizes secret protection, but cloud service provider can not directly access user data and destroy privacy of user；The present invention
With very high safety, the accuracy of distance between ciphertext data is effectively maintained.
More than, only presently preferred embodiments of the present invention is not intended to limit the present invention in any form；All current rows
The those of ordinary skill of industry can be shown in by specification attached drawing and above and swimmingly implement the present invention；But all to be familiar with sheet special
The technical staff of industry without departing from the scope of the present invention, is made a little using disclosed above technology contents
The equivalent variations of variation, modification and evolution is equivalent embodiment of the invention；Meanwhile all substantial technologicals according to the present invention
The variation, modification and evolution etc. of any equivalent variations to the above embodiments, still fall within technical solution of the present invention
Within protection scope.
Claims (10)
1. secret protection cluster data mining method, it is characterised in that include the following steps：
Key is generated, high-quality base, random integers matrix, open parameter are generated, to the high-quality base and the random integers matrix
Elementary transformation is carried out, base inferior is generated, is stored in local using the high-quality base as private key, is mentioned using the base inferior as public key
It hands over to cloud service provider；
Encryption data generates ciphertext by the public key encryption plaintext multidimensional data, by the ciphertext and the open parameter hair
It send to the cloud service provider；
Mining data, the cloud service provider call ciphertext central point computational algorithm and ciphertext apart from computational algorithm to described close
Text carries out data mining, returned data Result；
Ciphertext data is decrypted the data mining results using the public key and the private key, generates and excavates knot in plain text
Fruit.
2. secret protection cluster data mining method as described in claim 1, it is characterised in that：The step encryption data is also
Including being encrypted by homomorphic cryptography to the plaintext multidimensional data.
3. secret protection cluster data mining method as claimed in claim 2, it is characterised in that：The step mining data is also
Including the cloud service provider according to the distance of the cryptogram computation ciphertext data point and cluster centre point, the ciphertext
Data point will be divided into corresponding cluster to the distance of the cluster centre point apart from nearest ciphertext data point.
4. secret protection cluster data mining method as described in claim 1, which is characterized in that the step decrypted data packet
The nearest vector for calculating the closest ciphertext using Babai algorithm is included, passes through public key described in the nearest vector sum and generates institute
State literary Result clearly.
5. a kind of electronic equipment, it is characterised in that including：Processor；
Memory；And program, wherein described program is stored in the memory, and is configured to be held by processor
Row, described program include requiring method described in 1-4 any one for perform claim.
6. a kind of computer readable storage medium, is stored thereon with computer program, it is characterised in that：The computer program quilt
Processor executes the method as described in claim 1-4 any one.
7. secret protection cluster data mining system, it is characterised in that including：
Generate cipher key module：For generating high-quality base, random integers matrix, open parameter, to the high-quality base and described random
INTEGER MATRICES carries out elementary transformation, generates base inferior, is stored in local using the high-quality base as private key, and the base inferior is made
Cloud service provider is committed to for public key；
Encryption data module：For ciphertext being generated, by the ciphertext and the public affairs by the public key encryption plaintext multidimensional data
It opens parameter and is sent to the cloud service provider；
Mining data module：Call ciphertext central point computational algorithm and ciphertext apart from computational algorithm for the cloud service provider
Data mining, returned data Result are carried out to the ciphertext；
Ciphertext data module：For the data mining results to be decrypted using the public key and the private key, generate bright
Literary Result.
8. secret protection cluster data mining system as claimed in claim 7, it is characterised in that：The encryption data module is also
Including being encrypted by homomorphic cryptography to the plaintext multidimensional data.
9. secret protection cluster data mining system as claimed in claim 8, it is characterised in that：The mining data module is also
Including the cloud service provider according to the distance of the cryptogram computation ciphertext data point and cluster centre point, the ciphertext
Data point will be divided into corresponding cluster to the distance of the cluster centre point apart from nearest ciphertext data point.
10. secret protection cluster data mining system as claimed in claim 7, it is characterised in that：The ciphertext data module
Including calculating the nearest vector closest to the ciphertext using Babai algorithm, generated by public key described in the nearest vector sum
The plaintext Result.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201810589541.0A CN108881204A (en) | 2018-06-08 | 2018-06-08 | Secret protection cluster data mining method, electronic equipment, storage medium and system |
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| CN201810589541.0A CN108881204A (en) | 2018-06-08 | 2018-06-08 | Secret protection cluster data mining method, electronic equipment, storage medium and system |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110163292A (en) * | 2019-05-28 | 2019-08-23 | 电子科技大学 | Secret protection k-means clustering method based on vector homomorphic cryptography |
| CN110378708A (en) * | 2019-07-24 | 2019-10-25 | 核芯互联科技(青岛)有限公司 | A kind of concealed credibility certificate method, apparatus, system and storage medium |
| CN111107076A (en) * | 2019-12-16 | 2020-05-05 | 电子科技大学 | Safe and efficient matrix multiplication outsourcing method |
| CN112231737A (en) * | 2020-11-05 | 2021-01-15 | 深圳技术大学 | Data security comparison protocol implementation method, system, electronic device and storage medium |
| WO2021249500A1 (en) * | 2020-06-12 | 2021-12-16 | 支付宝(杭州)信息技术有限公司 | Method and apparatus for clustering private data of multiple parties |
| CN114070553A (en) * | 2021-10-29 | 2022-02-18 | 深圳技术大学 | Private data matching method, system and storage medium |
| CN114978623A (en) * | 2022-05-06 | 2022-08-30 | 支付宝(杭州)信息技术有限公司 | Privacy protection-based face comparison method and device |
| TWI835300B (en) * | 2022-02-28 | 2024-03-11 | 大陸商中國銀聯股份有限公司 | A data matching method, device, equipment and medium |
-
2018
- 2018-06-08 CN CN201810589541.0A patent/CN108881204A/en active Pending
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110163292A (en) * | 2019-05-28 | 2019-08-23 | 电子科技大学 | Secret protection k-means clustering method based on vector homomorphic cryptography |
| CN110378708A (en) * | 2019-07-24 | 2019-10-25 | 核芯互联科技(青岛)有限公司 | A kind of concealed credibility certificate method, apparatus, system and storage medium |
| CN111107076A (en) * | 2019-12-16 | 2020-05-05 | 电子科技大学 | Safe and efficient matrix multiplication outsourcing method |
| WO2021249500A1 (en) * | 2020-06-12 | 2021-12-16 | 支付宝(杭州)信息技术有限公司 | Method and apparatus for clustering private data of multiple parties |
| CN112231737A (en) * | 2020-11-05 | 2021-01-15 | 深圳技术大学 | Data security comparison protocol implementation method, system, electronic device and storage medium |
| CN112231737B (en) * | 2020-11-05 | 2023-08-22 | 深圳技术大学 | Data security comparison protocol implementation method, system, electronic device and storage medium |
| CN114070553A (en) * | 2021-10-29 | 2022-02-18 | 深圳技术大学 | Private data matching method, system and storage medium |
| TWI835300B (en) * | 2022-02-28 | 2024-03-11 | 大陸商中國銀聯股份有限公司 | A data matching method, device, equipment and medium |
| CN114978623A (en) * | 2022-05-06 | 2022-08-30 | 支付宝(杭州)信息技术有限公司 | Privacy protection-based face comparison method and device |
| CN114978623B (en) * | 2022-05-06 | 2023-11-17 | 支付宝(杭州)信息技术有限公司 | Face comparison method and device based on privacy protection |
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