CN112488895A - Informatization asset data anomaly analysis method - Google Patents
Informatization asset data anomaly analysis method Download PDFInfo
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- CN112488895A CN112488895A CN202011415351.0A CN202011415351A CN112488895A CN 112488895 A CN112488895 A CN 112488895A CN 202011415351 A CN202011415351 A CN 202011415351A CN 112488895 A CN112488895 A CN 112488895A
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- 238000004458 analytical method Methods 0.000 title claims abstract description 9
- 238000001514 detection method Methods 0.000 claims abstract description 59
- 238000000034 method Methods 0.000 claims abstract description 18
- 238000004140 cleaning Methods 0.000 claims abstract description 5
- 230000014759 maintenance of location Effects 0.000 claims abstract description 5
- 238000013500 data storage Methods 0.000 claims description 4
- 238000012423 maintenance Methods 0.000 claims description 4
- 230000005856 abnormality Effects 0.000 claims 7
- 230000008030 elimination Effects 0.000 abstract description 3
- 238000003379 elimination reaction Methods 0.000 abstract description 3
- 230000010354 integration Effects 0.000 abstract description 3
- 238000006467 substitution reaction Methods 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
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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
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
Abstract
The invention relates to the technical field of government affair service data governance, and particularly provides an informatization asset data anomaly analysis method which is characterized in that different informatization systems are detected according to different detection dimensions to generate detection reports, and the detection reports can be compared and a comparison report can be generated aiming at past detection and retention; the method comprises the steps of firstly sorting asset information related to the application system, cleaning the relation between each information and the application system, and analyzing each detectable related dimension. Compared with the prior art, the method and the system support flexible selection dimension detection, promote and accelerate elimination of suspected zombie information systems, promote integration and sharing of the information systems, and promote national unified electronic government affair network supporting capacity.
Description
Technical Field
The invention relates to the technical field of government affair service data governance, and particularly provides an informatization asset data anomaly analysis method.
Background
In the prior art, important emphasis is placed on the removal and integration of the bother information, and the 'review' and 'clear' are combined to accelerate the elimination of a 'bother' information system.
Basically finishes the cleaning work of the zombie information system with small use range and low frequency, and the system use is disconnected with the actual business process for a long time, the functions can be replaced by other systems, the occupied resources are in an idle state for a long time, the operation, the maintenance and the update are stopped.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a method for constructing the virtual machine image with strong practicability.
The technical scheme adopted by the invention for solving the technical problems is as follows:
an informatization asset data anomaly analysis method is characterized in that different informatization systems are detected according to different detection dimensions to generate detection reports, and the detection reports can be compared and comparison reports can be generated aiming at past detection retention;
the method comprises the steps of firstly sorting asset information related to the application system, cleaning the relation between each information and the application system, and analyzing each detectable related dimension.
Further, the method specifically comprises the following steps:
s1, detecting by a suspected zombie system;
s2, detecting by a high-input low-yield system;
and S3, detecting the system similarity.
Furthermore, the html page is used for detecting the dimension value selection, the selected latitude value is transmitted to the java background by using a js technology, the java background calls the mysql database to perform sql query, and the system which accords with the dimension is queried to be a suspected zombie system.
Further, in step S1, the detection dimension includes the number of tables, the amount of stored table data, the monthly growth amount of data, the ratio of the monthly growth amount of data to the total amount, the number of database instances, the number of system users, the time that the system has been online, the number of system servers, whether the service operation and maintenance time has ended, whether there is a corresponding service item, and whether an information resource directory is generated.
Further, in step S2, the html page performs detection dimension value selection, the js technology is used to transmit the selected latitude value to the java background, the java background calls the mysql database to perform sql query, and the system meeting the dimension is queried to be a high-input low-yield system.
Further, the detection dimension in step S2 includes system project funds, information resource catalog quantity, table data storage quantity, data month growth quantity, month growth data quantity to total quantity ratio, database instance quantity and system user quantity.
Further, in step S3, the html page performs detection dimension value selection, the js technology is used to transmit the selected latitude value to the java background, the java background calls the mysql database to perform sql query, and the system conforming to the dimension is queried as a similar system.
Further, the detection dimensions in step S3 include system name similarity, system function description similarity, system shared database similarity, system resource directory similarity, and system support business item similarity.
Compared with the prior art, the informatization asset data anomaly analysis method has the following outstanding beneficial effects:
the invention supports flexible selection of dimension detection, promotes and accelerates elimination of suspected zombie information systems, promotes integration and sharing of the information systems, and promotes national unified electronic government affair network supporting capability.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow diagram of a method for anomaly analysis of informative asset data.
Detailed Description
The present invention will be described in further detail with reference to specific embodiments in order to better understand the technical solutions of the present invention. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope 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.
A preferred embodiment is given below:
as shown in fig. 1, in the method for analyzing an anomaly of information-based asset data in this embodiment, different information-based systems are detected according to different detection dimensions to generate a detection report, and for past detection and retention, comparison can be performed to generate a comparison report. The method comprises the steps of firstly arranging asset information related to a system, wherein the asset information comprises a machine room, a network, a cloud platform, a virtual machine, a server, a field, a data table, a database, unstructured data, an application system, a project and the like. And cleaning the relation between each piece of information and the application system, and analyzing each detectable relevant dimension.
The method specifically comprises the following steps:
s1, detection by a suspected zombie system:
and selecting a detection dimension value on the html page, transmitting the selected latitude value to a java background by using a js technology, calling a mysql database by the java background to perform sql query, and querying a system which accords with the dimension as a suspected zombie system.
The detection dimension comprises the number of tables, the storage amount of table data, the monthly increment of data, the ratio of the monthly increment data to the total amount, the number of database instances, the number of system users, the online time of the system, the number of system servers, whether the service operation and maintenance time is finished, whether corresponding business events exist, whether an information resource catalog is generated and the like.
And generating a report of a suspected zombie system according to the detection dimension, wherein the report comprises a summary of detection results, the ratio of the detection system to the total system, the ratio of the suspected zombie system to the detection system, the ratio of the suspected zombie system to the total system, the number of the suspected zombie systems in the department, ranking and the like, and a list of information of the suspected zombie system.
S2, detecting by a high-input low-yield system:
and selecting a detection dimension value on the html page, transmitting the selected latitude value to a java background by using a js technology, calling a mysql database by the java background to perform sql query, and querying a system which accords with the dimension as a high-input low-yield system.
The detection dimension comprises system project funds, the number of information resource catalogs, the number of tables, the table data storage amount, the monthly data increase amount, the ratio of the monthly data increase amount to the total amount, the number of database instances and the number of system users.
And generating a high-input low-yield system report according to the detection dimension, wherein the report comprises a summary of detection results, statistics such as the proportion of the detection system in the total system, the proportion of the high-input low-yield system in the detection system, the proportion of the high-input low-yield system in the total system, the quantity of the department high-input low-yield system in the total system, ranking and the like, and a high-input low-.
S3, detecting system similarity:
and selecting a detection dimension value on the html page, transmitting the selected latitude value to a java background by using a js technology, calling a mysql database by the java background to perform sql query, and querying a system which accords with the dimension as a similar system.
The detection dimension comprises similar system names, similar system function descriptions, similar system shared databases, similar system resource catalogs and similar system support business items.
And generating a similar system report according to the detection dimension, wherein the report comprises a detection result summary, detection statistical analysis and a system information list meeting the dimension condition.
S4, self-defining detection:
and integrating all detection dimensions, freely selecting and detecting according to requirements, and generating a detection report.
The detection result generated by detection can be compared with the historical detection result to generate a comparison report, any historical detection retention can be selected for comparison, the report is divided into 3 parts, detection dimension comparison, detection result statistics comparison and detection system list comparison are carried out.
Wherein, the Mysql database stores a system table and a detection history table. The system table structure has fields of system attribute dimensions, and each piece of information system data has own attribute information. The detection history table stores the result information of each detection, so that history comparison is facilitated.
The above embodiments are only specific cases of the present invention, and the protection scope of the present invention includes but is not limited to the above embodiments, and any suitable changes or substitutions that are required by a person of ordinary skill in the art and are in accordance with the claims of an information asset data anomaly analysis method of the present invention shall fall within the protection scope of the present invention.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (8)
1. An informatization asset data anomaly analysis method is characterized in that different informatization systems are detected according to different detection dimensions to generate detection reports, and the detection reports can be compared and comparison reports can be generated aiming at past detection retention;
the method comprises the steps of firstly sorting asset information related to the application system, cleaning the relation between each information and the application system, and analyzing each detectable related dimension.
2. The method for analyzing the abnormality of the informationized asset data according to claim 1, specifically comprising the following steps:
s1, detecting by a suspected zombie system;
s2, detecting by a high-input low-yield system;
and S3, detecting the system similarity.
3. The method for analyzing the abnormality of the informationized asset data according to claim 2, wherein in step S1, a html page is used for selecting a detection dimension value, a js technology is used for transmitting the selected latitude value to a java background, the java background calls a mysql database to perform sql query, and a system conforming to the dimension is queried to be a suspected zombie system.
4. The method for analyzing the abnormality of the informationized asset data according to claim 3, wherein the detection dimensions in step S1 include table number, table data storage amount, monthly growth amount of data, monthly growth data amount to total amount ratio, database instance number, system user number, system on-line time, system server number, whether service operation and maintenance time has ended, whether corresponding service event exists, and whether information resource directory is generated.
5. The method for analyzing the abnormality of the informationized asset data according to claim 4, wherein in step S2, a html page is used for selecting a detection dimension value, a js technology is used for transmitting the selected latitude value to a java background, the java background calls a mysql database to perform sql query, and a system conforming to the dimension is queried to be a high-input low-yield system.
6. The method for analyzing the abnormality of the informative asset data according to claim 5, wherein the detection dimension in the step S2 includes system project capital, information resource catalog quantity, table data storage quantity, monthly data growth quantity to total quantity ratio, database instance quantity and system user quantity.
7. The method for analyzing the abnormality of the informationized asset data according to claim 6, wherein in step S3, the html page is subjected to detection dimension value selection, the selected latitude value is transmitted to a java background by using js technology, the java background calls a mysql database to perform sql query, and a system conforming to the dimension is queried to be a similar system.
8. The method for analyzing the abnormality of the informative asset data according to claim 7, wherein the detection dimension in the step S3 includes similarity of system name, similarity of system function description, similarity of system common database, similarity of system resource directory and similarity of system supporting business items.
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|---|---|---|---|---|
| CN104866489A (en) * | 2014-02-24 | 2015-08-26 | 赵冰 | System for extracting, storing and releasing selected website content |
| JP2017211858A (en) * | 2016-05-26 | 2017-11-30 | 日本電信電話株式会社 | Security administrative support system and security administrative support method |
| CN111858713A (en) * | 2020-07-21 | 2020-10-30 | 浪潮云信息技术股份公司 | Object-based government information asset management method and system |
| CN111970138A (en) * | 2020-03-31 | 2020-11-20 | 贵州电网有限责任公司 | Network resource management and control system and resource management method |
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- 2020-12-07 CN CN202011415351.0A patent/CN112488895A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104866489A (en) * | 2014-02-24 | 2015-08-26 | 赵冰 | System for extracting, storing and releasing selected website content |
| JP2017211858A (en) * | 2016-05-26 | 2017-11-30 | 日本電信電話株式会社 | Security administrative support system and security administrative support method |
| CN111970138A (en) * | 2020-03-31 | 2020-11-20 | 贵州电网有限责任公司 | Network resource management and control system and resource management method |
| CN111858713A (en) * | 2020-07-21 | 2020-10-30 | 浪潮云信息技术股份公司 | Object-based government information asset management method and system |
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