CN116627987A - Data distribution storage method, storage medium and related equipment based on noise hash - Google Patents

Data distribution storage method, storage medium and related equipment based on noise hash Download PDF

Info

Publication number
CN116627987A
CN116627987A CN202310670853.5A CN202310670853A CN116627987A CN 116627987 A CN116627987 A CN 116627987A CN 202310670853 A CN202310670853 A CN 202310670853A CN 116627987 A CN116627987 A CN 116627987A
Authority
CN
China
Prior art keywords
noise
server
data packet
region
service data
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.)
Pending
Application number
CN202310670853.5A
Other languages
Chinese (zh)
Inventor
洪宇坤
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Bank of China Ltd
Original Assignee
Bank of China Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Bank of China Ltd filed Critical Bank of China Ltd
Priority to CN202310670853.5A priority Critical patent/CN116627987A/en
Publication of CN116627987A publication Critical patent/CN116627987A/en
Pending legal-status Critical Current

Links

Classifications

    • 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
    • G06F16/22—Indexing; Data structures therefor; Storage structures
    • G06F16/2228—Indexing structures
    • G06F16/2255—Hash tables
    • 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
    • G06F16/2455—Query execution
    • 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
    • G06F21/602—Providing cryptographic facilities or services
    • 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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Software Systems (AREA)
  • Databases & Information Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Health & Medical Sciences (AREA)
  • Bioethics (AREA)
  • General Health & Medical Sciences (AREA)
  • Computer Hardware Design (AREA)
  • Computer Security & Cryptography (AREA)
  • Computational Linguistics (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

The data distribution storage method, the storage medium and the related equipment based on noise hash can be applied to the big data field or the financial field. The present disclosure is applied to a first regional server provided with a noise sensor. The noise sensor collects the noise digital signals converted by the hardware noise of the regional server, and because the hardware noise belonging to the physical source is difficult to be overcome by the third party object, the target connection information obtained after the business key words based on the noise digital signals and the business data packets are spliced has special encryption performance, and on the basis, the target hash codes after the hash processing of the target connection information are used for carrying out association matching with the regional server, so that the encryption of the whole data distribution and storage process is realized, the storage position of the data to be stolen is difficult to be accurately positioned by the third party object, and the safety of data storage is improved.

Description

Data distribution storage method, storage medium and related equipment based on noise hash
Technical Field
The disclosure relates to the field of big data, and in particular relates to a data distribution storage method, a storage medium and related equipment based on noise hash.
Background
In order to facilitate the customers to transact banking business, most banks are provided with banking outlets in various areas to provide business transacting services for the customers. For some larger-scale regions, banks will also distribute a corresponding number of servers for those regions so that data collected by banking sites in those regions can be stored in the corresponding servers.
However, since the data is stored in a centralized manner, third party objects except clients and banks easily attack servers in specific areas, so that data in the servers are stolen in a centralized manner, and the security of the data storage is seriously affected.
Therefore, how to effectively improve the security of data storage is a technical problem that needs to be solved by those skilled in the art.
Disclosure of Invention
In view of the foregoing, the present disclosure provides a data allocation and storage method, a storage medium and related devices based on noise hashing, which overcome or at least partially solve the foregoing problems, and the technical solutions are as follows:
a data distribution storage method based on noise hash, which is applied to a first regional server, wherein the first regional server is provided with a noise sensor, the method comprises the following steps:
Acquiring a service keyword in a service data packet uploaded by a website server;
collecting hardware noise of the first regional server by using the noise sensor, and converting the hardware noise into a corresponding noise digital signal;
splicing the business keywords with the noise digital signals to generate target connection information;
carrying out hash processing on the target connection information to obtain a target hash code;
determining a second regional server with a mapping relation with the target hash code;
and transmitting the service data packet to the second region server, so that the second region server stores the service data packet after receiving the service data packet, generates storage region information corresponding to the service data packet, and uploads the storage region information to the core server.
Optionally, the collecting, by using the noise sensor, the hardware noise of the first regional server, and converting the hardware noise into a corresponding noise digital signal, includes:
and starting the noise sensor to collect hardware noise of the first regional server in real time within a preset collection time period, and converting the hardware noise into a corresponding noise digital signal.
Optionally, before the determining the second region server having the mapping relationship with the target hash code, the method further includes:
and obtaining a region hash mapping table issued by the core server, wherein the region hash mapping table records the mapping relation between region codes and the region server.
Optionally, the determining a second region server having a mapping relationship with the target hash code includes:
extracting a region code in the target hash code;
and inquiring a second region server with a mapping relation with the region code in the region hash mapping table.
Optionally, the obtaining the service keyword in the service data packet uploaded by the website server includes:
identifying transaction information in a service data packet uploaded by a website server;
and carrying out keyword retrieval in the transaction information to obtain the service keywords.
Optionally, after the transmitting the service data packet to the second regional server, the method further includes:
acquiring a data query request corresponding to the service data packet sent by a user;
sending the data query request to the core server;
Acquiring the storage area information corresponding to the service data packet and fed back by the core server;
and guiding the user to inquire the service data packet at the second region server according to the stored region information.
Optionally, the banking website corresponding to the website server is located in the area corresponding to the first area server.
A noise hash based data distribution storage device for use with a first regional server provided with a noise sensor, the device comprising: a business key word obtaining unit, a noise digital signal obtaining unit, a target connection information generating unit, a target hash code obtaining unit, a mapping relation determining unit and a business data packet transmission unit,
the service keyword obtaining unit is used for obtaining the service keywords in the service data packet uploaded by the website server;
the noise digital signal obtaining unit is used for collecting hardware noise of the first regional server by using the noise sensor and converting the hardware noise into a corresponding noise digital signal;
the target connection information generating unit is used for splicing the business keywords with the noise digital signals to generate target connection information;
The target hash code obtaining unit is used for carrying out hash processing on the target connection information to obtain a target hash code;
the mapping relation determining unit is used for determining a second regional server with a mapping relation with the target hash code;
the service data packet transmission unit is configured to transmit the service data packet to the second area server, so that the second area server stores the service data packet after receiving the service data packet, generates storage area information corresponding to the service data packet, and uploads the storage area information to the core server.
A computer-readable storage medium having stored thereon a program which, when executed by a processor, implements the noise hash-based data allocation storage method of any of the above.
An electronic device comprising at least one processor, and at least one memory, bus connected to the processor; the processor and the memory complete communication with each other through the bus; the processor is configured to invoke the program instructions in the memory to perform the noise hash-based data allocation storage method of any of the above.
By means of the technical scheme, the data distribution storage method, the storage medium and the related equipment based on noise hash can be applied to the big data field or the financial field. The present disclosure is applied to a first regional server provided with a noise sensor. The method and the system can obtain the service keywords in the service data packet uploaded by the website server; collecting hardware noise of a first regional server by using a noise sensor, and converting the hardware noise into a corresponding noise digital signal; splicing the business keywords with the noise digital signals to generate target connection information; carrying out hash processing on the target connection information to obtain a target hash code; determining a second regional server with a mapping relation with the target hash code; and transmitting the service data packet to a second region server, so that the second region server stores the service data packet after receiving the service data packet, generates storage region information corresponding to the service data packet, and uploads the storage region information to the core server. The noise sensor collects the noise digital signals converted by the hardware noise of the regional server, and because the hardware noise belonging to the physical source is difficult to be overcome by the third party object, the target connection information obtained after the business key words based on the noise digital signals and the business data packets are spliced has special encryption performance, and on the basis, the target hash codes after the hash processing of the target connection information are used for carrying out association matching with the regional server, so that the encryption of the whole data distribution and storage process is realized, the storage position of the data to be stolen is difficult to be accurately positioned by the third party object, and the safety of data storage is improved.
The foregoing description is merely an overview of the technical solutions of the present disclosure, and may be implemented according to the content of the specification in order to make the technical means of the present disclosure more clearly understood, and in order to make the above and other objects, features and advantages of the present disclosure more clearly understood, the following specific embodiments of the present disclosure are specifically described.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the disclosure. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
FIG. 1 is a schematic flow chart of a method for storing data based on noise hash according to an embodiment of the disclosure;
FIG. 2 is a flow chart illustrating another implementation of a data allocation and storage method based on noise hashing according to an embodiment of the present disclosure;
FIG. 3 is a schematic flow chart of another embodiment of a data allocation and storage method based on noise hashing according to an embodiment of the present disclosure;
FIG. 4 is a schematic flow chart of another embodiment of a data allocation and storage method based on noise hashing according to an embodiment of the present disclosure;
FIG. 5 is a flow chart illustrating another implementation of a data allocation and storage method based on noise hashing according to an embodiment of the present disclosure;
fig. 6 illustrates a schematic structural diagram of a data allocation storage device based on noise hash according to an embodiment of the present disclosure;
fig. 7 shows a schematic structural diagram of an electronic device provided by an embodiment of the disclosure.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Currently, most banks have banking outlets distributed in various regions to provide convenient business handling services for customers. In practical cases, banks can deploy a website server matched with the number of banking websites in each region, so that data collected by the banking websites can be uploaded to corresponding region servers nearby through the website server. However, this results in that third party objects other than clients and banks easily launch attacks against regional servers in specific regions, steal data in regional servers, and seriously affect the security of data storage.
Although the data random storage mode can be used for scrambling the data storage position to a certain extent, the third party objects except the clients and banks are likely to finish invasion and monitor the data before the data distribution storage stage, and the monitored data are spliced to form complete transaction information, so that the data distribution storage mode is broken, the regional server where the target data are located is located and attacked, and the target data in the regional server are stolen.
In order to solve the technical problems, the embodiment of the disclosure provides a data distribution and storage method based on noise hash, which can realize encryption of the whole data distribution and storage process, effectively prevent third party objects from stealing data, and ensure the security of data storage.
The data distribution and storage method based on noise hash provided by the embodiment of the disclosure can be applied to a first regional server, and the first regional server is provided with a noise sensor.
The regional server is a server which is deployed in advance by a bank for any region. In a general case, the regional server is used for collecting banking data of a website server corresponding to each banking website in the region. The website server is a server which is deployed corresponding to any banking website. The website server is used for collecting banking business data generated by corresponding banking website.
The noise sensor is a sound sensor for receiving hardware noise. The noise sensor may support a digital output sensor. The noise sensor may convert the hardware noise into a corresponding digital signal after receiving the hardware noise.
As shown in fig. 1, a flow chart of an implementation manner of a data allocation and storage method based on noise hash according to an embodiment of the present disclosure may include:
s100, obtaining the service keywords in the service data packet uploaded by the website server.
The business data packet mainly comprises transaction information generated by banking outlets. Alternatively, the transaction information may include a transaction type, a serial number, and a transaction amount.
Wherein, the business keywords are keywords for characterizing the theme of the transaction information. For example: "running water on the same day" and "loan on the same day". The embodiment of the disclosure can preset one or more corresponding business keywords aiming at any transaction information theme so as to identify the business keywords in the business data packet, thereby obtaining the business keywords in the business data packet uploaded by the website server.
Optionally, the banking website corresponding to the website server is located in the area corresponding to the first area server.
It can be understood that, in a normal case, after the service data packet is collected by the website server corresponding to the banking website in each region, the service data packet is collected to the regional server corresponding to the region. According to the embodiment of the disclosure, the service data packets collected by the website servers in the local area are collected, so that the subsequent unified data distribution and storage of the service data packets of all the banking websites in the same area are facilitated.
S200, collecting hardware noise of the first regional server by using the noise sensor, and converting the hardware noise into corresponding noise digital signals.
The hardware noise is noise generated when the component hardware inside the first regional server runs. Specifically, the embodiment of the disclosure can collect the hardware noise inside the first regional server in real time by using the noise sensor, and convert the hardware noise into a corresponding digital signal in real time. According to the embodiment of the disclosure, the hardware noise which can be acquired in real time through the noise sensor arranged at the first regional server is beneficial to timely acquiring the digital signal under the condition that the data distribution and storage requirement appears, so that the connection information can be generated later.
And S300, splicing the business keywords with the noise digital signals to generate target connection information.
The target connection information is a character string formed by combining the service keywords and the noise digital signals. The embodiment of the disclosure can perform data splicing operation on the business keywords and the noise digital signals, and splice the business keywords and the noise digital signals into target connection information. Specifically, the embodiment of the disclosure may input the service keyword and the noise digital signal into the seed generator, and the target connection information generated by the seed generator is used as hashed input data. According to the embodiment of the disclosure, the target connection information is obtained by splicing the service keywords and the noise digital signals, so that the target connection information comprises random noise which is provided by a physical source and is difficult to attack by a third party object, the third party object is prevented from splicing the content in the service data packet in a monitoring mode, the data distribution storage mode is prevented from being cracked, and the safety of data storage is effectively improved.
S400, carrying out hash processing on the target connection information to obtain a target hash code.
Specifically, according to the embodiment of the disclosure, the target connection information can be subjected to hash processing through a hash algorithm, so that the target hash code is obtained. The hash algorithm is to convert an input with any length (also called as pre-mapping pre-image) into an output with a fixed length through the hash algorithm, and the output is a hash value. This transformation is a compressed mapping, i.e. the hash value is typically much smaller in space than the input, different inputs may be hashed to the same output, so it is not possible to determine a unique input value from the hash value (unidirectional, irreversible). Simply stated, a function of compressing messages of arbitrary length to a message digest of a fixed length.
Alternatively, the hash algorithm may be embodied as MD5 algorithm or SHA256 algorithm.
S500, determining a second regional server with a mapping relation with the target hash code.
The embodiment of the disclosure can pre-construct the mapping relation between the hash code and the regional server and store the mapping relation in the regional server. Specifically, the embodiment of the disclosure may query the second regional server having a mapping relationship with the target hash code by using the target hash code as a query condition.
According to the embodiment of the disclosure, the regional server with the mapping relation with the hash code is determined, and the service data packet can be distributed to the designated regional server for storage. The mapping relation between the hash codes and the regional servers can be dynamically adjusted, so that the effect of randomly storing the service data packets is realized. Because the business data packets collected by the servers in a certain area are randomly distributed to the servers in each area, if a third party object wants to steal the transaction information in a certain area, compared with the situation that one area server is cracked, the calculation force required by cracking a plurality of area servers is exponentially increased, the difficulty of the third party object in intensively stealing the data in a certain area is greatly increased, and the safety of the data can be effectively ensured.
And S600, transmitting the service data packet to a second region server, so that the second region server stores the service data packet after receiving the service data packet, generates storage region information corresponding to the service data packet, and uploads the storage region information to the core server.
Wherein the storage region information is used for indicating the storage position of the service data packet. The core server can record the storage area information so that when the service data packet needs to be queried later, the core server queries a second area server for storing the service data packet, and then queries the transaction information in the service data packet at the second area server.
The data distribution storage method based on noise hash can be applied to the field of big data or the field of finance. The present disclosure is applied to a first regional server provided with a noise sensor. The method and the system can obtain the service keywords in the service data packet uploaded by the website server; collecting hardware noise of a first regional server by using a noise sensor, and converting the hardware noise into a corresponding noise digital signal; splicing the business keywords with the noise digital signals to generate target connection information; carrying out hash processing on the target connection information to obtain a target hash code; determining a second regional server with a mapping relation with the target hash code; and transmitting the service data packet to a second region server, so that the second region server stores the service data packet after receiving the service data packet, generates storage region information corresponding to the service data packet, and uploads the storage region information to the core server. The noise sensor collects the noise digital signals converted by the hardware noise of the regional server, and because the hardware noise belonging to the physical source is difficult to be overcome by the third party object, the target connection information obtained after the business key words based on the noise digital signals and the business data packets are spliced has special encryption performance, and on the basis, the target hash codes after the hash processing of the target connection information are used for carrying out association matching with the regional server, so that the encryption of the whole data distribution and storage process is realized, the storage position of the data to be stolen is difficult to be accurately positioned by the third party object, and the safety of data storage is improved.
In the practical application process, in order to reasonably utilize the computing resources and energy sources of the regional server, the noise sensor is not normally set in a normally open state. Therefore, in order to avoid occupying excessive computing resources and also in order to save energy, the operation of the noise sensor can be controlled according to the actual service data packet allocation storage requirement.
Optionally, based on the method shown in fig. 1, as shown in fig. 2, a flowchart of another implementation of the data allocation and storage method based on noise hash according to the embodiment of the present disclosure may include:
s210, starting a noise sensor to collect hardware noise of the first regional server in real time within a preset collection time period, and converting the hardware noise into a corresponding noise digital signal.
The regional server can generate a starting instruction of the noise sensor under the condition that the service data packet uploaded by the website server is obtained, so that the noise sensor responds to the starting instruction to collect hardware noise of the first regional server in real time within a preset collection time period.
The preset acquisition time length can be set according to actual requirements. After the noise sensor works for a preset acquisition time period, the noise sensor can automatically resume the sleep state.
According to the embodiment of the disclosure, the service data packet is obtained as the trigger starting signal of the noise sensor, so that the noise sensor can be reasonably started to collect hardware noise of the first regional server within the preset collection time period, and therefore calculation resources and energy sources of the first regional server are reasonably utilized to complete collection work of noise digital signals, random noise required by subsequent hash processing is provided, and meanwhile, resource utilization efficiency of the first regional server is improved.
Optionally, before step S500, the embodiment of the present disclosure may further obtain a region hash map issued by the core server, where the region hash map records a mapping relationship between a region code and the region server.
The core server is responsible for managing and coordinating the servers in all areas. In the core server, a region hash mapping table may be made for recording the association relationship between the region code in the hash code and the region server. The core server may transmit the prepared region hash map to each region server, so that the region server allocates the region server to which the service data packet is to be stored according to the region hash map.
The association relationship between the region codes and the region servers in the region hash mapping table provided by the embodiment of the disclosure can be dynamically adjusted, so that the effect of randomly storing the service data packets is realized. According to the embodiment of the disclosure, the storage positions of the business data packets are distributed through the regional hash mapping table, so that the storage positions of the data are difficult to accurately position by a third party object, the difficulty of stealing the data is increased, and the safety of the data is effectively ensured.
Optionally, the embodiment of the present disclosure may preset characters at fixed code positions in the hash code to be region codes, so that a region server storing an association relationship with the region codes in the region hash mapping table is queried with the region codes as query conditions. For example: the embodiment of the disclosure can select the first 2 bits in the hash code as the region code, construct the association relationship between the region code and the region server, and record the association relationship in the region hash mapping table.
Optionally, based on the method shown in fig. 1, as shown in fig. 3, a flowchart of another implementation of the data allocation and storage method based on noise hash according to the embodiment of the present disclosure may include:
s510, extracting the region code in the target hash code.
Specifically, the embodiment of the disclosure can locate the target code position in the target hash code, extract the characters on the target code position, and obtain the region code in the target hash code.
S520, a second region server with a mapping relation with the region code is queried in the region hash mapping table.
Specifically, the embodiment of the disclosure may query the region code in the region hash mapping table, and determine a second region server having a mapping relationship with the region code.
According to the embodiment of the disclosure, the region codes in the target hash codes are queried in the region hash mapping table, and the second region server with the mapping relation with the region codes can be accurately determined, so that the service data packet corresponding to the target hash codes is distributed to the second region server for storage, the data security risk caused by centralized storage of the data in the same region is avoided, and the security of data storage is effectively ensured.
In practical cases, the website server may collect transaction information generated by banking website, package the transaction information into a service data packet, and transmit the service data packet to a corresponding regional server.
Optionally, based on the method shown in fig. 1, as shown in fig. 4, a flowchart of another implementation of the data allocation and storage method based on noise hash according to the embodiment of the present disclosure may include:
s110, identifying transaction information in the service data packet uploaded by the website server.
Specifically, the embodiment of the disclosure can analyze the service data packet uploaded by the website server, so as to identify the transaction information in the service data packet.
S120, keyword retrieval is carried out in the transaction information, and service keywords are obtained.
The embodiment of the disclosure can search the preset business keywords one by one in the transaction information, thereby searching the business keywords in the transaction information.
According to the embodiment of the disclosure, the business keywords in the business information are searched, so that the business information subject corresponding to the business data packet can be determined, the business data packet of the same business information subject can be stored in the same regional server later, and the data can be managed conveniently.
Optionally, based on the method shown in fig. 1, as shown in fig. 5, a flowchart of another implementation of the data allocation and storage method based on noise hash according to the embodiment of the present disclosure may further include, after step S600:
s700, obtaining a data query request corresponding to the service data packet sent by the user.
S710, sending the data query request to the core server.
S720, obtaining storage area information corresponding to the service data packet and fed back by the core server.
And S730, guiding the user to inquire the service data packet at the second regional server according to the stored regional information.
When any bank website wants to inquire a service data packet, a data inquiry request corresponding to the service data packet can be sent to a regional server of a region to which the bank website belongs, and the regional server sends the data inquiry request to a core server. After receiving the data query request, the core server queries the storage area information corresponding to the service data packet, and feeds back the storage area information to the area server, so that the area server can query the service data packet on the area server guided by the storage area information.
The embodiment of the disclosure can provide a service data packet inquiring function based on the storage area information stored by the core server, so that after noise hash processing and mapping distribution storage, banking outlets can still inquire and manage related transaction information.
Although operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. In certain circumstances, multitasking and parallel processing may be advantageous.
It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order and/or performed in parallel. Furthermore, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
Corresponding to the above method embodiments, the present disclosure further provides a data allocation storage device based on noise hash, where the data allocation storage device based on noise hash is applied to a first regional server, and the first regional server is provided with a noise sensor. The structure of the data allocation storage device based on noise hash is shown in fig. 6, and may include: a traffic key obtaining unit 100, a noise digital signal obtaining unit 200, a target connection information generating unit 300, a target hash code obtaining unit 400, a mapping relation determining unit 500, and a traffic packet transmitting unit 600.
The service key obtaining unit 100 is configured to obtain a service key in a service data packet uploaded by a website server.
The noise digital signal obtaining unit 200 is configured to collect hardware noise of the first regional server by using the noise sensor, and convert the hardware noise into a corresponding noise digital signal.
The target connection information generating unit 300 is configured to splice the service keyword and the noise digital signal to generate target connection information.
The target hash code obtaining unit 400 is configured to perform hash processing on the target connection information to obtain a target hash code.
The mapping relation determining unit 500 is configured to determine a second region server having a mapping relation with the target hash code.
The service data packet transmission unit 600 is configured to transmit the service data packet to the second area server, so that the second area server stores the service data packet after receiving the service data packet, generates storage area information corresponding to the service data packet, and uploads the storage area information to the core server.
Optionally, the noise digital signal obtaining unit 200 is specifically configured to start the noise sensor to collect, in real time, the hardware noise of the first regional server within a preset collection duration, and convert the hardware noise into a corresponding noise digital signal.
Optionally, the data allocation storage device based on noise hash may further include: and a region hash map obtaining unit.
And a region hash map obtaining unit, configured to obtain a region hash map issued by the core server before the mapping relationship determining unit 500 determines a second region server having a mapping relationship with the target hash code, where the region hash map records a mapping relationship between a region code and a region server.
Optionally, the mapping relation determining unit 500 may include: the region code extraction subunit and the mapping relation query subunit.
A region code extraction subunit, configured to extract a region code in the target hash code;
and the mapping relation inquiring subunit is used for inquiring a second region server which has a mapping relation with the region code in the region hash mapping table.
Optionally, the service keyword obtaining unit 100 may include: the transaction information identification subunit and the service keyword acquisition subunit.
The transaction information identification subunit is used for identifying transaction information in the service data packet uploaded by the website server;
and the business keyword obtaining subunit is used for carrying out keyword retrieval in the transaction information to obtain business keywords.
Optionally, the data allocation storage device based on noise hash may further include: the system comprises a data query request acquisition unit, a data query request transmission unit, a storage area information acquisition unit and a guide query unit.
And a data query request obtaining unit, configured to obtain a data query request corresponding to the service data packet sent by the user after the service data packet transmission unit 600 transmits the service data packet to the second regional server.
And the data query request sending unit is used for sending the data query request to the core server.
And the storage area information obtaining unit is used for obtaining the storage area information corresponding to the service data packet and fed back by the core server.
And the guiding and inquiring unit is used for guiding the user to inquire the service data packet at the second region server according to the stored region information.
Optionally, the banking website corresponding to the website server is located in the area corresponding to the first area server.
The data distribution storage device based on noise hash can be applied to the field of big data or the field of finance. The present disclosure is applied to a first regional server provided with a noise sensor. The method and the system can obtain the service keywords in the service data packet uploaded by the website server; collecting hardware noise of a first regional server by using a noise sensor, and converting the hardware noise into a corresponding noise digital signal; splicing the business keywords with the noise digital signals to generate target connection information; carrying out hash processing on the target connection information to obtain a target hash code; determining a second regional server with a mapping relation with the target hash code; and transmitting the service data packet to a second region server, so that the second region server stores the service data packet after receiving the service data packet, generates storage region information corresponding to the service data packet, and uploads the storage region information to the core server. The noise sensor collects the noise digital signals converted by the hardware noise of the regional server, and because the hardware noise belonging to the physical source is difficult to be overcome by the third party object, the target connection information obtained after the business key words based on the noise digital signals and the business data packets are spliced has special encryption performance, and on the basis, the target hash codes after the hash processing of the target connection information are used for carrying out association matching with the regional server, so that the encryption of the whole data distribution and storage process is realized, the storage position of the data to be stolen is difficult to be accurately positioned by the third party object, and the safety of data storage is improved.
The specific manner in which the individual units perform the operations in relation to the apparatus of the above embodiments has been described in detail in relation to the embodiments of the method and will not be described in detail here.
The data distribution storage device based on noise hash includes a processor and a memory, the above-mentioned service key obtaining unit 100, noise digital signal obtaining unit 200, target connection information generating unit 300, target hash code obtaining unit 400, mapping relation determining unit 500, service data packet transmitting unit 600, and the like are all stored as program units in the memory, and the processor executes the above-mentioned program units stored in the memory to implement the corresponding functions.
The processor includes a kernel, and the kernel fetches the corresponding program unit from the memory. The kernel can set one or more than one, collect noise digital signals converted from hardware noise of the regional server based on the noise sensor by adjusting kernel parameters, so that target connection information obtained after the noise digital signals are spliced with service keywords of the service data packet has special encryption performance, and on the basis, target hash codes obtained after hash processing of the target connection information are used for carrying out association matching with the regional server, encryption of the whole data distribution and storage process is realized, the storage position of data to be stolen is difficult to accurately position by a third party object, and the safety of data storage is improved.
Embodiments of the present disclosure provide a computer-readable storage medium having a program stored thereon, which when executed by a processor, implements the noise hash-based data allocation storage method.
The embodiment of the disclosure provides a processor for running a program, wherein the data distribution storage method based on noise hash is executed when the program runs.
As shown in fig. 7, an embodiment of the present disclosure provides an electronic device 1000, the electronic device 1000 comprising at least one processor 1001, and at least one memory 1002, bus 1003 connected to the processor 1001; wherein, the processor 1001 and the memory 1002 complete communication with each other through the bus 1003; the processor 1001 is configured to call program instructions in the memory 1002 to perform the above-described data allocation storage method based on noise hashing. The electronic device herein may be a server, a PC, a PAD, a mobile phone, etc.
The present disclosure also provides a computer program product adapted to perform a program that is initialized with the steps of a noisy hash-based data allocation storage method when executed on an electronic device.
It should be noted that, the data distribution storage method, the storage medium and the related device based on noise hash provided by the present disclosure may be used in the big data field or the financial field. The foregoing is merely an example, and is not intended to limit the application fields of the data distribution storage method, the storage medium and the related devices based on noise hash provided in the present disclosure.
The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus, electronic devices (systems), and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, the electronic device includes one or more processors (CPUs), memory, and a bus. The electronic device may also include input/output interfaces, network interfaces, and the like.
The memory may include volatile memory, random Access Memory (RAM), and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM), among other forms in computer readable media, the memory including at least one memory chip. Memory is an example of a computer-readable medium.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
In the description of the present disclosure, it should be understood that, if the directions or positional relationships indicated by the terms "upper", "lower", "front", "rear", "left" and "right", etc., are based on the directions or positional relationships shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the positions or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limitations of the present disclosure.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. It should also be noted that 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 one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises an element.
It will be appreciated by those skilled in the art that embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
The foregoing is merely exemplary of the present disclosure and is not intended to limit the present disclosure. Various modifications and variations of this disclosure will be apparent to those skilled in the art. Any modifications, equivalent substitutions, improvements, or the like, which are within the spirit and principles of the present disclosure, are intended to be included within the scope of the claims of the present disclosure.

Claims (10)

1. A data distribution storage method based on noise hashing, which is applied to a first regional server, wherein the first regional server is provided with a noise sensor, the method comprising:
acquiring a service keyword in a service data packet uploaded by a website server;
collecting hardware noise of the first regional server by using the noise sensor, and converting the hardware noise into a corresponding noise digital signal;
splicing the business keywords with the noise digital signals to generate target connection information;
carrying out hash processing on the target connection information to obtain a target hash code;
determining a second regional server with a mapping relation with the target hash code;
and transmitting the service data packet to the second region server, so that the second region server stores the service data packet after receiving the service data packet, generates storage region information corresponding to the service data packet, and uploads the storage region information to the core server.
2. The method of claim 1, wherein the capturing hardware noise of the first regional server with the noise sensor and converting the hardware noise into a corresponding noise digital signal comprises:
and starting the noise sensor to collect hardware noise of the first regional server in real time within a preset collection time period, and converting the hardware noise into a corresponding noise digital signal.
3. The method of claim 1, wherein prior to said determining a second locale server having a mapping relationship with the target hash code, the method further comprises:
and obtaining a region hash mapping table issued by the core server, wherein the region hash mapping table records the mapping relation between region codes and the region server.
4. The method of claim 3, wherein the determining a second locale server having a mapping relationship with the target hash code comprises:
extracting a region code in the target hash code;
and inquiring a second region server with a mapping relation with the region code in the region hash mapping table.
5. The method of claim 1, wherein obtaining the service key in the service data packet uploaded by the mesh point server comprises:
identifying transaction information in a service data packet uploaded by a website server;
and carrying out keyword retrieval in the transaction information to obtain the service keywords.
6. The method of claim 1, wherein after said transmitting said service data packet to said second regional server, said method further comprises:
acquiring a data query request corresponding to the service data packet sent by a user;
sending the data query request to the core server;
acquiring the storage area information corresponding to the service data packet and fed back by the core server;
and guiding the user to inquire the service data packet at the second region server according to the stored region information.
7. The method of any one of claims 1 to 6, wherein the banking outlets to which the outlet servers correspond are located in the region to which the first region servers correspond.
8. A data distribution storage device based on noise hashing, characterized by being applied to a first regional server provided with a noise sensor, the device comprising: a business key word obtaining unit, a noise digital signal obtaining unit, a target connection information generating unit, a target hash code obtaining unit, a mapping relation determining unit and a business data packet transmission unit,
The service keyword obtaining unit is used for obtaining the service keywords in the service data packet uploaded by the website server;
the noise digital signal obtaining unit is used for collecting hardware noise of the first regional server by using the noise sensor and converting the hardware noise into a corresponding noise digital signal;
the target connection information generating unit is used for splicing the business keywords with the noise digital signals to generate target connection information;
the target hash code obtaining unit is used for carrying out hash processing on the target connection information to obtain a target hash code;
the mapping relation determining unit is used for determining a second regional server with a mapping relation with the target hash code;
the service data packet transmission unit is configured to transmit the service data packet to the second area server, so that the second area server stores the service data packet after receiving the service data packet, generates storage area information corresponding to the service data packet, and uploads the storage area information to the core server.
9. A computer-readable storage medium having a program stored thereon, wherein the program when executed by a processor implements the noise hash-based data distribution storage method according to any one of claims 1 to 7.
10. An electronic device comprising at least one processor, and at least one memory, bus connected to the processor; the processor and the memory complete communication with each other through the bus; the processor is configured to invoke program instructions in the memory to perform the noise hash-based data allocation storage method of any of claims 1 to 7.
CN202310670853.5A 2023-06-07 2023-06-07 Data distribution storage method, storage medium and related equipment based on noise hash Pending CN116627987A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310670853.5A CN116627987A (en) 2023-06-07 2023-06-07 Data distribution storage method, storage medium and related equipment based on noise hash

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310670853.5A CN116627987A (en) 2023-06-07 2023-06-07 Data distribution storage method, storage medium and related equipment based on noise hash

Publications (1)

Publication Number Publication Date
CN116627987A true CN116627987A (en) 2023-08-22

Family

ID=87602448

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310670853.5A Pending CN116627987A (en) 2023-06-07 2023-06-07 Data distribution storage method, storage medium and related equipment based on noise hash

Country Status (1)

Country Link
CN (1) CN116627987A (en)

Similar Documents

Publication Publication Date Title
CN111274268B (en) Internet of things data transmission method and device, medium and electronic equipment
CN111752799A (en) Service link tracking method, device, equipment and storage medium
CN104144142B (en) A kind of Web bug excavation methods and system
CN103532754A (en) System and method for high-speed memory and distributed type processing of massive logs
CN112015674A (en) Cache resource access method and device based on multiple hierarchies and computer equipment
CN110083391A (en) Call request monitoring method, device, equipment and storage medium
CN109657107B (en) Terminal matching method and device based on third-party application
CN110505495B (en) Multimedia resource frame extraction method, device, server and storage medium
US11494403B2 (en) Method and apparatus for storing off-chain data
CN108052649A (en) The data managing method and its system of a kind of distributed file system
CN113296981A (en) Data processing method and device, electronic equipment and storage medium
CN110515803B (en) Processing method and device for log message and electronic equipment
CN117171108A (en) Virtual model mapping method and system
CN102685222A (en) Cloud storage resource management device for power system
CN116627987A (en) Data distribution storage method, storage medium and related equipment based on noise hash
CN115168310A (en) Log management method, device, medium and system in LDAP system
CN114070787A (en) Police service big data oriented data aggregation method and device, storage medium and electronic equipment
CN115221125A (en) File processing method and device, electronic equipment and readable storage medium
CN112765600A (en) Control method for collecting automatic synchronization CMDB based on HIDS intrusion detection
CN112910988A (en) Resource acquisition method and resource scheduling device
CN112015707A (en) Log data collection method and log data collection system
CN108075932B (en) Data monitoring method and device
CN115865862B (en) Data access method, system, device, electronic equipment and storage medium
CN110677403A (en) Sound detection data chaining method and device of Internet of things applying block chains
CN118264546A (en) Log recording method and device based on gateway

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