CN113779108B - Block chain sensitive word detection method - Google Patents
Block chain sensitive word detection method Download PDFInfo
- Publication number
- CN113779108B CN113779108B CN202110995812.4A CN202110995812A CN113779108B CN 113779108 B CN113779108 B CN 113779108B CN 202110995812 A CN202110995812 A CN 202110995812A CN 113779108 B CN113779108 B CN 113779108B
- Authority
- CN
- China
- Prior art keywords
- chain
- sensitive
- sensitive word
- transaction
- words
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 99
- 230000001960 triggered effect Effects 0.000 claims abstract description 4
- 238000000034 method Methods 0.000 claims description 38
- 238000012423 maintenance Methods 0.000 claims description 14
- 230000000977 initiatory effect Effects 0.000 claims description 7
- 238000012545 processing Methods 0.000 claims description 4
- 238000013461 design Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
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
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2471—Distributed queries
-
- 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
- G06F16/23—Updating
-
- 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
-
- 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
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- Business, Economics & Management (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Finance (AREA)
- Accounting & Taxation (AREA)
- Computing Systems (AREA)
- Economics (AREA)
- Software Systems (AREA)
- Probability & Statistics with Applications (AREA)
- Mathematical Physics (AREA)
- Fuzzy Systems (AREA)
- Development Economics (AREA)
- Computational Linguistics (AREA)
- Marketing (AREA)
- Strategic Management (AREA)
- Technology Law (AREA)
- General Business, Economics & Management (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
- Debugging And Monitoring (AREA)
Abstract
The invention discloses a block chain sensitive word detection method. Before a chain member initiates a uplink request, the member performs member sensitive word detection in the sensitive word consensus model, and then each member on the chain performs chain sensitive word detection in the sensitive word consensus model, and different transaction uplink strategies are performed according to detection results; the sensitive word synchronization model may be performed periodically or triggered by a sensitive word consensus model and a transaction uplink policy. On one hand, the invention can avoid the problem of inconsistent discrimination of sensitive words; on the other hand, the flexibility of sensitive word detection can be improved, so that the block chain sensitive word detection capability is improved.
Description
Technical Field
The invention relates to the field of information detection, in particular to a block chain sensitive word detection method.
Background
With the development of the growing popularity of the blockchain technology, the blockchain application is increasing, and the blockchain technology is also getting closer to daily life. By means of the non-tamperable characteristic of the blockchain data, information storage, information sharing and information checking are performed. On the other hand, countries promulgate blockchain information service management regulations in which blockchain applications are required to implement information content security management responsibilities. How to avoid the occurrence of unclean, unhealthy, or even illegal information in the information stored in the blockchain requires that the transaction information be subjected to sensitive word detection prior to the uplink.
The current blockchain sensitive word detection has the following problems: each member in the chain has a sensitive word library, and the problem of inconsistent discrimination among the members of each organization exists for whether a transaction contains sensitive words or not; the unified sensitive word library is used by each member in the chain, so that the problem of inaccuracy of sensitive words is solved, and normal words in some transactions can be judged to be different results by different members in the chain.
Disclosure of Invention
Aiming at the problems, the invention provides a block chain sensitive word detection method capable of improving the compliance and the legality of uplink information.
The invention aims at realizing the following technical scheme:
according to a first aspect of the present invention, there is provided a blockchain sensitive word detection method, comprising:
Detecting the sensitive words through a sensitive word consensus model; the sensitive word consensus model comprises a detection model of member sensitive words and a consensus detection model of chain sensitive words; the member sensitive words are maintained by each member independently, and the sensitive words on the chain are maintained by each member through consensus;
Executing different transaction uplink strategies according to the detection result;
And updating the sensitive word through the sensitive word synchronization model.
Further, the detection flow includes:
before a chain member initiates a transaction uplink request, the member firstly loads a member sensitive word;
The member carries out sensitive word detection on the transaction information in the uplink request to obtain a detection result;
If the detection result is that the sensitive word is included, the detection of the sensitive word on the chain is not carried out; otherwise, the member initiates a transaction uplink request to other members on the chain, and the other members on the chain load sensitive words on the chain;
and the other members perform sensitive word consensus detection on the transaction information in the uplink request to obtain a detection result.
Further, a transaction data area to be detected is designed on the blockchain and is used for storing transaction contents which are detected through member sensitive words and wait for the detection of sensitive word consensus on the chain; the transaction data area to be detected is not disclosed, is opened only in the sensitive word consensus stage, and is newly added, inquired and deleted through intelligent contracts.
Further, when the detection of the member sensitive words is completed and the detection result does not contain the member sensitive words, the chain member uploads the transaction information to be uploaded to the transaction data area to be detected by calling the form of the intelligent contract; each member on the chain loads the sensitive word on the chain by executing the form of the intelligent contract, and whether the transaction information stored in the transaction data area to be detected contains the sensitive word on the chain is detected; each member is identified together, and finally, the detection result of the sensitive word on the chain is determined; processing is performed according to the transaction uplink policy while removing the transaction from the transaction data area to be detected.
Further, a sensitive word data area on the chain is designed on the blockchain and is used for storing sensitive words which need to be loaded by each chain member during the detection of the co-identification of the sensitive words on the chain; the sensitive word data area on the chain is disclosed to all chain members.
Further, the sensitive word synchronization model can be executed at regular time or triggered by the sensitive word consensus model and the transaction uplink policy;
the member sensitive words are updated independently by each chain member;
The sensitive words on the chain are updated through a predictor, or the sensitive word maintenance contract is called by the chain member to update;
When a chain member carries out on-chain sensitive word consensus detection on transaction information, if the detection result of the member is inconsistent with the consensus detection result, the member needs to update the on-chain sensitive word;
When a chain member passes the member sensitive word detection on transaction information but finds that there is a high weight sensitive word on the chain sensitive word consensus detection, the chain member needs to update the member sensitive word.
Further, the chain member may invoke a sensitive word maintenance contract to update and maintain sensitive words on the chain, including:
(1) The contract has a method for adding, deleting, modifying, inquiring and auditing sensitive words, and the new adding, deleting and modifying of the sensitive words can be effective only after the sensitive words are audited;
(2) The sensitive words imported by the contract are object structures and comprise the following attributes: id. Name, industry, source, weight, expiration time;
(3) All chain members can call the new add, delete, modify and query methods in the sensitive word maintenance contract, but the sensitive word auditing method must satisfy that the call address is in the contract whitelist address to call.
Further, the automatic timing acquisition and updating of the sensitive words of the specific content by the sensitive word predictor updates and maintains the sensitive words on the chain, and the method comprises the following steps:
(1) Deploying a sensitive word update contract, the contract comprising a sensitive word update method updateSwf (), the method receiving sensitive word data as parameters;
(2) Deploying a predictor for periodically polling to acquire general or authority-issued sensitive words, and submitting sensitive word data to a sensitive word update contract;
(3) And updateSwf () of the sensitive word update contract sorts the sensitive word data according to the format of the sensitive word object on the chain, marks the source, and compares and updates the sensitive word data with the existing sensitive word on the chain of the same source.
Further, the transaction uplink policy specifically includes:
(1) The transaction detection result is that the member sensitive words are contained: stopping the uplink request, returning uplink failure information, and marking sensitive words in the transaction information;
(2) The transaction detection result is that the member sensitive word is not contained but the chain sensitive word is contained: the chain member initiating the uplink request can select to update the member sensitive word of the chain member;
(3) The transaction detection result is free of member sensitive words and free of chain sensitive words: direct uplink transaction information.
Further, if the detection of the sensitive words on the chain finds that the sensitive words with high weight exist, the occupied weight exceeds the preset value of the strategy, the uplink request is refused, and meanwhile, the chain member initiating the uplink request should update the member sensitive words of the chain member.
According to a second aspect of the present invention there is provided a computer device comprising a memory and a processor, the memory having stored therein computer readable instructions which, when executed by the processor, cause the processor to perform the steps in the blockchain-sensitive word detection method described above.
According to a third aspect of the present invention there is provided a storage medium storing computer readable instructions that when executed by one or more processors cause the one or more processors to perform the steps in the blockchain-sensitive word detection method described above.
The beneficial effects of the invention are as follows: the invention divides the sensitive words into the sensitive words on the chain and the member sensitive words, designs a sensitive word consensus model, a sensitive word synchronous model and a transaction uplink strategy, and can avoid the problem of inconsistent discrimination of the sensitive words on one hand; on the other hand, the flexibility of sensitive word detection can be improved, so that the block chain sensitive word detection capability is improved.
Drawings
FIG. 1 is a flowchart of a method for detecting blockchain sensitive words provided by an embodiment of the present invention;
FIG. 2 is a flow chart of a design of a sensitive word maintenance contract provided by an embodiment of the present invention;
FIG. 3 is a flow chart of a design of a sensitive word predictor provided by an embodiment of the present invention;
Fig. 4 is a schematic diagram of a transaction uplink policy according to an embodiment of the present invention.
Detailed Description
For a better understanding of the technical solution of the present application, the following detailed description of the embodiments of the present application refers to the accompanying drawings.
It should be understood that the described embodiments are merely some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The terminology used in the embodiments of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The block chain sensitive word detection method provided by the embodiment of the invention comprises the following steps: a sensitive word consensus model, a sensitive word synchronization model, and a transaction uplink policy. The flow is as follows: before a chain member initiates a uplink request, the member performs member sensitive word detection in a sensitive word consensus model, and then each member on the chain performs chain sensitive word detection in the sensitive word consensus model. And executing different transaction uplink strategies according to the detection result. The sensitive word synchronization model may be performed periodically or triggered by a sensitive word consensus model and a transaction uplink policy.
(1) Sensitive word consensus model
Sensitive words are divided into chain sensitive words and member sensitive words. The sensitive words on the chain are commonly maintained by each member through consensus, and the sensitive words of the members are independently maintained by each member. The sensitive word consensus model comprises a detection model of member sensitive words and a consensus detection model of chain sensitive words. The detection flow is shown in fig. 1, and specifically comprises the following steps:
before a blockchain member initiates a transaction uplink request, the member firstly loads a member sensitive word;
the member detects the sensitive words of the transaction information in the uplink request to obtain a detection result, wherein the detection result comprises information such as whether the sensitive words are contained, the number of the sensitive words, the position of the sensitive words and the like;
If the sensitive word is included, the detection of the sensitive word on the chain is not carried out; if the sensitive word is not contained, the member initiates a transaction uplink request to other members on the chain, and the other members on the chain load the sensitive word on the chain;
and carrying out sensitive word consensus detection on transaction information in the uplink request by other members to obtain a detection result, wherein the detection result comprises information such as whether sensitive words are contained, the number of the sensitive words, the position and the like.
Specifically:
A data area of 'to-be-detected transaction' is designed, the data area is positioned on a blockchain, and transaction contents which pass member sensitive word detection and wait for sensitive word consensus detection on the chain are stored. The data area is not disclosed, and is only opened in the sensitive word consensus stage, and is newly added, inquired and deleted through intelligent contracts.
The detection model of the member sensitive words is executed by the member which initiates the uplink request, the process of detecting the sensitive words is also completed by the member only, and other members on the chain do not participate.
And when the detection of the member sensitive words is performed and the detection result does not contain the member sensitive words, the chain member uploads the transaction information to be uplinked to a transaction to be detected data area on the blockchain by calling the form of an intelligent contract. And loading the sensitive words on the chain by each member on the chain through executing the intelligent contract, and detecting whether the transaction information stored in the transaction to be detected data area contains the sensitive words on the chain.
The sensitive words on the chain are provided with a plurality of attributes including industry, source, weight, failure time and the like, and the loaded sensitive words, detection methods and the like are determined according to the attributes.
And each member is identified together, and finally, the detection result of the sensitive word on the chain is determined. Processing is performed according to a subsequent transaction uplink policy while removing the transaction from the "to-be-detected transaction" data field.
In the step of detecting the sensitive words in the sensitive word consensus model, there is no requirement on a sensitive word detection algorithm, and any one or more preset types can be used, including a classical AC algorithm and a common DFA algorithm.
(2) Sensitive word synchronization model
And designing an on-chain sensitive word data area which is positioned on the blockchain and stores sensitive words which need to be loaded by each chain member during on-chain sensitive word consensus detection. The data area is disclosed to all chain members, and updated and maintained through intelligent contracts and predictors. The sensitive word synchronization model is the same as the sensitive word consensus model, and is mainly used for on-chain sensitive word synchronization.
The member sensitive words are maintained and updated by each chain member independently, so that each chain member can use different sensitive words conveniently, and the member sensitive words are flexibly adapted to own requirements.
The sensitive words on the chain are commonly maintained by each chain member through consensus, so that consistency is maintained. Therefore, the on-chain sensitive words are stored in the "on-chain sensitive word" data area on the blockchain. The maintenance modes mainly include two modes: one is an intelligent contract, which is maintained by calling the intelligent contract; the other is a propulsor, through which certain general, authority-issued sensitive words can be acquired and updated.
Time of sensitive word synchronization:
1. The member sensitive words are updated independently by the individual chain members.
2. The sensitive words on the chain can be updated automatically and regularly by the propulsor, and the sensitive word maintenance contract can be updated by the chain member.
3. When a chain member carries out on-chain sensitive word consensus detection on transaction information, if the detection result of the member is inconsistent with the consensus detection result, the member needs to update the on-chain sensitive word.
4. When a chain member passes the member sensitive word detection on transaction information but finds that there is a high weight sensitive word on the chain sensitive word consensus detection, the chain member needs to update the member sensitive word.
In one embodiment, the design flow of the sensitive word maintenance contract is shown in fig. 2, specifically:
1. the contracts comprise a sensitive word new adding method, a sensitive word deleting method, a sensitive word modifying method, a sensitive word inquiring method and a sensitive word auditing method, and the new adding, deleting and modifying of the sensitive word can be effective only after the sensitive word auditing method is adopted.
2. The sensitive words transmitted by the contracts are object structures and comprise the following attributes: id. Name, industry, source, weight, expiration time, etc. The id is used for identifying the sensitive words, the name is the content of the sensitive words, the source and industry are used for distinguishing the types of the sensitive words, the weight is used for identifying the importance degree of the sensitive words, and some important sensitive words can be set with large weight, so that various conditions can be processed by matching with the subsequent transaction uplink strategy.
3. All chain members can call the new add, delete, modify and query methods in the sensitive word maintenance contract, but the sensitive word auditing method must satisfy that the call address is in the contract whitelist address to call.
The sensitive word maintenance contract designed by the invention can flexibly and conveniently update and maintain the sensitive words on the chain by each chain member, and ensures the validity and the credibility of the sensitive words through the auditing flow.
In one embodiment, the design flow of the sensitive word predictor is shown in fig. 3, specifically:
a predictor (Oracle) for sensitive word maintenance is designed to obtain and update sensitive words of specific content, such as sensitive words issued by a general or authority.
1. A sensitive word update contract is deployed, the contract containing sensitive word update methods updateSwf (), which receive sensitive word data as parameters.
2. A predictor is deployed which functions to periodically poll for generic or authoritative sensitive words and then submit the sensitive word data to a sensitive word update contract for on-chain sensitive word updates.
3. The updateSwf () method of the sensitive word update contract sorts the sensitive word data according to the format of the sensitive word object on the chain, particularly marks the source, and then compares and updates the sensitive word data with the existing sensitive word on the chain of the same source.
The sensitive word predictive machine designed by the invention can automatically acquire and update the sensitive words of specific contents at fixed time, keep the sensitive words on the chain to meet the latest requirements and reduce the maintenance work of the sensitive words on the chain.
(3) Transaction uplink policy
The transaction uplink strategy is a method for processing an uplink request after a sensitive word detection result is obtained through a sensitive word consensus model. The purpose of the policy is to avoid the occurrence of data containing sensitive words on the chain while maximally satisfying the member's uplink request. The sensitive word consensus model eventually has three results, namely: contains member sensitive words, does not contain member sensitive words but contains on-chain sensitive words, does not contain member sensitive words and does not contain on-chain sensitive words. The general strategy is as follows:
1. The transaction detection result is that the member sensitive words are contained, and because the member sensitive word detection is performed by the chain member initiating the uplink request, the transaction information in the uplink request is described to contain the self-set sensitive words, so that the strategy is designed to stop the uplink request, return the uplink failure information and mark the sensitive words in the transaction information.
2. The transaction detection result is that the method does not contain member sensitive words but contains on-chain sensitive words, and because the on-chain sensitive words are commonly maintained by all members on the chain, the situation that the on-chain sensitive words cannot accurately meet the requirement of a requester for initiating the uplink can occur, so that the strategy is designed as uplink transaction hash information. On one hand, the transaction checking function can be provided, and on the other hand, the problems caused by checking other members on the chain due to the existence of sensitive words in the transaction information can be avoided; at the same time, the chain member that initiated the uplink request may choose to update its own member sensitive word.
3. And if the transaction detection result is that the member sensitive words are not contained and the chain sensitive words are not contained, the transaction information is directly linked.
The above are three results in general, and the following special strategies can be designed:
If the detection of the sensitive words on the chain finds that the sensitive words with high weight exist, the occupied weight exceeds the preset value of the strategy, the uplink request is refused, and meanwhile, the chain member initiating the uplink request should update the member sensitive words of the chain member.
In one embodiment, a computer device is provided, including a memory and a processor, where the memory stores computer readable instructions that, when executed by the processor, cause the processor to perform the steps in the block chain sensitive word detection method in each of the embodiments described above.
In one embodiment, a storage medium storing computer readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps in the block chain sensitive word detection method in each of the embodiments described above is presented. Wherein the storage medium may be a non-volatile storage medium.
Those of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be implemented by a program to instruct related hardware, the program may be stored in a computer readable storage medium, and the storage medium may include: read Only Memory (ROM), random access memory (RAM, random Access Memory), magnetic or optical disk, and the like.
The foregoing description of the preferred embodiment(s) is (are) merely intended to illustrate the embodiment(s) of the present invention, and it is not intended to limit the embodiment(s) of the present invention to the particular embodiment(s) described.
Claims (8)
1. A method for detecting blockchain sensitive words, the method comprising:
Detecting the sensitive words through a sensitive word consensus model; the sensitive word consensus model comprises a detection model of member sensitive words and a consensus detection model of chain sensitive words; the member sensitive words are maintained by each member independently, and the sensitive words on the chain are maintained by each member through consensus;
Executing different transaction uplink strategies according to the detection result;
updating the sensitive word through a sensitive word synchronization model;
The method comprises the steps of designing a transaction data area to be detected on a blockchain, wherein the transaction data area is used for storing transaction contents which are detected through member sensitive words and wait for the consensus detection of the sensitive words on the chain; the transaction data area to be detected is not disclosed, is opened only in the sensitive word consensus stage, and is newly added, inquired and deleted through intelligent contracts;
When the detection of the member sensitive words is finished and the detection result does not contain the member sensitive words, the chain member uploads the transaction information to be uplinked to the transaction data area to be detected by calling the form of intelligent contract; each member on the chain loads the sensitive word on the chain by executing the form of the intelligent contract, and whether the transaction information stored in the transaction data area to be detected contains the sensitive word on the chain is detected; each member is identified together, and finally, the detection result of the sensitive word on the chain is determined; processing is performed according to the transaction uplink policy while removing the transaction from the transaction data area to be detected.
2. The method of claim 1, wherein the detecting process comprises:
before a chain member initiates a transaction uplink request, the member firstly loads a member sensitive word;
The member carries out sensitive word detection on the transaction information in the uplink request to obtain a detection result;
If the detection result is that the sensitive word is included, the detection of the sensitive word on the chain is not carried out; otherwise, the member initiates a transaction uplink request to other members on the chain, and the other members on the chain load sensitive words on the chain;
and the other members perform sensitive word consensus detection on the transaction information in the uplink request to obtain a detection result.
3. The method of claim 1, wherein an on-chain sensitive word data area is designed on the blockchain for storing sensitive words that each chain member needs to load when detecting the on-chain sensitive word consensus; the sensitive word data area on the chain is disclosed to all chain members.
4. The method of claim 1, wherein the sensitive word synchronization model is executed periodically or triggered by a sensitive word consensus model and a transaction uplink policy;
the member sensitive words are updated independently by each chain member;
The sensitive words on the chain are updated through a predictor, or the sensitive word maintenance contract is called by the chain member to update;
When a chain member carries out on-chain sensitive word consensus detection on transaction information, if the detection result of the member is inconsistent with the consensus detection result, the member needs to update the on-chain sensitive word;
When a chain member passes the member sensitive word detection on transaction information but finds that there is a high weight sensitive word on the chain sensitive word consensus detection, the chain member needs to update the member sensitive word.
5. The method of claim 1, wherein the chain member invoking the sensitive word maintenance contract to update and maintain sensitive words on the chain comprises:
(1) The contract has a method for adding, deleting, modifying, inquiring and auditing sensitive words, and the new adding, deleting and modifying of the sensitive words can be effective only after the sensitive words are audited;
(2) The sensitive words imported by the contract are object structures and comprise the following attributes: id. Name, industry, source, weight, expiration time;
(3) All chain members can call the new add, delete, modify and query methods in the sensitive word maintenance contract, but the sensitive word auditing method must satisfy that the call address is in the contract whitelist address to call.
6. The method of claim 1, wherein automatically acquiring and updating the sensitive words of the specific content at regular time by the sensitive word predictor, and updating and maintaining the sensitive words on the chain, comprises:
(1) Deploying a sensitive word update contract, the contract comprising a sensitive word update method updateSwf (), the method receiving sensitive word data as parameters;
(2) Deploying a predictor for periodically polling to acquire general or authority-issued sensitive words, and submitting sensitive word data to a sensitive word update contract;
(3) And updateSwf () of the sensitive word update contract sorts the sensitive word data according to the format of the sensitive word object on the chain, marks the source, and compares and updates the sensitive word data with the existing sensitive word on the chain of the same source.
7. The method according to claim 1, wherein the transaction uplink policy is specifically:
(1) The transaction detection result is that the member sensitive words are contained: stopping the uplink request, returning uplink failure information, and marking sensitive words in the transaction information;
(2) The transaction detection result is that the member sensitive word is not contained but the chain sensitive word is contained: the method comprises the steps that (1) the uplink transaction hash information is obtained, and a chain member initiating a uplink request selects and updates a member sensitive word of the chain member;
(3) The transaction detection result is free of member sensitive words and free of chain sensitive words: direct uplink transaction information.
8. The method of claim 1 wherein if the presence of a high weight sensitive word is detected during detection of the sensitive word on the chain, the uplink request is denied and the member of the chain initiating the uplink request should update its member sensitive word if the weight of the high weight sensitive word exceeds a value preset by the policy.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110995812.4A CN113779108B (en) | 2021-08-27 | 2021-08-27 | Block chain sensitive word detection method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110995812.4A CN113779108B (en) | 2021-08-27 | 2021-08-27 | Block chain sensitive word detection method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113779108A CN113779108A (en) | 2021-12-10 |
| CN113779108B true CN113779108B (en) | 2024-04-19 |
Family
ID=78839594
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110995812.4A Active CN113779108B (en) | 2021-08-27 | 2021-08-27 | Block chain sensitive word detection method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113779108B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110472012A (en) * | 2019-07-19 | 2019-11-19 | 深圳市中农易讯信息技术有限公司 | A kind of block chain sensitivity word treatment method, device, storage medium and equipment |
| CN110502916A (en) * | 2018-05-16 | 2019-11-26 | 苏宁易购集团股份有限公司 | A kind of sensitive data processing method and system based on block chain |
| CN111343142A (en) * | 2020-01-22 | 2020-06-26 | 腾讯科技（深圳）有限公司 | Data processing method and device based on block chain network and storage medium |
| CN112559551A (en) * | 2020-11-25 | 2021-03-26 | 山东浪潮质量链科技有限公司 | Keyword supervision method, device and medium based on block chain |
| CN112700242A (en) * | 2020-12-28 | 2021-04-23 | 山东浪潮质量链科技有限公司 | Method, device and medium for detecting sensitive information of block chain in advance |
-
2021
- 2021-08-27 CN CN202110995812.4A patent/CN113779108B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110502916A (en) * | 2018-05-16 | 2019-11-26 | 苏宁易购集团股份有限公司 | A kind of sensitive data processing method and system based on block chain |
| CN110472012A (en) * | 2019-07-19 | 2019-11-19 | 深圳市中农易讯信息技术有限公司 | A kind of block chain sensitivity word treatment method, device, storage medium and equipment |
| CN111343142A (en) * | 2020-01-22 | 2020-06-26 | 腾讯科技（深圳）有限公司 | Data processing method and device based on block chain network and storage medium |
| CN112559551A (en) * | 2020-11-25 | 2021-03-26 | 山东浪潮质量链科技有限公司 | Keyword supervision method, device and medium based on block chain |
| CN112700242A (en) * | 2020-12-28 | 2021-04-23 | 山东浪潮质量链科技有限公司 | Method, device and medium for detecting sensitive information of block chain in advance |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113779108A (en) | 2021-12-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111478961B (en) | Multi-tenant service calling method and device | |
| US7254578B2 (en) | Concurrency classes for shared file systems | |
| US11347933B1 (en) | Distributed collaborative storage with operational transformation | |
| US20070118572A1 (en) | Detecting changes in data | |
| CN103577483B (en) | The method and system of date storage method and system and data access | |
| CN109379398B (en) | Data synchronization method and device | |
| CN113448862B (en) | Software version testing method and device and computer equipment | |
| CN106021566A (en) | Method, device and system for improving concurrent processing capacity of single database | |
| US20200342008A1 (en) | System for lightweight objects | |
| CN113779108B (en) | Block chain sensitive word detection method | |
| CN112445805A (en) | Data query method and device | |
| US8131884B1 (en) | Reusing system configuration information and metadata for related operations | |
| US8856081B1 (en) | Single retention policy | |
| CN106529281A (en) | Executable file processing method and device | |
| CA3130318A1 (en) | Data acquisition demand processing method and device, computer equipment and storage medium | |
| CN106126708A (en) | A kind of method and apparatus of the file deleting terminal storage | |
| CN105975567B (en) | Method and device for processing internal file of application program | |
| CN107193590A (en) | A kind of anti-root methods based on android | |
| KR20150017925A (en) | A detect system against malicious processes by using the full path of access files | |
| CN116662355A (en) | Marking method for invalid index, storage medium and computer device | |
| CN116303320A (en) | Real-time task management method, device, equipment and medium based on log file | |
| US11308048B2 (en) | Database migration method, apparatus, device, and computer-readable medium | |
| EP0422877A2 (en) | A method for invalidating access plans in a database system | |
| CN110909012B (en) | Method, device, equipment and storage medium for blocking database object | |
| US9626371B2 (en) | Attribute selectable file operation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |