CN111831634A - Cloud platform processing system and method based on big data - Google Patents
Cloud platform processing system and method based on big data Download PDFInfo
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- CN111831634A CN111831634A CN202010650734.XA CN202010650734A CN111831634A CN 111831634 A CN111831634 A CN 111831634A CN 202010650734 A CN202010650734 A CN 202010650734A CN 111831634 A CN111831634 A CN 111831634A
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- 238000012545 processing Methods 0.000 title claims abstract description 27
- 238000000034 method Methods 0.000 title claims abstract description 24
- 238000013075 data extraction Methods 0.000 claims abstract description 35
- 238000004458 analytical method Methods 0.000 claims abstract description 23
- 238000013500 data storage Methods 0.000 claims abstract description 22
- 238000012544 monitoring process Methods 0.000 claims description 23
- 238000002372 labelling Methods 0.000 claims description 20
- 241000700605 Viruses Species 0.000 claims description 7
- 238000003672 processing method Methods 0.000 claims description 6
- 238000001514 detection method Methods 0.000 claims description 4
- 238000000605 extraction Methods 0.000 claims description 4
- 230000008439 repair process Effects 0.000 claims description 4
- 238000012552 review Methods 0.000 claims description 2
- 238000012163 sequencing technique Methods 0.000 abstract description 7
- 238000007405 data analysis Methods 0.000 description 13
- 238000010586 diagram Methods 0.000 description 3
- 239000000284 extract Substances 0.000 description 2
- 238000012216 screening Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
- G06F11/302—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system component is a software system
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
- G06F21/57—Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
- G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
Abstract
The invention discloses a cloud platform processing system and a method based on big data, which comprises a data acquisition module, a data storage module, a user operation module, a data extraction module and a cloud computing analysis module, wherein the data storage module comprises public cloud equipment, a data classification module, a redundancy encryption module, a data marking module and private cloud equipment, and the data extraction module comprises an identification module, a sequencing module, a selection module, a marking identification module and a self-checking module. The safety of the cloud platform is improved.
Description
Technical Field
The invention relates to the technical field of big data processing, in particular to a cloud platform processing system and a cloud platform processing method based on big data.
Background
Big data is an IT industry term, and refers to a data set which cannot be captured, managed and processed by a conventional software tool within a certain time range, the relation between the big data and cloud computing is as dense as the front and back of a coin, the big data cannot be processed by a single computer necessarily, a distributed architecture must be adopted, and the method must rely on distributed processing, a distributed database, cloud storage and virtualization technologies of cloud computing;
however, the current cloud platform processing system for big data processing does not perform self-checking during data extraction in the data extraction process, so that viruses in public cloud equipment enter private cloud equipment in the data extraction process, the private cloud equipment is seriously damaged, and the security of the cloud platform is affected.
Disclosure of Invention
The invention provides a cloud platform processing system and a cloud platform processing method based on big data, which can effectively solve the problem that the security of a cloud platform is influenced because viruses in public cloud equipment enter private cloud equipment in the data extraction process and cause serious damage to the private cloud equipment because the current cloud platform processing system for big data processing does not perform self-check during data extraction in the data extraction process.
In order to achieve the purpose, the invention provides the following technical scheme: a cloud platform processing system based on big data comprises a data acquisition module, a data storage module, a user operation module, a data extraction module and a cloud computing analysis module;
the data storage module comprises public cloud equipment, a data classification module, a redundancy encryption module, a data annotation module and private cloud equipment;
the data extraction module comprises an identification module, a sorting module, a selection module, a label identification module and a self-checking module.
Preferably, the self-checking module is connected with public cloud equipment, the selection module is connected with the public cloud equipment and the private cloud equipment respectively, the selection module is connected with the labeling identification module, the private cloud equipment, the public cloud equipment, the sequencing module and the self-checking module respectively, and the identification module is connected with the sequencing module.
Preferably, the private cloud equipment stores company operation data and user data of the user, carries out classification and labeling according to the use condition, and the public cloud equipment accesses the internet, updates the current market trend in real time and analyzes the market trend.
Preferably, the data classification module is connected with the redundant encryption module, and the private cloud equipment is respectively connected with the redundant encryption module and the data labeling module;
the general encrypted data acquired by the data acquisition module enter a data classification module in the data storage module for classification, the classified data are subjected to redundant encryption through a redundant encryption module, the classified data subjected to redundant encryption enter private equipment for storage, and the classified data are labeled by a data labeling module, so that later extraction and identification are facilitated.
Preferably, the redundant encryption module comprises a schema micro data labeling tool and a data labeling tool, and is used for directly labeling simple articles, book reviews, events, local merchants, movies, products, restaurants, software applications and television sequels, and creating a new webpage set by using the data labeling tool for labeling data of special types.
Preferably, a safety monitoring module is connected between the data storage module and the user operation module;
the safety monitoring module comprises an operation tracking recorder, a monitoring server, an early warning module and a data restoration module;
the operation tracking recorder is connected with the monitoring server, and the early warning module is respectively connected with the data restoration module and the monitoring server.
Preferably, the operation tracking recorder records the classification encryption of data in the data storage process and the identification analysis operation of the data in the data extraction process, monitors the data damage and loss condition in each step of operation through the monitoring server, immediately carries out early warning prompt through the early warning module when detecting that the data is damaged and lost, and repairs the data by using the data repairing module.
Preferably, the data extraction process is as follows:
s1, inputting a login password on the user operation module;
s2, inputting requirements after login authentication;
s3, extracting corresponding data from the storage module according to the requirement;
s4, detecting the integrity and validity of the data, re-extracting the necessary data which are not detected, and if not, sending an instruction to the data acquisition module for collection;
and S5, processing the extracted data by the cloud computing analysis module, and presenting an analysis result in the user operation module.
Preferably, in S3 of the data extraction, the identification module is used to identify and analyze the requirements of the user, the sorting module is used to sort the relevance of the data to be extracted, and the tagging identification module is used to identify the data tagged in the private cloud device in a classified manner;
the method comprises the steps of extracting marked data with the relevance exceeding 20% in the private cloud equipment, extracting the data with the relevance exceeding 20% in the public cloud equipment to a self-checking module, carrying out security detection on the data to be extracted in the public cloud equipment, and preventing viruses in the data from entering the private cloud equipment through the extracting module to attack.
Preferably, in S4, the data extraction module selectively extracts complete and valid data, checks whether the required data is completely extracted, and if necessary data is not extracted, extracts the data storage module again, and if necessary data is not extracted yet, issues an instruction to the data acquisition module to collect the missing module, and acquires the missing data.
Compared with the prior art, the invention has the beneficial effects that:
by arranging the public cloud equipment and the self-checking module, data of the public cloud equipment and data of the private cloud equipment are extracted and analyzed simultaneously, the data of an enterprise are combined with market trends to obtain a more accurate analysis result, and the data with danger signals are rejected out of the door through self-checking of the self-checking module, so that the possibility that viruses in the public cloud equipment enter the private cloud equipment in the data extraction process is reduced, and the safety of a cloud platform is improved;
the data is selected through the selection module, the data with high correlation degree is selected, the incomplete invalid data are removed until the required data are completely selected, and the data can be rapidly identified and screened through the marking information of the data when being selected, so that the screening time is shortened, the screening accuracy is improved, and the data processing efficiency is improved;
in the whole data storage and extraction process, the operation tracking recorder in the safety monitoring module is used for recording the operation steps, the monitoring server is used for monitoring the integrity and loss of data, the data with early warning is repaired, the risk of data loss is reduced, the time for acquiring the data again is shortened, and the time for analyzing the data is saved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
In the drawings:
FIG. 1 is a schematic structural view of the present invention;
FIG. 2 is a schematic diagram of the structure of the data collection module of the present invention;
FIG. 3 is a flow chart of data extraction of the present invention;
FIG. 4 is a schematic diagram of the structure of the data storage module of the present invention;
fig. 5 is a schematic structural diagram of the security monitoring module of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Example 1: as shown in fig. 1-2, the present invention provides a technical solution, a cloud platform processing system based on big data, which includes a data acquisition module, a data storage module, a user operation module, a data extraction module, and a cloud computing analysis module;
the data storage module comprises public cloud equipment, a data classification module, a redundancy encryption module, a data annotation module and private cloud equipment;
the data extraction module comprises an identification module, a sorting module, a selection module, a label identification module and a self-checking module.
The self-checking module is connected with the public cloud equipment, the selection module is respectively connected with the public cloud equipment and the private cloud equipment, the selection module is respectively connected with the marking identification module, the private cloud equipment, the public cloud equipment, the sequencing module and the self-checking module, and the identification module is connected with the sequencing module.
The private cloud equipment stores company operation data and user data of users, classification and labeling are carried out according to use conditions, the public cloud equipment is connected to the Internet, the current market trend is updated in real time, and market trends are analyzed.
Example 2: as shown in fig. 4, the present invention provides a technical solution, in a cloud platform processing system based on big data, a data classification module is connected with a redundant encryption module, and a private cloud device is respectively connected with the redundant encryption module and a data tagging module;
the common encrypted data acquired by the data acquisition module enter a data classification module in the data storage module for classification, the classified data are subjected to redundant encryption through a redundant encryption module, the classified data subjected to redundant encryption enter private equipment for storage, and the classified data are labeled by a data labeling module, so that later extraction and identification are facilitated.
The redundant encryption module comprises a schema micro data labeling and data labeling tool, and is used for directly labeling simple articles, book comments, events, local merchants, movies, products, restaurants, software applications and television sequels, and creating a new webpage set by using the data labeling tool for labeling special types of data such as user consumption records, movies newly shown in the recent year and the like.
Example 3: as shown in fig. 5, the present invention provides a technical solution, a cloud platform processing system based on big data, a security monitoring module is connected between a data storage module and a user operation module;
the safety monitoring module comprises an operation tracking recorder, a monitoring server, an early warning module and a data restoration module;
the operation tracking recorder is connected with the monitoring server, and the early warning module is respectively connected with the data restoration module and the monitoring server.
The operation tracking recorder records the classification encryption of data in the data storage process and the identification analysis operation of the data in the data extraction process, monitors the data damage and loss condition in each step of operation through the monitoring server, immediately carries out early warning prompt through the early warning module when detecting that the data is damaged and lost, and restores the data by using the data restoration module.
The working principle and the using process of the invention are as follows: firstly, inputting a login password on a user operation module, inputting a requirement after login authentication, identifying and analyzing the requirement of a user by using an identification module, sequencing data to be extracted from high to low relevance by using a sequencing module, and identifying classified and labeled data in private cloud equipment by using a labeling identification module;
extracting the marked data with the relevance exceeding 20% in the private cloud equipment, extracting the data with the relevance exceeding 20% in the public cloud equipment to a self-checking module, carrying out security detection on the data to be extracted in the public cloud equipment, preventing viruses in the data from entering the private cloud equipment through the extracting module to attack,
the complete and effective data are selected and extracted, the completeness of the required data extraction is checked, if the data extraction is complete, the data are transmitted to a cloud computing analysis module, a data analysis result is analyzed and calculated by the cloud computing analysis module, and the data analysis result is presented to a user operation module;
if the data extraction is not complete and necessary data with the correlation degree exceeding 50% is lacked, extracting the private cloud equipment and the public cloud equipment again, extracting required complete data, transmitting all the extracted data to the cloud computing and analyzing module, analyzing and calculating a data analysis result by using the cloud computing and analyzing module, and presenting the data analysis result to the user operation module;
deleting incomplete data if necessary data are not extracted, sending an instruction for collecting a missing module to a data acquisition module, acquiring the missing data again until complete data are acquired, transmitting all the extracted data to a cloud computing analysis module, analyzing and calculating a data analysis result by using the cloud computing analysis module, and presenting the data analysis result to a user operation module;
the operation tracking recorder records the classification encryption of data in the data storage process and the identification analysis operation of the data in the data extraction process, monitors the data damage and loss condition in each step of operation through the monitoring server, immediately carries out early warning prompt through the early warning module when detecting that the data is damaged and lost, and repairs the data by using the data repairing module, thereby avoiding the loss of the data, saving the time for obtaining the data again and improving the efficiency of data analysis.
Example 4: as shown in fig. 3, the present invention provides a technical solution, a cloud platform processing method based on big data, and a data extraction process includes:
s1, inputting a login password on the user operation module;
s2, inputting requirements after login authentication;
s3, extracting corresponding data from the storage module according to the requirement;
s4, detecting the integrity and validity of the data, re-extracting the necessary data which are not detected, and if not, sending an instruction to the data acquisition module for collection;
and S5, processing the extracted data by the cloud computing analysis module, and presenting an analysis result in the user operation module.
In the data extraction step S3, an identification module is used for identifying and analyzing the requirements of the user, a sorting module is used for sorting the data to be extracted from high to low relevance, and a label identification module is used for identifying the classified and labeled data in the private cloud equipment;
the method comprises the steps of extracting marked data with the relevance exceeding 20% in the private cloud equipment, extracting the data with the relevance exceeding 20% in the public cloud equipment to a self-checking module, carrying out security detection on the data to be extracted in the public cloud equipment, and preventing viruses in the data from entering the private cloud equipment through the extracting module to attack.
In the data extraction step S4, the complete and effective data is selectively extracted, the completeness of the required data extraction is checked, and if the data extraction is complete, the data is transmitted to the cloud computing analysis module, the cloud computing analysis module is used to analyze and calculate the data analysis result, and the data analysis result is presented to the user operation module;
if the data extraction is not complete and necessary data with the correlation degree exceeding 50% is lacked, extracting the private cloud equipment and the public cloud equipment again, extracting required complete data, transmitting all the extracted data to the cloud computing and analyzing module, analyzing and calculating a data analysis result by using the cloud computing and analyzing module, and presenting the data analysis result to the user operation module;
and deleting the incomplete data if the necessary data is not extracted, sending an instruction for collecting the missing module to the data acquisition module, acquiring the missing data again until the complete data is acquired, transmitting all the extracted data to the cloud computing analysis module, analyzing and calculating a data analysis result by using the cloud computing analysis module, and presenting the data analysis result to the user operation module.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. 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 (10)
1. The utility model provides a cloud platform processing system based on big data which characterized in that: the cloud computing system comprises a data acquisition module, a data storage module, a user operation module, a data extraction module and a cloud computing analysis module;
the data storage module comprises public cloud equipment, a data classification module, a redundancy encryption module, a data annotation module and private cloud equipment;
the data extraction module comprises an identification module, a sorting module, a selection module, a label identification module and a self-checking module.
2. The cloud platform processing system based on big data according to claim 1, wherein the self-checking module is connected with public cloud equipment, the selection module is connected with the public cloud equipment and the private cloud equipment, the selection module is connected with the labeling recognition module, the private cloud equipment, the public cloud equipment, the sorting module and the self-checking module, and the recognition module is connected with the sorting module.
3. The cloud platform processing system based on big data as claimed in claim 1, wherein the private cloud device stores company operation data and user data of users, and carries out classification and labeling according to use conditions, and the public cloud device accesses the internet, updates current market trend in real time, and analyzes market trend.
4. The big data based cloud platform processing system according to claim 1, wherein the data classification module is connected to a redundant encryption module, and the private cloud device is connected to the redundant encryption module and the data tagging module, respectively;
the general encrypted data acquired by the data acquisition module enter a data classification module in the data storage module for classification, the classified data are subjected to redundant encryption through a redundant encryption module, the classified data subjected to redundant encryption enter private equipment for storage, and the classified data are labeled by a data labeling module, so that later extraction and identification are facilitated.
5. The big-data-based cloud platform processing system according to claim 4, wherein the redundant encryption module comprises schema micro data tagging and data tagging tools, and is used for directly tagging simple articles, book reviews, events, local merchants, movies, products, restaurants, software applications and television sequels, and for tagging a new webpage set created by data of a special category by using the data tagging tools.
6. The cloud platform processing system based on big data according to claim 1, wherein a security monitoring module is connected between the data storage module and the user operation module;
the safety monitoring module comprises an operation tracking recorder, a monitoring server, an early warning module and a data restoration module;
the operation tracking recorder is connected with the monitoring server, and the early warning module is respectively connected with the data restoration module and the monitoring server.
7. The cloud platform processing system based on big data as claimed in claim 6, wherein the operation tracking recorder records classification encryption of data in a data storage process and identification and analysis operations of data in a data extraction process, monitors the data damage and loss condition in each operation through the monitoring server, immediately performs early warning prompt through the early warning module when detecting data damage and loss, and repairs the data by using the data repair module.
8. The processing method of the cloud platform processing system based on big data according to any one of claims 1 to 7, wherein the data extraction process is as follows:
s1, inputting a login password on the user operation module;
s2, inputting requirements after login authentication;
s3, extracting corresponding data from the storage module according to the requirement;
s4, detecting the integrity and validity of the data, re-extracting the necessary data which are not detected, and if not, sending an instruction to the data acquisition module for collection;
and S5, processing the extracted data by the cloud computing analysis module, and presenting an analysis result in the user operation module.
9. The cloud platform processing method based on big data according to claim 8, wherein in S3 of data extraction, an identification module is used to identify and analyze the needs of a user, a ranking module is used to rank the relevance of the data to be extracted, and a label identification module is used to identify the data labeled in a classification manner in the private cloud device;
the method comprises the steps of extracting marked data with the relevance exceeding 20% in the private cloud equipment, extracting the data with the relevance exceeding 20% in the public cloud equipment to a self-checking module, carrying out security detection on the data to be extracted in the public cloud equipment, and preventing viruses in the data from entering the private cloud equipment through the extracting module to attack.
10. The cloud platform processing method based on big data according to claim 8, wherein in S4 of data extraction, complete and valid data is selectively extracted, whether the required data is extracted completely is checked, if necessary data is not extracted, the data storage module is extracted again, and if necessary data is not extracted yet, the data acquisition module is instructed to collect missing data, so as to acquire the missing data.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113157373A (en) * | 2021-04-27 | 2021-07-23 | 上海全云互联网科技有限公司 | Content annotation platform and method based on cloud desktop |
| CN113900801A (en) * | 2021-09-26 | 2022-01-07 | 成都飞机工业（集团）有限责任公司 | Cloud platform data management system and method |
| CN115203136A (en) * | 2022-09-14 | 2022-10-18 | 南方电网调峰调频发电有限公司 | Artificial intelligence management system based on big data |
-
2020
- 2020-07-08 CN CN202010650734.XA patent/CN111831634A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113157373A (en) * | 2021-04-27 | 2021-07-23 | 上海全云互联网科技有限公司 | Content annotation platform and method based on cloud desktop |
| CN113157373B (en) * | 2021-04-27 | 2023-04-18 | 上海全云互联网科技有限公司 | Content labeling system and method based on cloud desktop |
| CN113900801A (en) * | 2021-09-26 | 2022-01-07 | 成都飞机工业（集团）有限责任公司 | Cloud platform data management system and method |
| CN115203136A (en) * | 2022-09-14 | 2022-10-18 | 南方电网调峰调频发电有限公司 | Artificial intelligence management system based on big data |
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