Method and system for processing untrusted person list
By generating a summary data file and fingerprint data file, and using the cloth bird filter and the abstract database for two levels, solve the problem of poor data security, long search time and slow list update in the list of dishonest people, and achieve efficient and efficient and efficient and efficient, and achieve efficient and efficient and efficient, and achieve efficient and efficient and efficient, and achieve efficient and efficient and efficient, and achieve efficient and efficient and efficient, and achieve efficient and efficient, and achieve efficient and efficient and efficient, and achieve efficient and efficient and efficient, and achieve efficient and efficient and efficient, and achieve efficient and efficient and efficient, and achieve efficient and efficient and efficient, and achieve efficient and efficient and efficient, and achieve efficient and efficient and efficient, and achieve efficient and efficient and efficient, and achieve efficient and efficient and efficient, Safety and accurate List of List of Trust.
Patent Information
- Application Number
- CN202411523803.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-29
- Publication Date
- 2025-01-28
AI Technical Summary
In the process of lists of dishonest persons, there are problems such as poor data security, long search time and slow list update speed in the process of lists of dishonest persons.
By obtaining the original dishonor information, generate a summary data file and fingerprint data file, and load the fingerprint data file to the cloth bird filter. The abstract data file is stored to the broken person's summary database. Essence
Under the premise of ensuring data security, improve the finding efficiency of the list of dishonest people, ensure accuracy, and support the fast update of the list of people who have a fast update.
Smart Images
Figure CN119377264A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of dishonest person identification, and in particular to a method and system for processing a dishonest person list. Background Art
[0002] At present, my country has implemented "restriction measures for dishonest persons". The civil aviation booking system receives the dishonest person list sent by the Civil Aviation Administration and conducts dishonest person checks during the ticket sales process: if the passenger is on the dishonest person list, the ticket sales will be intercepted and the ticket issuance will be terminated. This will implement the requirement that dishonest persons are prohibited from boarding airplanes.
[0003] The currently known technical solutions are: the relevant departments regularly publish a list of dishonest persons, in which the dishonest persons' information is transmitted in plain text; the civil aviation reservation system loads the list of dishonest persons into a relational database; when searching, the SQL select statement is used to query the dishonest persons in the database with the current passenger information as the query condition; and finally the judgment result of whether the current passenger is a dishonest person is returned.
[0004] This technical solution mainly has the following problems:
[0005] (1) Poor data security. The information of dishonest persons includes personal information of citizens, such as ID card number, etc. The information of dishonest persons is required to be kept confidential. Transmission and storage in plain text may lead to data security issues such as data leakage.
[0006] (2) Long search time. When searching for dishonest persons, it is required that no one should be missed and everyone should be checked; it is also required to be efficient and fast, and be able to determine whether the passenger is on the dishonest person list in the shortest possible time. Using a solution based on relational database search, each booking and ticketing request needs to go through a database query to determine whether the passenger is on the dishonest person list. For the application scenario of civil aviation tickets, more than 99% of the passengers who book and issue tickets are not dishonest persons; however, according to the existing technical solution, they still need to go through a database search. This causes high database access pressure and long time consumption, and ultimately leads to a longer response time for the civil aviation booking system.
[0007] (3) The list is updated slowly. To add someone to the list of dishonest persons or remove someone from the list of dishonest persons, multiple transmission and loading steps are required before the update takes effect. The list of dishonest persons is updated slowly. Summary of the invention
[0008] In view of the above problems, the present disclosure provides a method for processing a list of dishonest persons, the method comprising:
[0009] Obtain original information of defaulters;
[0010] Based on the original information of the defaulter, a summary data file and a fingerprint data file are generated;
[0011] Loading the fingerprint data file into the first cuckoo filter, and storing the summary data file into the defaulter summary database;
[0012] Use the First Cuckoo Filter and the Dishonest Person Summary Database to search for current personnel.
[0013] Preferably, the fingerprint data file is generated based on the original information of the defaulter, including:
[0014] Establishing the initial second cuckoo filter;
[0015] The original information of the defaulter is entered into the initial second cuckoo filter to obtain the original fingerprint data file of the defaulter.
[0016] Preferably, based on the original information of the defaulter, a summary data file is generated, including:
[0017] Obtaining the original characteristic code of the defaulter according to the original information of the defaulter;
[0018] Calculate the original characteristic code of the defaulter by using a digest algorithm to obtain a digest value;
[0019] The summary data file is generated based on the summary value.
[0020] Preferably, searching the current person using the first cuckoo filter and the defaulter summary database includes:
[0021] Get current personnel information;
[0022] Use the first cuckoo filter to perform a primary search on the current personnel information and obtain the primary search result;
[0023] Based on the primary search result, the summary database is used to perform a secondary search on the current personnel information to obtain the secondary search result.
[0024] Preferably, the first cuckoo filter is used to perform a primary search on the current personnel information to obtain the primary search result, including:
[0025] Enter the current personnel information into the first cuckoo filter;
[0026] Run the first cuckoo filter and output the first-level search results;
[0027] If the first-level search result is 0, the current person is released;
[0028] If the first-level search result is 1, a second-level search is performed.
[0029] Preferably, based on the primary search result, a secondary search is performed on the current personnel information using the summary database to obtain the secondary search result, including:
[0030] Use summary algorithm to calculate current personnel information and obtain summary data;
[0031] Perform secondary search on summary data through summary database and output secondary search result;
[0032] If the secondary search result is 0, the current person is released;
[0033] If the secondary search result is 1, the current person is on the list of dishonest persons and is intercepted.
[0034] Preferably, the method further comprises:
[0035] Manage the list of dishonest persons through the dishonest person management interface on the First Cuckoo Filter and the dishonest person summary database;
[0036] The management includes adding or removing the defaulter information in the first cuckoo filter and the defaulter summary database.
[0037] The present disclosure also provides a system for processing a list of dishonest persons, the system comprising:
[0038] The acquisition module is used to obtain the original information of the defaulter;
[0039] A generation module, used to generate a summary data file and a fingerprint data file based on the original defaulter information;
[0040] A loading and storing module, used for loading the fingerprint data file into the first cuckoo filter, and storing the summary data file into the defaulter summary database;
[0041] The search module is used to search for the current person using the first cuckoo filter and the defaulter summary database.
[0042] Preferably, the generating module generates the fingerprint data file based on the original defaulter information, including:
[0043] The generating module establishes an initial second cuckoo filter;
[0044] The original information of the defaulter is entered into the initial second cuckoo filter to obtain the original fingerprint data file of the defaulter.
[0045] Preferably, the generating module generates a summary data file based on the original information of the defaulter, including:
[0046] Obtaining the original characteristic code of the defaulter according to the original information of the defaulter;
[0047] Calculate the original characteristic code of the defaulter by using a digest algorithm to obtain a digest value;
[0048] The summary data file is generated based on the summary value.
[0049] Preferably, the search module is used to search the current person using the first cuckoo filter and the defaulter summary database, including:
[0050] The search module is used to obtain the current personnel information;
[0051] Use the first cuckoo filter to perform a primary search on the current personnel information and obtain the primary search result;
[0052] Based on the primary search result, the summary database is used to perform a secondary search on the current personnel information to obtain the secondary search result.
[0053] Preferably, the first cuckoo filter is used to perform a primary search on the current personnel information to obtain the primary search result, including:
[0054] Enter the current personnel information into the first cuckoo filter;
[0055] Run the first cuckoo filter and output the first-level search results;
[0056] If the first-level search result is 0, the current person is released;
[0057] If the first-level search result is 1, a second-level search is performed.
[0058] Preferably, based on the primary search result, a secondary search is performed on the current personnel information using the summary database to obtain the secondary search result, including:
[0059] Use summary algorithm to calculate current personnel information and obtain summary data;
[0060] Perform secondary search on summary data through summary database and output secondary search result;
[0061] If the secondary search result is 0, the current person is released;
[0062] If the secondary search result is 1, the current person is on the list of dishonest persons and is intercepted.
[0063] Preferably, the system further comprises:
[0064] A management module, used to manage the list of dishonest persons on the first cuckoo filter and the dishonest person summary database through the dishonest person management interface;
[0065] The management includes adding or removing the defaulter information in the first cuckoo filter and the defaulter summary database.
[0066] The present disclosure has the following beneficial effects:
[0067] (1) The present disclosure pre-processes the information of dishonest persons, obtains fingerprint data files and summary data files after one-way irreversible processing of plain text, and uses fingerprint data files and summary data files for subsequent transmission and storage, avoiding the use of plain text, and realizing the transmission and storage of the dishonest person list under the premise of ensuring data security. This method can effectively protect the privacy data of dishonest users and avoid the risk of data leakage;
[0068] (2) The present disclosure adopts a two-level search mechanism of cuckoo filter + database, which effectively reduces the search time and ensures accuracy. With the help of cuckoo filter as the first-level search, most of them are released "quickly". For "suspects" that cannot be accurately judged by the first-level search, the second-level search based on the database is used to achieve "precise" identification;
[0069] (3) The present disclosure provides a method for quickly updating the list of dishonest persons, allowing maintenance operations to be performed on dishonest persons, which takes effect immediately without waiting. The supported maintenance operations include adding and removing dishonest persons.
[0070] Other features and advantages of the present disclosure will be described in the following description, and partly become apparent from the description, or be understood by implementing the present disclosure. The purpose and other advantages of the present disclosure can be realized and obtained by the structures indicated in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS
[0071] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.
[0072] Figure 1 A diagram showing a method for processing a list of dishonest persons in an embodiment of the present disclosure;
[0073] Figure 2 A detailed flow chart of the method for processing the list of dishonest persons in the embodiment of the present disclosure is shown;
[0074] Figure 3 A system diagram showing the processing of the list of dishonest persons in an embodiment of the present disclosure;
[0075] Figure 4A diagram showing a device for processing a list of dishonest persons in an embodiment of the present disclosure. DETAILED DESCRIPTION
[0076] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as being limited to the examples set forth herein; on the contrary, these embodiments are provided so that the present disclosure will be more comprehensive and complete, and the concepts of the example embodiments are fully conveyed to those skilled in the art. The described features, structures, or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced while omitting one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known technical solutions are not shown or described in detail to avoid obscuring various aspects of the present disclosure.
[0077] In addition, the accompanying drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware units or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.
[0078] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the steps. For example, some steps may be decomposed, while some steps may be combined or partially combined, so the actual execution order may change according to the actual situation.
[0079] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein, for example.
[0080] In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or sub-modules is not necessarily limited to those steps or sub-modules explicitly listed, but may include other steps or sub-modules not explicitly listed or inherent to these processes, methods, products, or apparatuses.
[0081] like Figure 1As shown, the present disclosure proposes a method for processing a list of dishonest persons, the method comprising:
[0082] Obtain original information of defaulters;
[0083] Based on the original information of the defaulter, a summary data file and a fingerprint data file are generated;
[0084] Loading the fingerprint data file into the first cuckoo filter, and storing the summary data file into the defaulter summary database;
[0085] Use the First Cuckoo Filter and the Dishonest Person Summary Database to search for current personnel.
[0086] Furthermore, based on the original information of the defaulter, the fingerprint data file is generated, including:
[0087] Establishing the initial second cuckoo filter;
[0088] The original information of the defaulter is entered into the initial second cuckoo filter to obtain the original fingerprint data file of the defaulter.
[0089] Furthermore, based on the original information of the defaulter, a summary data file is generated, including:
[0090] Obtaining the original characteristic code of the defaulter according to the original information of the defaulter;
[0091] Calculate the original characteristic code of the defaulter by using a digest algorithm to obtain a digest value;
[0092] The summary data file is generated based on the summary value.
[0093] Furthermore, the first cuckoo filter and the defaulter summary database are used to search for the current person, including:
[0094] Get current personnel information;
[0095] Use the first cuckoo filter to perform a primary search on the current personnel information and obtain the primary search result;
[0096] Based on the primary search result, the summary database is used to perform a secondary search on the current personnel information to obtain the secondary search result.
[0097] Furthermore, the first cuckoo filter is used to perform a primary search on the current personnel information to obtain a primary search result, including:
[0098] Enter the current personnel information into the first cuckoo filter;
[0099] Run the first cuckoo filter and output the first-level search results;
[0100] If the first-level search result is 0, the current person is released;
[0101] If the first-level search result is 1, a second-level search is performed.
[0102] Further, based on the primary search result, a secondary search is performed on the current personnel information using the summary database to obtain the secondary search result, including:
[0103] Use summary algorithm to calculate current personnel information and obtain summary data;
[0104] Perform secondary search on summary data through summary database and output secondary search result;
[0105] If the secondary search result is 0, the current person is released;
[0106] If the secondary search result is 1, the current person is on the list of dishonest persons and is intercepted.
[0107] Furthermore, the method further comprises:
[0108] Manage the list of dishonest persons through the dishonest person management interface on the First Cuckoo Filter and the dishonest person summary database;
[0109] The management includes adding or removing the defaulter information in the first cuckoo filter and the defaulter summary database.
[0110] The detailed technical solution of this disclosure is as follows Figure 2 As shown in the figure:
[0111] 1. Input the information of dishonest persons: input the original information of dishonest persons; call the second cuckoo filter; call summary data generation.
[0112] 2. Second Cuckoo Filter: Cuckoo filter for data preprocessing. Required operations: filter creation: cf.reserve; element addition: cf.addnx; support data export: cf.scandump.
[0113] 3. Fingerprint data export: Export the data in the second cuckoo filter as a fingerprint data file.
[0114] 4. Summary data generation: used to pre-process the original information of defaulters and generate summary data files; for each information of defaulters, use the summary algorithm to calculate and obtain its summary value; and record the summary value in the summary data file.
[0115] 5. Dishonest person management interface: manage the data in the first cuckoo filter and the dishonest person summary database; management operations include: add and remove.
[0116] 6. Fingerprint data import: read the fingerprint data file; load the data into the first cuckoo filter.
[0117] 7. Summary data import: read the summary data file; load the data into the defaulter summary database.
[0118] 8. The first cuckoo filter: a cuckoo filter that supports the search and addition and deletion of dishonest persons. Required operations: element existence: cf.exists; element addition: cf.addnx; element deletion: cf.del; data import: cf.loadchunk.
[0119] 9. Dishonest person summary database: A database that stores dishonest person summary information. Required operations: Insert: add a new dishonest person summary to the database; Delete: remove a dishonest person from the database; Query: determine whether a person is on the dishonest person list.
[0120] 10. Dishonest person search interface: for business system to call; to determine whether a given passenger is on the list of dishonest persons.
[0121] The present disclosure adopts a cuckoo filter and a digest algorithm to pre-process the original information of the defaulter, thereby avoiding plaintext transmission and plaintext storage.
[0122] Fingerprint data:
[0123] Based on the second cuckoo filter, the information of the defaulter is preprocessed to obtain fingerprint data.
[0124] First, the plaintext data is inserted into the cuckoo filter, and then the fingerprint data in the cuckoo filter is saved, which realizes the one-way processing of the original plaintext information and prevents others from knowing the plaintext of the defaulter. The exported fingerprint data is written into a file. This file is then transmitted and imported into the first cuckoo filter for defaulter search.
[0125] Summary data:
[0126] Use the summary algorithm to pre-process the original information of the defaulter to obtain summary data;
[0127] The summary data is stored in the summary data file. The summary data file is transmitted and imported into the defaulter summary database for defaulter search.
[0128] In the present disclosure, a two-level search mechanism of cuckoo filter + database is adopted, which effectively reduces the time consumption of search and ensures accuracy at the same time. This mechanism can determine with certainty whether a certain passenger is a dishonest person. Using the cuckoo filter as the primary search means, the passengers who are not dishonest persons, who account for the vast majority, can be accurately identified and quickly and directly released; for the suspected dishonest persons found in the primary search, a secondary search is carried out: by searching the dishonest person summary database, accurate identification is achieved.
[0129] First level search:
[0130] Use Cuckoo Filter as a primary lookup method.
[0131] The vast majority of people who are not on the list of dishonest persons can be confirmed as not being on the list simply by going through the Cuckoo filter.
[0132] The cuckoo filter has the characteristic of fast search. Using the cuckoo filter as the first-level search can achieve "fast" release of the majority.
[0133] Secondary search:
[0134] For suspected defaulters who were not released in the first-level search, accurate judgments are made based on the summary database to ensure the accuracy of the final results.
[0135] In this disclosure, a method for quickly updating a dishonest person is provided, allowing the management agency to perform maintenance operations on the dishonest person, and the operation takes effect immediately without waiting. The supported operations include adding a dishonest person and removing a dishonest person.
[0136] Increase:
[0137] Adding elements to the cuckoo filter
[0138] Removed:
[0139] Remove elements from the cuckoo filter.
[0140] Compared with Bloom filter, the advantages of Cuckoo filter include: support for element deletion.
[0141] If a Bloom filter is used, elements cannot be deleted.
[0142] The original use scenario of the present disclosure is the processing of the list of dishonest persons in the civil aviation reservation system. The present disclosure can also be applied to scenarios such as railways and banks that require similar processing of the list of dishonest persons.
[0143] In the present disclosure, the implementation of the cuckoo filter can be redis stack or other components with the same function. The component functional requirements are: implement the cuckoo hash algorithm; provide add, del, scandump, loadchunk and other interfaces required by this technical solution;
[0144] The defaulter summary database can be implemented as a relational database or redis set. This database is a data management program with search function;
[0145] The digest algorithm used to generate the digest data includes SM3, MD5, etc. Other algorithms that can achieve one-way irreversible processing and avoid conflicts can be used as substitutes.
[0146] Example 1: Based on redis stack
[0147] Use redis stack's cuckoo filter as the cuckoo filter.
[0148] The set of redis stack is used as the summary database of defaulters.
[0149] 1. Fingerprint data file generation (fingerprint_file)
[0150] S1. Create the second cuckoo filter
[0151] CF.RESERVE blacklist capacity[BUCKETSIZE bucketsize][MAXITERATI ONSmaxiterations][EXPANSION expansion], where: capacity is a required parameter, and its value is capacity = n*f / α, where n is the number of defaulters; f is the fingerprint length, which is fixed to 8; α is the filling factor, which is set to 0.9. bucketsize, maxiterations, expansion, etc. are optional parameters, and their values are (2, 20, 1) respectively.
[0152] S2. Write capacity, bucketsize, maxiterations, and expansion to the file fingerprint_file: fingerprint data file;
[0153] S3. Start pre-processing of information of dishonest persons;
[0154] S4. Perform the following operations on each defaulter;
[0155] S5. Get the original information of the next defaulter: <name, ID type, ID number>;
[0156] S6. Calculate the defaulter feature code item: concatenate name + ID type + ID number in sequence;
[0157] S7. Write the item to the second cuckoo filter: CF.ADDNX blacklist item;
[0158] S8. Repeat S4 until all defaulters have been processed;
[0159] S9. Start exporting fingerprint data;
[0160] S10. Execute CF.SCANDUMP on the second cuckoo filter to obtain iterator and Data;
[0161] S11. Write iterator and Data to file fingerprint_file: fingerprint data file;
[0162] S12. If iterator is not equal to 0, execute S10;
[0163] S13. If iterator is equal to 0, the fingerprint data export is completed;
[0164] S14. Record the final file fingerprint_file: fingerprint data file.
[0165] 2. Digest data file generation (digest_file)
[0166] S1. For each defaulter, perform the following operations;
[0167] S2. Obtain the original information of the next defaulter: <name, ID type, ID number>;
[0168] S3. Calculate the defaulter feature code item: concatenate name + ID type + ID number in sequence;
[0169] S4. Use the national secret algorithm SM3 to calculate the digest of item;
[0170] S5. Write the digest into digest_file: digest data file;
[0171] S6. Repeat S2 until all defaulters have been dealt with;
[0172] S7. Record the final file digest_file: summary data file.
[0173] 3. Import fingerprint data
[0174] S1. Receive file fingerprint_file: fingerprint data file;
[0175] S2. Read the first line from fingerprint_file: capacity, bucketsize, maxiterations, expansion;
[0176] S3. Create the first cuckoo filter CF.RESERVE blacklist capacity[BUCKETSIZEbucketsize][MAXITERATIONS maxiterations][EXPANSION expansion], where capacity, bucketsize, maxiterations, and expansion are the values read in the previous step;
[0177] S4. Read the next line from fingerprint_file: get iterator and data;
[0178] S5. Write data to the second cuckoo filter: CF.loadchunk blacklist iterator data;
[0179] S6. If iterator is not equal to 0, execute S3;
[0180] S7. If iterator is equal to 0, the fingerprint data import is completed.
[0181] 4. Summary data import
[0182] S1. Receive file digest_file: digest data file;
[0183] S2. Read the next line from digest_file: get digest;
[0184] S3. Write digest into the defaulter summary database: sadd blacklist_set digest;
[0185] S4. If the file is not read completely, execute S2;
[0186] S5. If the file is read completely, the process ends.
[0187] 5. Find the person who has lost his credibility
[0188] S1. Receive a defaulter search request. The request parameters include: <name, ID type, ID number>;
[0189] S2. Start the first level search;
[0190] S3. Calculate the defaulter feature code item: concatenate name + ID type + ID number in sequence;
[0191] S4. Use CF.EXISTS blacklist item for the first cuckoo filter;
[0192] S5. If the result is 0, the final return result is whitelist release;
[0193] S6. If the result is 1, perform a secondary search;
[0194] S7. Start secondary search;
[0195] S8. Use the national secret algorithm SM3 to obtain the digest of item. ;
[0196] S9. Check whether the digest exists in the defaulter summary database: execute sismember blacklist_setdigest;
[0197] S10. If the result is 0, the final return result is whitelist release;
[0198] S11. If the result is 1, the final return result is that the defaulter is intercepted.
[0199] 6. Adding dishonest people
[0200] S1. Receive a request to add a defaulter. The request parameters include: <name, certificate type, certificate number>;
[0201] S2. Calculate the personal feature code item: concatenate name + ID type + ID number in sequence;
[0202] S3. Modify the first cuckoo filter: execute CF.ADDNX blacklist item;
[0203] S4. Use the national secret algorithm SM3 to calculate the digest of item;
[0204] S5. Modify the defaulter summary database: execute sadd blacklist_set digest;
[0205] S6. Addition completed.
[0206] 7. Remove dishonest people
[0207] S1. Receive a request to remove a dishonest person. The request parameters include: <name, certificate type, certificate number>;
[0208] S2. Calculate the personal feature code item: concatenate name + ID type + ID number in sequence;
[0209] S3. Modify the first cuckoo filter: execute CF.DEL blacklist item;
[0210] S4. Use the national secret algorithm SM3 to calculate the digest of item;
[0211] S5. Modify the blacklist summary database: execute smove blacklist_set digest;
[0212] S6. Removal completed.
[0213] Example 2: Based on redis stack + relational database
[0214] Compared with Example 1, the defaulter summary database adopts the relational database Ocean Base instead.
[0215] 8. Summary data import
[0216] S1. Create a relational table blacklist to store dishonest persons;
[0217] S2. Receive file digest_file: summary data file;
[0218] S3. Read the next line from digest_file: get digest;
[0219] S4. Write the digest into the defaulter summary database: Use the SQL insert statement to insert the digest into the defaulter table blacklist;
[0220] S5. If the file is not completely read, execute S3;
[0221] S6. If the file is read completely, the process ends.
[0222] 9. Find the person who has lost his credibility
[0223] S1. Receive a defaulter search request. The request parameters include: <name, ID type, ID number>;
[0224] S2. Start the first level search;
[0225] S3. Calculate the defaulter feature code item: concatenate name + ID type + ID number in sequence;
[0226] S4. Use CF.EXISTS blacklist item for the first cuckoo filter;
[0227] S5. If the result is 0, the final return result is whitelist release;
[0228] S6. If the result is 1, perform a secondary search;
[0229] S7. Start secondary search;
[0230] S8. Use the national secret algorithm SM3 to obtain the digest of item;
[0231] S9. Check whether digest exists in the defaulter summary database: execute SQL select statement, select * from blacklist where digest_colomn = digest;
[0232] S10. If the result set contains 0 records, the final returned result is whitelist release;
[0233] S11. If the result is not 0 records, the final returned result is the defaulter interception.
[0234] 10. Adding dishonest persons
[0235] S1. Receive a request to add a defaulter. The request parameters include: <name, certificate type, certificate number>;
[0236] S2. Calculate the personal feature code item: concatenate name + ID type + ID number in sequence;
[0237] S3. Modify the first cuckoo filter: execute CF.ADDNX blacklist item;
[0238] S4. Use the national secret algorithm SM3 to calculate the digest of item;
[0239] S5. Modify the defaulter summary database: execute the SQL insert statement, insert into blacklistvalues(digest);
[0240] S6. Addition completed.
[0241] 11. Remove dishonest people
[0242] S1. Receive a request to remove a dishonest person. The request parameters include: <name, certificate type, certificate number>;
[0243] S2. Calculate the personal feature code item: concatenate name + ID type + ID number in sequence;
[0244] S3. Modify the first cuckoo filter: execute CF.DEL blacklist item;
[0245] S4. Use the national secret algorithm SM3 to calculate the digest of item;
[0246] S5. Modify the defaulter summary database: execute sql delete statement, delete from blacklist where digest_column = digest;
[0247] S6. Removal completed.
[0248] Example 3: Digest algorithm uses md5
[0249] Compared with Example 1, the digest algorithm is changed from SM3 to md5.
[0250] 12. digest_file (digest data file) generation
[0251] S1. Traverse each defaulter and perform the following operations;
[0252] S2. Obtain the original information of the next defaulter: <name, ID type, ID number>;
[0253] S3. Calculate the defaulter feature code item: concatenate name + ID type + ID number in sequence;
[0254] S4. Use the digest algorithm md5 to calculate the digest of the item;
[0255] S5. Write the digest into digest_file: digest data file;
[0256] S6. Repeat S2 until all defaulters have been dealt with;
[0257] S7. Record the final file digest_file: summary data file.
[0258] 13. Find the person who has lost his credibility
[0259] S1. Receive a defaulter search request. The request parameters include: <name, ID type, ID number>;
[0260] S2. Start the first level search;
[0261] S3. Calculate the defaulter feature code item: concatenate name + ID type + ID number in sequence;
[0262] S4. Use CF.EXISTS blacklist item for the first cuckoo filter;
[0263] S5. If the result is 0, the final return result is whitelist release;
[0264] S6. If the result is 1, perform a secondary search;
[0265] S7. Start secondary search;
[0266] S8. Use the digest algorithm md5 to obtain the digest of the item;
[0267] S9. Check whether the digest exists in the defaulter summary database: execute sismember blacklist_setdigest;
[0268] S10. If the result is 0, the final return result is whitelist release;
[0269] S11. If the result is 1, the final return result is that the defaulter is intercepted.
[0270] 14. Adding dishonest persons
[0271] S1. Receive a request to add a defaulter. The request parameters include: <name, certificate type, certificate number>;
[0272] S2. Calculate the personal feature code item: concatenate name + ID type + ID number in sequence;
[0273] S3. Modify the first cuckoo filter: execute CF.ADDNX blacklist item;
[0274] S7. Use the digest algorithm md5 to calculate the digest of the item;
[0275] S6. Modify the defaulter summary database: execute sadd blacklist_set digest;
[0276] S7. Addition completed.
[0277] 15. Remove dishonest people
[0278] S1. Receive a request to remove a dishonest person. The request parameters include: <name, certificate type, certificate number>;
[0279] S2. Calculate the personal feature code item: concatenate name + ID type + ID number in sequence;
[0280] S3. Modify the first cuckoo filter: execute CF.DEL blacklist item;
[0281] S4. Use the digest algorithm md5 to calculate the digest of the item;
[0282] S8. Modify the blacklist summary database: execute smove blacklist_set digest;
[0283] S5. Removal completed.
[0284] like Figure 3 As shown, the present disclosure also proposes a system for processing a list of dishonest persons, the system comprising:
[0285] The acquisition module is used to obtain the original information of the defaulter;
[0286] A generation module, used to generate a summary data file and a fingerprint data file based on the original defaulter information;
[0287] A loading and storing module, used for loading the fingerprint data file into the first cuckoo filter, and storing the summary data file into the defaulter summary database;
[0288] The search module is used to search for the current person using the first cuckoo filter and the defaulter summary database.
[0289] Furthermore, the system further comprises:
[0290] A management module, used to manage the list of dishonest persons on the first cuckoo filter and the dishonest person summary database through the dishonest person management interface;
[0291] The management includes adding or removing the defaulter information in the first cuckoo filter and the defaulter summary database.
[0292] like Figure 4 As shown, corresponding to the method for processing the list of dishonest persons provided above, the present disclosure also provides a device for processing the list of dishonest persons. Since the embodiment of the device is similar to the above method embodiment, the description is relatively simple. Please refer to the description of the above method embodiment for relevant points. The device described below is only schematic. The device may include: a processor 1, a memory 2 and a communication bus (i.e., the above device bus) and a search engine, wherein the processor 1 and the memory 2 communicate with each other through the communication bus and communicate with the outside through the communication interface. The processor 1 can call the logic instructions in the memory 2 to execute the method for processing the list of dishonest persons.
[0293] In addition, the logic instructions in the above-mentioned memory 2 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present disclosure is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present disclosure. The aforementioned storage medium includes: a storage chip, a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a disk or an optical disk, and other media that can store program codes.
[0294] On the other hand, an embodiment of the present disclosure further provides a processor-readable storage medium, on which a computer program 3 is stored. When the computer program 3 is executed by the processor 1, the method for processing the list of defaulters provided in the above embodiments is implemented.
[0295] The processor-readable storage medium can be any available medium or data storage device that can be accessed by the processor 1, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (such as CD, DVD, BD, HVD, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NANDFLASH), solid-state drive (SSD)), etc.
[0296] Those skilled in the art should understand that although the present disclosure is described in detail with reference to the aforementioned embodiments, it is still possible to modify the technical solutions recorded in the aforementioned embodiments, or to make equivalent replacements for some of the technical features therein; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure.
Claims
1. A method for processing a list of dishonest persons, characterized in that: The method comprises: Obtain original information of defaulters; Based on the original information of the defaulter, a summary data file and a fingerprint data file are generated; Loading the fingerprint data file into the first cuckoo filter, and storing the summary data file into the defaulter summary database; Use the First Cuckoo Filter and the Dishonest Person Summary Database to search for current personnel.
2. The method for processing the list of dishonest persons according to claim 1, characterized in that: Based on the original information of the defaulter, the fingerprint data file is generated, including: Establishing the initial second cuckoo filter; The original information of the defaulter is entered into the initial second cuckoo filter to obtain the original fingerprint data file of the defaulter.
3. The method for processing the list of dishonest persons according to claim 1, characterized in that: Based on the original information of the defaulter, a summary data file is generated, including: Obtaining the original characteristic code of the defaulter according to the original information of the defaulter; Calculate the original characteristic code of the defaulter by using a digest algorithm to obtain a digest value; The summary data file is generated based on the summary value.
4. The method for processing the list of dishonest persons according to claim 1, characterized in that: Use the First Cuckoo Filter and the Dishonest Person Summary Database to search for current personnel, including: Get current personnel information; Use the first cuckoo filter to perform a primary search on the current personnel information and obtain the primary search result; Based on the primary search result, the summary database is used to perform a secondary search on the current personnel information to obtain the secondary search result.
5. The method for processing the list of dishonest persons according to claim 1, characterized in that: Use the first cuckoo filter to perform a primary search on the current personnel information and obtain the primary search results, including: Enter the current personnel information into the first cuckoo filter; Run the first cuckoo filter and output the first-level search results; If the first-level search result is 0, the current person is not a dishonest person and is released directly; If the first-level search result is 1, it means that the person is a suspected person and the second-level search will continue.
6. The method for processing the list of dishonest persons according to claim 4, characterized in that: Based on the primary search results, the summary database is used to perform a secondary search on the current personnel information to obtain the secondary search results, including: Use summary algorithm to calculate current personnel information and obtain summary data; Perform secondary search on summary data through summary database and output secondary search result; If the secondary search result is 0, the current person is released; If the secondary search result is 1, the current person is on the list of dishonest persons and is intercepted.
7. The method for processing the list of dishonest persons according to claim 1, characterized in that: The method further comprises: Manage the list of dishonest persons through the dishonest person management interface on the First Cuckoo Filter and the dishonest person summary database; The management includes adding or removing the defaulter information in the first cuckoo filter and the defaulter summary database.
8. A system for processing a list of dishonest persons, characterized in that: The system comprises: The acquisition module is used to obtain the original information of the defaulter; A generation module, used to generate a summary data file and a fingerprint data file based on the original defaulter information; A loading and storing module, used for loading the fingerprint data file into the first cuckoo filter, and storing the summary data file into the defaulter summary database; The search module is used to search for the current person using the first cuckoo filter and the defaulter summary database.
9. The system for processing the list of dishonest persons according to claim 8, characterized in that: A generation module generates the fingerprint data file based on the original defaulter information, including: The generating module establishes an initial second cuckoo filter; The original information of the defaulter is entered into the initial second cuckoo filter to obtain the original fingerprint data file of the defaulter.
10. The system for processing the list of dishonest persons according to claim 8, characterized in that: A generation module generates a summary data file based on the original defaulter information, including: Obtaining the original characteristic code of the defaulter according to the original information of the defaulter; Calculate the original characteristic code of the defaulter by using a digest algorithm to obtain a digest value; The summary data file is generated based on the summary value.
11. The system for processing the list of dishonest persons according to claim 8, characterized in that: The search module is used to search the current person using the first cuckoo filter and the defaulter summary database, including: The search module is used to obtain the current personnel information; Use the first cuckoo filter to perform a primary search on the current personnel information and obtain the primary search result; Based on the primary search result, the summary database is used to perform a secondary search on the current personnel information to obtain the secondary search result.
12. The system for processing the list of dishonest persons according to claim 11, characterized in that: Use the first cuckoo filter to perform a primary search on the current personnel information and obtain the primary search results, including: Enter the current personnel information into the first cuckoo filter; Run the first cuckoo filter and output the first-level search results; If the first-level search result is 0, the current person is released; If the first-level search result is 1, a second-level search is performed.
13. The system for processing the list of dishonest persons according to claim 11, characterized in that: Based on the primary search results, the summary database is used to perform a secondary search on the current personnel information to obtain the secondary search results, including: Use summary algorithm to calculate current personnel information and obtain summary data; Perform secondary search on summary data through summary database and output secondary search result; If the secondary search result is 0, the current person is released; If the secondary search result is 1, the current person is on the list of dishonest persons and is intercepted.
14. The system for processing the list of dishonest persons according to claim 9, characterized in that: The system further comprises: A management module, used to manage the list of dishonest persons on the first cuckoo filter and the dishonest person summary database through the dishonest person management interface; The management includes adding or removing the defaulter information in the first cuckoo filter and the defaulter summary database.