CN109617964B - Big data storage method and device based on block chain - Google Patents
Big data storage method and device based on block chain Download PDFInfo
- Publication number
- CN109617964B CN109617964B CN201811521943.3A CN201811521943A CN109617964B CN 109617964 B CN109617964 B CN 109617964B CN 201811521943 A CN201811521943 A CN 201811521943A CN 109617964 B CN109617964 B CN 109617964B
- Authority
- CN
- China
- Prior art keywords
- data
- uplink
- capacity
- uplink data
- storage
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- 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
- H04L67/1097—Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The embodiment of the invention relates to the technical field of data storage, in particular to a block chain-based big data storage method and device.
Description
Technical Field
The embodiment of the invention relates to the technical field of data storage, in particular to a big data storage method and device based on a block chain.
Background
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism and an encryption algorithm, and has the characteristics of decentralization, openness, no tampering and the like. The important information asset of big data plays an important role in the modern information society, so that the combination of big data and a block chain has profound significance. However, due to the limitations of its implementation principle, the blockchain does not support the storage of large data.
Disclosure of Invention
In view of this, the present invention provides a block chain based big data storage method and apparatus.
The embodiment of the invention provides a big data storage method based on a block chain, which is applied to a server side and comprises the following steps:
acquiring the storage capacity of a block;
extracting first abstract data in big data to be stored, taking the first abstract data as first uplink data, and taking data except the first abstract data in the big data to be stored as first non-uplink data;
obtaining a first data capacity of the first uplink data;
and judging whether the first data capacity exceeds the storage capacity, if the first data capacity does not exceed the storage capacity, encrypting the first uplink data and the first non-uplink data, and storing the encrypted first uplink data in the block.
Optionally, the method further comprises:
if the first data capacity exceeds the storage capacity, extracting second abstract data from the first abstract data, taking the second abstract data as second uplink data, and taking data except the second abstract data in the big data to be stored as second non-uplink data;
obtaining a second data capacity of the second uplink data;
and judging whether the second data capacity exceeds the storage capacity, if the second data capacity does not exceed the storage capacity, encrypting the second uplink data and the second non-uplink data, and storing the encrypted second uplink data in the block.
Optionally, the step of extracting second summary data from the first summary data includes:
acquiring the priority of each metadata in the first summary data;
and selecting a preset number of metadata in the first summary data as the second summary data according to the sequence of the priority from high to low.
Optionally, the step of extracting second summary data from the first summary data includes:
acquiring a field name of each metadata in the first summary data;
aiming at each acquired field name, searching whether a set field name corresponding to the field name exists in a preset field name database, and if so, extracting metadata corresponding to the field name;
and taking at least one piece of metadata obtained by extraction as the second summary data.
Optionally, the step of encrypting the first uplink data and the first non-uplink data includes:
generating a public key according to the first uplink data;
generating a private key according to the first non-uplink data;
and establishing a corresponding relation between the public key and the private key, wherein the corresponding relation is unique.
The embodiment of the invention also provides a big data storage device based on the block chain, which is applied to a server side, and the device comprises:
the storage capacity acquisition module is used for acquiring the storage capacity of the block;
the data processing device comprises a summary data extraction module, a data storage module and a data processing module, wherein the summary data extraction module is used for extracting first summary data in big data to be stored, taking the first summary data as first uplink data, and taking data except the first summary data in the big data to be stored as first non-uplink data;
a data capacity obtaining module, configured to obtain a first data capacity of the first uplink data;
and the uplink module is used for judging whether the first data capacity exceeds the storage capacity, encrypting the first uplink data and the first non-uplink data if the first data capacity does not exceed the storage capacity, and storing the encrypted first uplink data in the block.
Optionally, the uplink module is further configured to extract second abstract data from the first abstract data if the first data capacity exceeds the storage capacity, use the second abstract data as second uplink data, and use data of the large data to be stored, except for the second abstract data, as second non-uplink data; the data capacity obtaining module is further configured to obtain a second data capacity of the second uplink data; the uplink module is further configured to determine whether the second data capacity exceeds the storage capacity, encrypt the second uplink data and the second non-uplink data if the second data capacity does not exceed the storage capacity, and store the encrypted second uplink data in the block.
Optionally, the uplink module extracts second summary data from the first summary data by:
acquiring the priority of each metadata in the first summary data;
and selecting a preset number of metadata in the first summary data as the second summary data according to the sequence of the priority from high to low.
Optionally, the uplink module extracts second summary data from the first summary data by:
acquiring a field name of each metadata in the first summary data;
aiming at each acquired field name, searching whether a set field name corresponding to the field name exists in a preset field name database, and if so, extracting metadata corresponding to the field name;
and taking at least one piece of metadata obtained by extraction as the second summary data.
Optionally, the uplink module encrypts the first uplink data and the first non-uplink data by:
generating a public key according to the first uplink data;
generating a private key according to the first non-uplink data;
and establishing a corresponding relation between the public key and the private key, wherein the corresponding relation is unique.
The embodiment of the invention also provides a server, which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the computer program to realize the block chain-based big data storage method.
The embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium includes a computer program, and when the computer program runs, the computer program controls a server where the computer-readable storage medium is located to execute the above big data storage method based on the block chain.
Advantageous effects
According to the block chain-based big data storage method and device provided by the embodiment of the invention, the big data to be stored can be 'split' into the first uplink data and the first non-uplink data according to the storage capacity of the block, when the first data capacity of the first uplink data meets the storage capacity requirement, the first uplink data and the first non-uplink data are encrypted, and the first uplink data is stored in the block, so that the storage of the big data in the block chain can be realized, and the limitation of the big data uplink storage is improved. In addition, the first uplink data and the first non-uplink data are encrypted, so that the non-tamper property of the large data to be stored is ensured, and the large data can also have the same characteristics as the block chain.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a block diagram of a server 10 according to an embodiment of the present invention.
Fig. 2 is a flowchart of a block chain-based big data storage method according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a large data storage based on a block chain according to an embodiment of the present invention.
Fig. 4 is a block diagram of a large data storage device 20 based on a block chain according to an embodiment of the present invention.
Icon:
10-a server side; 11-a memory; 12-a processor; 13-a network module;
20-big data storage based on block chains; 21-a storage capacity acquisition module; 22-abstract data extraction module; 23-a data capacity acquisition module; 24-uplink module.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
The inventors have investigated that it is difficult to achieve full uplink storage of large data due to the nature of the blockchain itself.
The above prior art solutions have shortcomings which are the results of practical and careful study of the inventor, and therefore, the discovery process of the above problems and the solutions proposed by the following embodiments of the present invention to the above problems should be the contribution of the inventor to the present invention in the course of the present invention.
Based on the above research, embodiments of the present invention provide a block chain-based big data storage method and apparatus, which implement uplink storage after splitting big data, and improve the limitation of big data uplink storage.
Fig. 1 is a block diagram illustrating a server 10 according to an embodiment of the present invention. The server 10 in the embodiment of the present invention has data storage, transmission, and processing functions, and as shown in fig. 1, the server 10 includes: memory 11, processor 12, network module 13 and big data storage based on block chain 20.
The memory 11, the processor 12 and the network module 13 are electrically connected directly or indirectly to realize data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The memory 11 stores a big data storage device 20 based on a block chain, the big data storage device 20 based on a block chain includes at least one software functional module which can be stored in the memory 11 in a form of software or firmware (firmware), and the processor 12 executes various functional applications and data processing by running software programs and modules stored in the memory 11, for example, the big data storage device 20 based on a block chain in the embodiment of the present invention, so as to implement the big data storage method based on a block chain in the embodiment of the present invention.
The Memory 11 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The memory 11 is used for storing a program, and the processor 12 executes the program after receiving an execution instruction.
The processor 12 may be an integrated circuit chip having data processing capabilities. The Processor 12 may be a general-purpose Processor including a Central Processing Unit (CPU), a Network Processor (NP), and the like. The various methods, steps and logic blocks disclosed in embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The network module 13 is used for establishing communication connection between the server 10 and other communication terminal devices through a network, and implementing transceiving operation of network signals and data. The network signal may include a wireless signal or a wired signal.
It is understood that the configuration shown in fig. 1 is merely illustrative, and that the server 10 may include more or fewer components than shown in fig. 1, or have a different configuration than shown in fig. 1. The components shown in fig. 1 may be implemented in hardware, software, or a combination thereof.
An embodiment of the present invention also provides a computer-readable storage medium, which includes a computer program. The computer program controls the server 10 where the readable storage medium is located to execute the following block chain-based big data storage method.
Fig. 2 shows a flowchart of a block chain-based big data storage method according to an embodiment of the present invention. The method steps defined by the flow related to the method are applied to the server 10 and can be implemented by the processor 12. The specific process shown in FIG. 2 will be described in detail below:
in step S21, the storage capacity of the block is obtained.
It can be understood that, since the blockchain network is composed of individual blocks, the storage capacity of each block is relatively small in view of the principles of the network-wide storage and the distributed ledger. For example, even if bitcoin is operated for 10 years, the total storage capacity does not exceed 200G.
The capacity of the large data far exceeds the storage capacity of the block, and the storage capacity of the block needs to be analyzed in order to realize the large data uplink.
In this embodiment, the storage capacity of the block is Z0。
Step S22, extract the first abstract data in the big data to be stored, use the first abstract data as the first uplink data, and use the data in the big data to be stored except the first abstract data as the first non-uplink data.
For example, the big data to be stored is data, and the extracted first summary data is dataa1。
The first uplink data is dataa1The first non-uplink data is data-dataa1。
In step S23, a first data capacity of the first uplink data is obtained.
For example, dataa1Has a data capacity of Z1。
In step S24, it is determined whether the first data capacity exceeds the storage capacity.
It can be understood that the data capacity of the big data is much larger than the storage capacity of the block, and even the summary data of the big data may be larger than the storage capacity of the block, and for enabling successful uplink of the big data, the data capacity of Z needs to be much larger than the storage capacity of the block1And (6) judging.
If Z is1Not exceeding Z0The process proceeds to step S25.
If Z is1Over Z0The process proceeds to step S26.
Step S25, encrypt the first uplink data and the first non-uplink data, and store the encrypted first uplink data in the block.
It will be understood that if Z is1Not exceeding Z0Will dataa1And data-dataa1Respectively encrypted, and then the encrypted dataa1And storing the data to the block.
By the method, the data can be split and can be acquireda1The data characteristics can be well reflected as the summary data of the data, so that the storage mode of the large data uplink is satisfied.
Further, for dataa1And data-dataa1Separate encryption ensures that the big data has the non-tamper property of the block chain.
For example, please refer to FIG. 3 in combination, according to the dataa1Generating a public key k1cAccording to data-dataa1Generating a private key k1sAnd establishes a public key k1cAnd a private key k1sWherein the corresponding relationship is unique. Thus, the uncollapsibility of the large data can be ensured.
Specifically, dataa1Are stored in block chains and therefore have non-tamper-evident properties. According to data-dataa1Generated private Key k1sIs also unique, therefore, only in data-dataa1Without being tampered withCommon secret key k1cAnd a private key k1sCan be matched to further realize dataa1And data-dataa1And (4) splicing and verifying. Also for example, if data-dataa1Is tampered as data-dataa1-1, data-dataa1-1 the generated private key is k, at which time k1cAnd k cannot pass the splice verification.
Therefore, in the embodiment, the big data is "split" and stored, so that the limitation of uplink storage of the big data is solved, and meanwhile, the encryption operation can ensure that the big data is not tamper-proof, so that the big data can have the same characteristics as the block chain.
It will be appreciated that the first non-uplink data capacity is large and can be stored in a conventional large data storage platform.
Step S26, extracting the second abstract data from the first abstract data, using the second abstract data as the second uplink data, and using the data except the second abstract data in the big data to be stored as the second non-uplink data.
It will be understood that if Z is1Over Z0Indicates dataa1The data capacity of (2) is still too large, and data is needed to be processed at the momenta1Further simplification is made, in particular, from dataa1Extracting the second abstract data as the second uplink dataa2To convert data to dataa2As second non-uplink data.
Optionally, the slave dataa1Extract data therefroma2This can be done in two ways.
One method is to obtain the dataa1The data is selected according to the priority of each metadata in the sequence from high to lowa1A predetermined number of metadata as dataa2。
Another method is to obtain dataa1For each field name of the obtained field name, searching whether a set field name corresponding to the field name exists in a preset field name database, if so, extracting the metadata corresponding to the field name, and taking at least one extracted metadata as dataa2。
Wherein the set field names can be edited by the user at his or her discretion.
Step S27, obtaining a second data capacity of the second uplink data, and performing a corresponding operation according to a comparison result between the second data capacity and the storage capacity.
Acquiring dataa2Second data capacity Z2According to Z2And Z0Until the data capacity of the extracted summary data is less than Z0Until then, storage is performed as in step S25.
Optionally, the data may be encrypted in an asymmetric manner.
On the basis of the above, as shown in fig. 4, an embodiment of the present invention provides a block chain based big data storage device 20, where the block chain based big data storage device 20 includes: a storage capacity obtaining module 21, a summary data extracting module 22, a data capacity obtaining module 23 and a uplink module 24.
A storage capacity obtaining module 21, configured to obtain the storage capacity of the block.
Since the storage capacity obtaining module 21 is similar to the implementation principle of step S21 in fig. 2, it will not be further described here.
The abstract data extracting module 22 is configured to extract first abstract data in the big data to be stored, use the first abstract data as first uplink data, and use data, other than the first abstract data, in the big data to be stored as first non-uplink data.
Since the abstract data extraction module 22 is similar to the implementation principle of step S22 in fig. 2, it will not be further described here.
A data capacity obtaining module 23, configured to obtain a first data capacity of the first uplink data.
Since the data capacity obtaining module 23 is similar to the implementation principle of step S23 in fig. 2, it will not be further described here.
An uplink module 24, configured to determine whether the first data capacity exceeds the storage capacity, and encrypt the first uplink data and the first non-uplink data if the first data capacity does not exceed the storage capacity, and store the encrypted first uplink data in the block.
Since the upper chain module 24 is similar to the implementation principle of the steps S24, S25, S26 and S27 in fig. 2, no further description is provided here.
In summary, the block chain based storage method and apparatus provided in the embodiments of the present invention can improve the limitation of big data uplink storage.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus and method embodiments described above are illustrative only, as the flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention or a part of the technical solution that substantially contributes to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server 10, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes. It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A big data storage method based on a block chain is applied to a server side, and the method comprises the following steps:
acquiring the storage capacity of a block;
extracting first abstract data in big data to be stored, taking the first abstract data as first uplink data, and taking data except the first abstract data in the big data to be stored as first non-uplink data;
obtaining a first data capacity of the first uplink data;
judging whether the first data capacity exceeds the storage capacity, if the first data capacity does not exceed the storage capacity, encrypting the first uplink data and the first non-uplink data, and storing the encrypted first uplink data in the block;
the method further comprises the following steps:
if the first data capacity exceeds the storage capacity, extracting second abstract data from the first abstract data, taking the second abstract data as second uplink data, and taking data except the second abstract data in the big data to be stored as second non-uplink data;
obtaining a second data capacity of the second uplink data;
judging whether the second data capacity exceeds the storage capacity, if the second data capacity does not exceed the storage capacity, encrypting the second uplink data and the second non-uplink data, and storing the encrypted second uplink data in the block;
the step of extracting second summary data from the first summary data comprises:
acquiring a field name of each metadata in the first summary data;
aiming at each acquired field name, searching whether a set field name corresponding to the field name exists in a preset field name database, and if so, extracting metadata corresponding to the field name;
and taking at least one piece of metadata obtained by extraction as the second summary data.
2. The blockchain-based big data storage method according to claim 1, wherein the step of extracting the second summary data from the first summary data includes:
acquiring the priority of each metadata in the first summary data;
and selecting a preset number of metadata in the first summary data as the second summary data according to the sequence of the priority from high to low.
3. The blockchain-based big data storage method according to claim 1, wherein the step of encrypting the first uplink data and the first non-uplink data includes:
generating a public key according to the first uplink data;
generating a private key according to the first non-uplink data;
and establishing a corresponding relation between the public key and the private key, wherein the corresponding relation is unique.
4. A big data storage device based on a block chain is applied to a server side, and the device comprises:
the storage capacity acquisition module is used for acquiring the storage capacity of the block;
the data processing device comprises a summary data extraction module, a data storage module and a data processing module, wherein the summary data extraction module is used for extracting first summary data in big data to be stored, taking the first summary data as first uplink data, and taking data except the first summary data in the big data to be stored as first non-uplink data;
a data capacity obtaining module, configured to obtain a first data capacity of the first uplink data;
an uplink module, configured to determine whether the first data capacity exceeds the storage capacity, encrypt the first uplink data and the first non-uplink data if the first data capacity does not exceed the storage capacity, and store the encrypted first uplink data in the block;
the uplink module is further configured to extract second abstract data from the first abstract data if the first data capacity exceeds the storage capacity, use the second abstract data as second uplink data, and use data, except the second abstract data, in the large data to be stored as second non-uplink data; the data capacity obtaining module is further configured to obtain a second data capacity of the second uplink data; the uplink module is further configured to determine whether the second data capacity exceeds the storage capacity, encrypt the second uplink data and the second non-uplink data if the second data capacity does not exceed the storage capacity, and store the encrypted second uplink data in the block;
the uplink module extracts second summary data from the first summary data by:
acquiring a field name of each metadata in the first summary data;
aiming at each acquired field name, searching whether a set field name corresponding to the field name exists in a preset field name database, and if so, extracting metadata corresponding to the field name;
and taking at least one piece of metadata obtained by extraction as the second summary data.
5. The blockchain-based big data storage device according to claim 4, wherein the uplink module extracts second summary data from the first summary data by:
acquiring the priority of each metadata in the first summary data;
and selecting a preset number of metadata in the first summary data as the second summary data according to the sequence of the priority from high to low.
6. The blockchain-based big data storage device of claim 4, wherein the uplink module encrypts the first uplink data and the first non-uplink data by:
generating a public key according to the first uplink data;
generating a private key according to the first non-uplink data;
and establishing a corresponding relation between the public key and the private key, wherein the corresponding relation is unique.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811521943.3A CN109617964B (en) | 2018-12-12 | 2018-12-12 | Big data storage method and device based on block chain |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811521943.3A CN109617964B (en) | 2018-12-12 | 2018-12-12 | Big data storage method and device based on block chain |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109617964A CN109617964A (en) | 2019-04-12 |
| CN109617964B true CN109617964B (en) | 2021-11-09 |
Family
ID=66007244
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811521943.3A Active CN109617964B (en) | 2018-12-12 | 2018-12-12 | Big data storage method and device based on block chain |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109617964B (en) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110190949B (en) * | 2019-05-31 | 2023-04-14 | 杭州复杂美科技有限公司 | Method, system, apparatus and storage medium for large data volume resource uplink |
| CN111126947B (en) * | 2019-11-29 | 2024-02-13 | 泰康保险集团股份有限公司 | Integrated management method, device, medium and electronic equipment for business data |
| CN111031041A (en) * | 2019-12-13 | 2020-04-17 | 山东众阳健康科技集团有限公司 | Block chain-based data uplink storage method, system, medium and equipment |
| CN111262876B (en) * | 2020-01-22 | 2022-05-27 | 腾讯科技（深圳）有限公司 | Data processing method, device and equipment based on block chain and storage medium |
| CN113254973A (en) * | 2021-06-10 | 2021-08-13 | 永旗(北京)科技有限公司 | Safety encryption system and method based on big data |
| CN113434909B (en) * | 2021-06-25 | 2023-12-29 | 湖北央中巨石信息技术有限公司 | Data on-demand evidence-storing method based on blockchain |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107391527A (en) * | 2017-03-28 | 2017-11-24 | 阿里巴巴集团控股有限公司 | A kind of data processing method and equipment based on block chain |
| CN107426170A (en) * | 2017-05-24 | 2017-12-01 | 阿里巴巴集团控股有限公司 | A kind of data processing method and equipment based on block chain |
| CN108197947A (en) * | 2017-12-27 | 2018-06-22 | 深圳市轱辘车联数据技术有限公司 | A kind of vehicle accessory data processing method and device for block chain |
| CN108566420A (en) * | 2018-03-29 | 2018-09-21 | 上海点融信息科技有限责任公司 | Data processing method, equipment and computer readable storage medium for block chain |
| CN108696594A (en) * | 2018-05-27 | 2018-10-23 | 佛山市虚拟现实大数据产业研究院有限公司 | A kind of the big data traffic load equalization methods and device of market surpervision block chain |
| CN108717466A (en) * | 2018-06-05 | 2018-10-30 | 中国平安人寿保险股份有限公司 | Collage-credit data storage method, device, computer equipment and storage medium |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20170264428A1 (en) * | 2016-03-08 | 2017-09-14 | Manifold Technology, Inc. | Data storage system with blockchain technology |
| US10114980B2 (en) * | 2016-07-21 | 2018-10-30 | Acronis International Gmbh | System and method for verifying data integrity using a blockchain network |
| CN106897348B (en) * | 2016-08-19 | 2020-10-27 | 创新先进技术有限公司 | Data storage method, data verification method, data source tracing method and equipment |
| JP2020522796A (en) * | 2017-06-01 | 2020-07-30 | シュヴェイ， インク． ディー／ビー／エー アクソーニＳＣＨＶＥＹ， ＩＮＣ． ｄ／ｂ／ａ ＡＸＯＮＩ | A distributed, privately subspaced blockchain data structure that manages secure access restrictions |
| CN107948283A (en) * | 2017-11-24 | 2018-04-20 | 中钞信用卡产业发展有限公司杭州区块链技术研究院 | A kind of big file of alliance's chain stores and the method and system of verification |
-
2018
- 2018-12-12 CN CN201811521943.3A patent/CN109617964B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107391527A (en) * | 2017-03-28 | 2017-11-24 | 阿里巴巴集团控股有限公司 | A kind of data processing method and equipment based on block chain |
| CN107426170A (en) * | 2017-05-24 | 2017-12-01 | 阿里巴巴集团控股有限公司 | A kind of data processing method and equipment based on block chain |
| CN108197947A (en) * | 2017-12-27 | 2018-06-22 | 深圳市轱辘车联数据技术有限公司 | A kind of vehicle accessory data processing method and device for block chain |
| CN108566420A (en) * | 2018-03-29 | 2018-09-21 | 上海点融信息科技有限责任公司 | Data processing method, equipment and computer readable storage medium for block chain |
| CN108696594A (en) * | 2018-05-27 | 2018-10-23 | 佛山市虚拟现实大数据产业研究院有限公司 | A kind of the big data traffic load equalization methods and device of market surpervision block chain |
| CN108717466A (en) * | 2018-06-05 | 2018-10-30 | 中国平安人寿保险股份有限公司 | Collage-credit data storage method, device, computer equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109617964A (en) | 2019-04-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109617964B (en) | Big data storage method and device based on block chain | |
| EP0675614B1 (en) | Apparatus for the secure exchange of data according to the RSA method limited to digital signatures and message verification and smart card containing such an apparatus | |
| RU2017131519A (en) | SYSTEMS AND METHODS OF SAFE HANDLING WITH BIOMETRIC DATA | |
| JP6444426B2 (en) | Voiceprint registration method, voiceprint logon method, apparatus, storage medium and equipment | |
| CN109766479B (en) | Data processing method and device, electronic equipment and storage medium | |
| FR3025339A1 (en) | METHOD FOR USING A DEVICE FOR UNLOCKING ANOTHER DEVICE | |
| US9461995B2 (en) | Terminal, network locking and network unlocking method for same, and storage medium | |
| TW201917618A (en) | Model training method and device and method and device of detecting URL | |
| CN108270561B (en) | Data sending method and device and key index generating method and device | |
| FR2699300A1 (en) | Authentication of terminal by server - using signature algorithm in terminal to encode random number sent by server and validating returned signature | |
| CN111680013A (en) | Data sharing method based on block chain, electronic equipment and device | |
| CN113726515B (en) | UKEY-based key processing method, storage medium and electronic device | |
| WO2009050368A2 (en) | Secure communication between an electronic label and a reader | |
| FR2975550A1 (en) | ACCESS PROTECTED BY BIOMETRY TO ELECTRONIC DEVICES | |
| WO2015196642A1 (en) | Data encryption method, decryption method and device | |
| CN110929173A (en) | Method, device, equipment and medium for identifying same person | |
| CN111294209B (en) | Block chain-based intelligent terminal security verification method and device | |
| EP2206068B1 (en) | Distributed database | |
| EP2426652A1 (en) | Simplified method for customising a smart card and associated device | |
| CN116644485A (en) | Anti-counterfeiting authentication method and device for server memory, electronic equipment and storage medium | |
| CN110597822A (en) | Information searching method and device in block chain, storage medium and computer equipment | |
| WO2017174141A1 (en) | Method for providing a proof-of-retrievability | |
| WO2019175482A1 (en) | Secure data processing | |
| CN113051622B (en) | Index construction method, device, equipment and storage medium | |
| CA2613884A1 (en) | Method for providing a secured communication between a user and an entity |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |