CPE nameplate data generation and management method

Abstract

The invention relates to the technical field of nameplate data management, in particular to a CPE nameplate data generation and management method, which comprises the following steps of: uniformly converting an IMEI (International Mobile Equipment Identity) field, an MAC (Media Access Control) address and a serial number into integers, and comparing the integers with a prefix character set bit by bit to establish bucket ciphertext mapping, so as to form a comparison baseline which can be directly positioned according to a bucket number and a field bit sequence; the uniqueness and level-to-level management precision of a data generation stage are improved, an uploading permission is generated through an index state and a preset condition and is bound with a batch number and an order number, addition and threshold judgment are executed in a ciphertext domain in combination with homomorphic encryption, the data exposure risk caused by plaintext expansion is avoided, coexistence of batch state calculation and high-strength security is realized, and the data processing efficiency is improved. The abnormal record is further identified through the isolated forest algorithm, the abnormal detection precision and the response speed are improved, the completeness of batch filing and the high efficiency of subsequent tracing are ensured, and the data security, the retrieval efficiency and the management controllability in a large-scale production scene are enhanced.

Description

Technical Field

[0001] This invention relates to the field of nameplate data management technology, and in particular to a method for generating and managing CPE nameplate data. Background Technology

[0002] The field of nameplate data management technology mainly involves the unified generation, encryption processing, verification, storage management, batch statistics, export, and printing of nameplate data for communication terminal equipment. The goal is to achieve standardized generation and centralized management of IMEI, MAC address, serial number, and SSID identification data through software and server interaction, thereby improving the consistency, security, and traceability of nameplate data during the generation process and meeting the data compliance and information management needs of CPE equipment in large-scale production and operation.

[0003] A method for generating and managing CPE nameplate data is a technical solution that uses client-server collaboration to generate, verify, upload, and store CPE device nameplate information in a standardized manner. The aim is to solve the problems of scattered nameplate data generation, inconsistent styles, and difficult management in existing CPE device nameplate data systems. This method achieves centralized processing of nameplate data, ensuring the uniqueness and legality of the generated data. It also enables batch export, classification statistics, and printing on the server side. The desired effects are improved nameplate data generation efficiency, enhanced data security, improved management convenience, and reduced error rates associated with traditional methods.

[0004] Existing technologies suffer from several drawbacks in practical operation. The generation end is fragmented, and the verification end is decoupled. For devices originating from the same source, there is a lack of unified positional labeling and binning organization. Field verification remains at the row and record levels. Duplicate conflicts often only become apparent after data entry through statistical reports, leading to rejections and duplicate exports. Anomalies and records lack a unified mapping between index numbers and batch numbers at the archiving level, requiring cross-table searches for traceability, resulting in high positioning costs and a high risk of omissions. File-level comparisons are coarse-grained, making it difficult to quickly locate character position differences. Error debugging requires line-by-line comparison, impacting outbound verification efficiency. During high-concurrency upload periods, the lack of batch-based access control and status closure makes hot batches prone to write congestion and duplicate data entry risks, leading to fluctuations in statistical standards and extended queuing times for subsequent printing tasks. These shortcomings, in large-scale production and operation scenarios, cause a chain reaction of increased rework, longer traceability times, and the spread of erroneous records to downstream processes. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a method for generating and managing CPE nameplate data.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a method for generating and managing CPE nameplate data, comprising the following steps:

[0007] S1: The IMEI field, MAC address and serial number generated by the client are converted into integers and then compared with the prefix character set bit by bit. The results are stored in the corresponding buckets of encrypted ciphertext and written into the identifier table to generate a bucketed encrypted tag set.

[0008] S2: Based on the bucketed encrypted tag set, call the bucketed index table and compare the fields item by item, perform duplicate detection and record the sequence number position, match the comparison results with the rule table item by item and output the status to obtain the bucketed key rule status index table.

[0009] S3: Based on the bucket key rule status index table, bind the batch number and order number and set the token triggering condition, determine the index status value and generate an upload permit, and write the permit, batch number and order number into the control table to form a batch upload token;

[0010] S4: Based on the batch upload token, upload the nameplate data file through the client and call the corresponding encrypted comparison, compare the IMEI field, MAC address and serial number position character by character and mark the differences, write the results into the verification table to form a plaintext verification status set;

[0011] S5: Based on the plaintext verification status set, call the abnormal path table and write the failure record, bucket number, and sequence number into the abnormal archive area. After the successful record is archived, it is added to the qualified archive area along with the batch number. Establish the correspondence between the index number and the batch number and construct the batch archive index table.

[0012] As a further embodiment of the present invention, the bucket encryption tag set includes a bucket number, encrypted ciphertext, and field index number; the bucket key rule status index table includes a bucket number, sequence number position, and field comparison status; the batch upload token includes a batch number, order number, and upload permission; the plaintext verification status set includes an IMEI field difference marker, a MAC address difference marker, and a serial number difference marker; and the batch archive index table includes an index number, a batch number, and an archive area number.

[0013] As a further aspect of the present invention, the specific steps for generating the bucketed encrypted tag set are as follows:

[0014] The system reads characters from the IMEI field, MAC address and serial number generated by the client and converts them into integers. It then compares the integers with the prefix character set and records the comparison values. The numerical results are written to a temporary index table to generate a field comparison index table.

[0015] Based on the field comparison index table, the comparison results are extracted one by one and located to the corresponding bucket. The bucket mapping relationship between the comparison results and the encrypted ciphertext is established. The corresponding relationship content is synchronized to the identifier table and a batch index is generated. After generating the bucket index data, a reference is established, and a bucket encryption tag set is generated.

[0016] As a further aspect of the present invention, the specific steps for obtaining the bucket key rule state index table are as follows:

[0017] Based on the aforementioned bucketed encrypted tag set, the bucketed index table is called and the field content is read. The comparison values ​​of IMEI, MAC, and serial number are extracted item by item and the positions are recorded. The comparison values ​​are encrypted using a homomorphic encryption algorithm and written into the index table. An entry identifier is established, and a field comparison record set is generated.

[0018] Based on the field comparison record set, duplicate values ​​are marked after each field is detected, the corresponding serial number position of the duplicate field is recorded and mapped, the serial number and the marked data are integrated and written into the result table to generate a duplicate detection result set.

[0019] Based on the duplicate detection result set, the detection data is extracted item by item and matched with the rule table in terms of prefix, length, and character range. The status of each comparison is output and recorded in the status table. The status and bucketing information are integrated and stored to generate a bucketing key rule status index table.

[0020] As a further aspect of the present invention, the specific execution process of the homomorphic encryption algorithm is as follows: Based on the bucketed encryption tag set, a server public and private key is generated and the private key is stored on the server. The public key is sent to the authorized client. The IMEI comparison value, MAC comparison value, and serial number comparison value are concatenated with the bucket number and batch number according to the field position order to form a plaintext block using fixed-length integer encoding. An independent random factor is generated for each plaintext block using a random seed. The blocks are encrypted one by one to generate a ciphertext vector. The correspondence between the ciphertext vector and the entry identifier, field position order, bucket number, and batch number is recorded. The ciphertext digest is calculated and the timestamp is recorded. The digest is written to the corresponding row and column of the bucketed index table. All ciphertexts under the same bucket are read on the server side. The numerical summation operation is performed on each item to obtain the total value. The total value is compared with a preset threshold. After confirming the comparison result, a count item and a matching identifier record are generated. The operation product and the item identifier are associated with the item and placed in the state cache.

[0021] As a further aspect of the present invention, the integration and storage of status and bucket information specifically involves writing each status value obtained from prefix matching, length verification, and character range comparison, along with the corresponding bucket number and field order, into the same structured storage table. The table includes a bucket number field, a field order field, a status value field, and a record time field. During the writing process, an index is established using the bucket number and field order as a combined primary key, so that subsequent retrievals can accurately locate the corresponding status value and associated field based on the bucket number.

[0022] As a further aspect of the present invention, the specific steps for constructing the batch upload token are as follows:

[0023] Based on the bucket key rule status index table, batch number and order number are bound and corresponding fields are established. Trigger conditions are set and index status values ​​are read. The corresponding contents of batch number, order number and status value are recorded and written into a temporary control table to generate a batch trigger judgment table.

[0024] Based on the batch trigger determination table, the index status value is read and compared with the trigger conditions item by item. If the comparison result meets the conditions, an upload license record is generated. The corresponding entries of the license, batch number and order number are written and stored in the control table. A batch index is established and recorded, and a batch upload token is generated.

[0025] As a further aspect of the present invention, the specific steps for forming the plaintext verification state set are as follows:

[0026] Based on the batch upload token, upload the nameplate data file to the server and separate the file content. Read the IMEI field, MAC address and serial number in the file, record each piece of data and store it in the cache table to generate a batch data cache table.

[0027] Based on the batch data cache table, each record is extracted and the corresponding ciphertext is called. The IMEI field, MAC address and serial number position are compared character by character. Different characters are marked and difference records are established. An isolated forest is introduced to identify anomalies in the difference records and output anomaly labels to generate a field difference record table.

[0028] Based on the field difference record table, each difference result and the corresponding entry of the original data are written to the verification table, the comparison status is integrated and stored in the order of the entries to form a unified result set and generate a plaintext verification status set.

[0029] As a further aspect of the present invention, the specific execution process of the isolated forest is as follows: based on the set of differential records, field features are extracted and a splitting threshold is generated within a numerical range; multiple random partitioning trees are constructed and records are split layer by layer; the path length of each record to the leaf node in each tree is recorded; the average path length of each tree is calculated and converted into a score; based on the comparison result of the score and the set threshold, abnormal and normal indicators are output; and the indicator, along with the row number, field position, and bucket number of the corresponding record, are stored in the original set of differential records.

[0030] As a further aspect of the present invention, the specific steps for constructing the batch archive index table are as follows:

[0031] Based on the plaintext verification status set, the abnormal path table is called and the failure record is retrieved. The corresponding bucket number and sequence number of the failure record are extracted and written into the abnormal archive area. After establishing the record index, an abnormal list is formed and an abnormal archive record table is generated.

[0032] Based on the abnormal archive record table, the successfully archived record is written to the qualified archive area with an appended batch number, the correspondence between the index number and the batch number is established and stored in the unified index library, forming a batch archive mapping set and generating a batch archive index table.

[0033] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0034] 1. In this invention, by uniformly converting the IMEI field, MAC address and serial number into integers and comparing them bit by bit with the prefix character set to establish a bucketed ciphertext mapping, a comparison baseline that can be directly located by bucket number and field position order is formed, which improves the uniqueness and hierarchical management accuracy of the data generation stage.

[0035] 2. In this invention, an upload permit is generated by index status and preset conditions and bound to batch number and order number. Homomorphic encryption is combined to perform summation and threshold determination in the ciphertext field, avoiding the data exposure risk caused by plaintext expansion, and realizing the coexistence of batch status calculation and high-strength security.

[0036] 3. In this invention, the isolated forest algorithm is used to further identify abnormal records, improve the accuracy and response speed of anomaly detection, and establish an index mapping between qualified records and batch numbers, which ensures the integrity of batch archiving and the efficiency of subsequent traceability, and enhances data security, retrieval efficiency and management controllability in large-scale production scenarios. Attached Figure Description

[0037] Figure 1 This is a schematic diagram of the main steps of the present invention. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0039] Example 1

[0040] Please see Figure 1 This invention provides a technical solution: a method for generating and managing CPE nameplate data, comprising the following steps:

[0041] S1: The IMEI field, MAC address and serial number generated by the client are converted into integers and then compared with the prefix character set bit by bit. The results are stored in the corresponding buckets of encrypted ciphertext and written into the identifier table to generate a bucketed encrypted tag set.

[0042] S2: Based on the bucketed encrypted tag set, call the bucketed index table and compare the fields item by item to perform duplicate detection and record the sequence number position. Match the comparison results item by item with the rule table and output the status to obtain the bucketed key rule status index table.

[0043] S3: Based on the bucket key rule status index table, bind the batch number and order number and set the token trigger condition, determine the index status value and generate the upload permission, write the permission and batch number and order number into the control table to form the batch upload token;

[0044] S4: Based on the batch upload token, the nameplate data file is uploaded through the client and the corresponding encrypted comparison is called. The IMEI field, MAC address and serial number position are compared character by character and the differences are marked. The results are written into the verification table to form a plaintext verification status set.

[0045] S5: Based on the plaintext verification status set, call the abnormal path table and write the failure record, bucket number, and sequence number into the abnormal archive area. After the successful record is archived, it is added to the qualified archive area along with the batch number. Establish the correspondence between the index number and the batch number and build the batch archive index table.

[0046] The bucket encryption tag set includes bucket number, encrypted ciphertext, and field index number; the bucket key rule status index table includes bucket number, sequence number position, and field comparison status; the batch upload token includes batch number, order number, and upload permission; the plaintext verification status set includes IMEI field difference marker, MAC address difference marker, and serial number difference marker; and the batch archive index table includes index number, batch number, and archive area number.

[0047] The specific steps for generating a bucketed encrypted tag set are as follows:

[0048] The system reads characters from the IMEI field, MAC address and serial number generated by the client and converts them into integers. It then compares the integers with the prefix character set and records the comparison values. The numerical results are written to a temporary index table to generate a field comparison index table.

[0049] Based on the field comparison index table, the comparison results are extracted one by one and located to the corresponding bucket. The bucket mapping relationship between the comparison results and the encrypted ciphertext is established. The corresponding relationship content is synchronized to the identifier table and a batch index is generated. After the bucket index data is generated, a reference is established and a bucket encryption tag set is generated.

[0050] Based on the IMEI field, MAC address, and serial number generated by the client, each character is read and converted into a decimal integer according to the ASCII encoding range 0 to 127. The length of the output integer array is set to 15. The prefix character set stores 36 characters in a fixed order, including 26 uppercase letters A to Z and 10 digits 0 to 9. When comparing characters bit by bit, the comparison counter is set to an initial value of 0 and incremented by 1 after each character match. The integer value of each character is compared with the integer value of the corresponding character in the prefix character set. If they are the same, the comparison value is recorded as 1; otherwise, the comparison value is recorded as 0. The recorded results are written to a temporary index table. The fields of the temporary index table include field name, position number, comparison value, and recording time. The recording time format is set to year, month, day, hour, minute, and second. A field comparison index table is generated.

[0051] Based on the field comparison index table, the bucket number is set as an integer sequence starting from 0 with a maximum value of 99. The bucket number is determined by taking the remainder of 100 based on the field position. The comparison results are extracted one by one, and a correspondence is established between the field position and the bucket number. The comparison value and the bucket number are combined into a fixed-length 64-bit hexadecimal string. The bucket mapping table contains three columns: bucket number, comparison value combination code, and record sequence number. The record is appended with the generation time format as year, month, day, hour, minute, and second. The comparison results and encrypted ciphertext are stored in the mapping table. The bucket mapping relationship between the comparison results and the encrypted ciphertext is established and synchronized to the identifier table. The identifier table fields include bucket number, combination code, batch number, and generation time. The batch number is set as an eight-digit auto-incrementing sequence. After generating the bucket index data, a foreign key reference is established between the index number and the identifier table to generate a bucket encryption tag set.

[0052] The specific steps to obtain the bucket key rule status index table are as follows:

[0053] Based on the bucketed encrypted tag set, the bucketed index table is called and the field content is read. The comparison values ​​of IMEI, MAC and serial number are extracted item by item and the position is recorded. The comparison values ​​are encrypted using the homomorphic encryption algorithm and written into the index table. An entry identifier is established to generate a field comparison record set.

[0054] Based on the field comparison record set, duplicate values ​​are marked after each field is detected, the corresponding serial number position of the duplicate field is recorded and mapped, and the serial number and marked data are integrated and written into the result table to generate a duplicate detection result set.

[0055] Based on the duplicate detection result set, the detection data is extracted item by item and matched with the rule table in terms of prefix, length and character range. The status of each comparison is output and recorded in the status table. The status and bucketing information are integrated and stored to generate a bucketing key rule status index table.

[0056] Based on a bucketed encrypted tag set, the comparison values ​​of IMEI, MAC, and serial number are extracted item by item and their positions are recorded. A homomorphic encryption algorithm is used with a preset public key modulus length of 2048 bits. A public key and private key are randomly generated and stored on the server. After receiving the public key, the client encodes the comparison value into an integer using a fixed-length 16-bit decimal sequence, with the encoding range set to 0 to 16 minus 1. The bucket number and sequence number of each record are used as random seeds to generate an independent random factor of 32-bit decimal integer length. The integer encoding and the random factor are then compared numerically. After concatenation, the plaintext is divided into 64-bit plaintext blocks. Additive homomorphic encryption is performed on each plaintext block. During the operation, the ciphertext generation parameters are set, including the modulus N (which is the public key modulus), the radix g (which is 2), and the exponent (which is the integer of the concatenated plaintext block). The resulting ciphertext is in hexadecimal string format with a fixed length of 512 characters. When writing to the index table, the ciphertext is stored in combination with the bucket number, sequence number, and field position, and an entry identifier is established. The entry identifier is an auto-incrementing sequence number with a length of 12-bit integer and is written to the field comparison record set to generate the field comparison record set.

[0057] Based on the field comparison record set, duplicate values ​​are marked after each field is detected. The detection threshold is set to complete consistency of the comparison values. When scanning each record, it is sorted by bucket number and compared within the same bucket. A two-pointer loop is used to compare the encrypted value strings of the records before and after, with a fixed length of 512 characters. If they are the same, a mark value of 1 is written in the mark field; otherwise, a mark value of 0 is written. The sequence number position corresponding to the duplicate field is recorded and mapped. The sequence number position and the mark value are combined to form a mapping string with a length of 20 characters. The sequence number and mark data are integrated and written to the result table. The fields of the result table include bucket number, sequence number, mark value, mapping string, and record time. The record time format is year, month, day, hour, minute, and second. A duplicate detection result set is generated.

[0058] Based on the duplicate detection result set, each detection data is extracted and matched with the rule table for prefix, length, and character range. The prefix field in the rule table allows uppercase letters A to Z and numbers 0 to 9 with a length of 2 to 5 characters. The length field allows a range of 10 to 20 characters. The character range field limits the ASCII code range to 48 to 90. During the matching process, each duplicate detection record is read and the plaintext length information before encryption is compared with the conditions in the rule table. Prefix matching uses the first 2 to 5 characters of the record as the comparison object, length matching uses the overall length of the record as the comparison object, and character range matching uses the integer value of each character as the comparison object. After the matching is completed, the status of each comparison is output. The status value is represented by an integer. A qualified value is written as 1, and an unqualified value is written as 0. The status is recorded in the status table. The status table fields include bucket number, sequence number, status value, and record time. The record time format is year, month, day, hour, minute, and second. The status and bucket information are integrated and stored to generate a bucket key rule status index table.

[0059] The specific execution process of the homomorphic encryption algorithm is as follows: Based on the bucketed encryption tag set, a server public and private key is generated and stored on the server. The public key is sent to the authorized client. The IMEI comparison value, MAC comparison value, and serial number comparison value are concatenated with the bucket number and batch number according to the field position order to form a plaintext block using fixed-length integer encoding. An independent random factor is generated for each plaintext block using a random seed. The blocks are encrypted one by one and a ciphertext vector is generated. The correspondence between the ciphertext vector and the entry identifier, field position order, bucket number, and batch number is recorded. The ciphertext digest is calculated and the timestamp is recorded. It is written into the corresponding row and column of the bucket index table. On the server side, all ciphertexts under the same bucket are read. The numerical summation operation is performed on each item to obtain the total value. The total value is compared with the preset threshold. After confirming the comparison result, a count item and a matching identifier record are generated. The operation product and the item identifier are associated with the item and placed in the state cache.

[0060] Homomorphic encryption algorithms, according to the formula:

[0061]

[0062] Where: E(A) represents the encrypted ciphertext, A represents the plaintext data to be encrypted, g represents the encryption base, r represents the random factor, n represents the public key modulus, calculated by multiplying two large prime numbers, N represents the encryption modulus, and F... bucket The bin number represents the data encryption result, which is further refined during the encryption process. mod indicates that the modulo operation is to divide one number by another and return the remainder of the division. H (IMEI), H (MAC), and H (serial number) represent the hash values ​​of the IMEI field, MAC address field, and serial number field, respectively.

[0063] Execution process: First, for the data to be encrypted, the fields are converted into integer values ​​through specific encoding rules. An additive homomorphic encryption algorithm is used to encrypt the plaintext data. During the encryption process, a fixed encryption base g is first selected. Then, a random factor r is generated using the bucket number and sequence number. The public key modulus n and encryption modulus N are set for ciphertext calculation. Each plaintext field is used as an encryption object and processed by a specified hash function to obtain hash values ​​H (IMEI), H (MAC), and H (serial number). The hash values, encryption base, and random factor are combined to perform encryption calculations on each field to generate the final ciphertext result.

[0064] The integration and storage of status and bucket information involves writing each status value obtained from prefix matching, length verification, and character range comparison, along with its corresponding bucket number and field order, into the same structured storage table. The table includes a bucket number field, a field order field, a status value field, and a record time field. During the writing process, an index is created using the bucket number and field order as a composite primary key, enabling subsequent retrieval to accurately locate the corresponding status value and associated fields based on the bucket number.

[0065] The specific steps to generate a batch upload token are as follows:

[0066] Based on the bucket key rule status index table, batch number and order number are bound and corresponding fields are established. Trigger conditions are set and index status values ​​are read. The corresponding contents of batch number, order number and status value are recorded and written to a temporary control table to generate a batch trigger judgment table.

[0067] Based on the batch trigger determination table, the index status value is read and compared with the trigger conditions item by item. The comparison result is confirmed to meet the conditions and an upload license record is generated. The corresponding entries of the license, batch number and order number are written and stored in the control table. A batch index is established and recorded, and a batch upload token is generated.

[0068] Based on the bucket key rule status index table, the index table is first read and the batch number and order number fields are extracted. The trigger condition is set to a status value of 1. When reading records, the status value field of each record is extracted and the status value of each record is compared with the preset trigger condition. If the status value meets the condition, the corresponding batch number, order number and status value are recorded to the temporary control table. The temporary control table fields include batch number, order number, status value and record time. The record time format is year, month, day, hour, minute and second. The data is written to the temporary control table to generate the batch trigger judgment table. The batch trigger judgment table includes fields such as batch number, order number, status value and trigger time.

[0069] Based on the batch trigger determination table, the index status value is read and compared with the trigger conditions item by item. The batch number, order number, and status value fields in the batch trigger determination table are read and extracted one by one and compared with the trigger conditions item by item. The trigger condition is set to status value = 1. The batch number, order number, and status value that meet the conditions are stored in a mapping table in memory to generate upload license records. The license record fields include batch number, order number, status value, and license generation time. The generated upload license records are written to the control table. The control table fields include batch number, order number, upload license, and record time. A batch index is created and linked to the control table through a foreign key to generate batch upload tokens.

[0070] The specific steps for forming a plaintext verification state set are as follows:

[0071] Based on the batch upload token, upload the nameplate data file to the server and separate the file content. Read the IMEI field, MAC address and serial number in the file, record each piece of data and store it in the cache table to generate a batch data cache table.

[0072] Based on the batch data cache table, each record is extracted and the corresponding ciphertext is called. The IMEI field, MAC address and serial number position are compared character by character. Different characters are marked and difference records are established. An isolated forest is introduced to identify anomalies in the difference records and output anomaly labels to generate a field difference record table.

[0073] Based on the field difference record table, write each difference result and the corresponding entry of the original data into the verification table, integrate the comparison status and store them in the order of the entries to form a unified result set and generate a plaintext verification status set.

[0074] Based on batch upload tokens, the nameplate data file is uploaded to the server and the file content is separated. The file content is read and the records are parsed line by line. The file is split by line, and the IMEI field, MAC address and serial number are extracted for each record. The field data of each record is converted into integers. The field data range is set as follows: IMEI is 15 digits, MAC address is 12 hexadecimal characters and serial number is 8 digits. After the data is verified, the IMEI, MAC address and serial number are written to the batch data cache table. The cache table fields include IMEI field, MAC address field, serial number field and record time. The record time is set to the system time when each record is uploaded, in seconds. A batch data cache table is generated. The table is a temporary storage structure for each batch of data. The number of records stored increases gradually according to the upload batch.

[0075] Based on the batch data cache table, each record is extracted and the corresponding ciphertext is retrieved. The character positions of the IMEI field, MAC address and serial number are compared character by character. During the character comparison, the character positions of each field are compared and checked one by one to see if they match the corresponding ciphertext. If the characters are different, the difference is marked and the position of the difference characters is recorded. The isolated forest algorithm is used for anomaly identification. In the algorithm, the parameters of the isolated forest are set as follows: the number of trees is 100 and the training sample size is set to auto, which means that it will adapt to the data volume by default. After the model is built, each difference record is used as a sample input to determine whether it is an anomaly. The anomaly label is 1 and the normal label is 0. A field difference record table is generated.

[0076] Based on the field difference record table, each difference result and its corresponding entry to the original data are written to the verification table. The verification table will contain fields such as IMEI, MAC address, serial number, difference flag, exception label, and record time. When writing data to the table one by one, the difference flag is checked first. If the flag is 1, it means that there is a difference in the data. Then, the IMEI, MAC address, and serial number of the record are matched with the original data, and the difference flag, exception label, and other data are written to the verification table. The records in the table are sorted by record time, and the sorting rule is to sort in ascending order by the timestamp field, generating a plaintext verification status set.

[0077] The specific execution process of the isolated forest is as follows: based on the set of differential records, field features are extracted and a splitting threshold is generated within the numerical range. Multiple random partitioning trees are constructed and records are split layer by layer. The path length of each record to the leaf node in each tree is recorded. The average path length of each tree is calculated and converted into a score. Based on the comparison result of the score and the set threshold, abnormal and normal indicators are output. The indicator, along with the row number, field position, and bucket number of the corresponding record, are stored in the original set of differential records.

[0078] An isolated forest, according to the formula:

[0079]

[0080] Where: s(A) represents the anomaly score, represents the degree of anomaly of sample A, N represents the total number of training trees in the isolated forest, and T j Let d(A,T) represent the j-th tree. j ) indicates that sample A is in tree T j The path length P to the leaf node. bucket Indicates the bin number, c(T) j ) represents tree T j The average path length, where Q represents the weighting coefficient, set to 0.8;

[0081] Execution process: First, multiple trees are trained on the sample data. Each tree determines the degree of anomaly based on the path length of the sample. For each sample A, the algorithm calculates the anomaly level through tree T. j Calculate the path length d(A,T) j ), and the average path length of the tree c(T) j The shorter the path length, the more likely sample A is to be isolated and more likely to be an outlier. This calculation is repeated until all trees have been processed, and the path length d(A,T) is calculated. j ) and the average path length c(T) of each tree j A comparison is performed to generate a ratio, further refining the analysis of sample A, and introducing the bin number P. bucket The sample is subdivided, weighted information is added, and the accuracy of anomaly scoring is improved. A weight coefficient Q is introduced to adjust the influence of each tree on the final anomaly score. After the scores of the trees are weighted, the average value is taken, and the anomaly score s(A) of sample A is finally obtained.

[0082] The specific steps for constructing the batch archive index table are as follows:

[0083] Based on the plaintext verification status set, the abnormal path table is called and the failure record is retrieved. The corresponding bucket number and sequence number of the failure record are extracted and written into the abnormal archive area. After the record index is established, an abnormal list is formed and an abnormal archive record table is generated.

[0084] Based on the abnormal archive record table, the successful archive record is written to the qualified archive area with the batch number attached, the correspondence between the index number and the batch number is established and stored in the unified index library, forming a batch archive mapping set and generating a batch archive index table.

[0085] Based on the plaintext verification status set, the abnormal path table is called and the failure records are retrieved. All records marked as failure are extracted and the failure mark is set to 0. The set of records that meet the failure conditions is filtered out. The bucket number and sequence number of each failure record are extracted. The information is combined into a string and stored in the abnormal archive area. The fields of the abnormal archive area include bucket number, sequence number, failure reason and record time. The record time is obtained by the system time function and the format is year, month, day, hour, minute and second. The failure records are written to the archive area. After storage, a composite index is set for the bucket number and sequence number to ensure fast query. The record index is built through the index and an abnormal list is generated to generate an abnormal archive record table.

[0086] Based on the abnormal archive record table, successfully archived records are written to the qualified archive area with an appended batch number. Records with a successful status are filtered out, and the success flag is set to 1. The bucket number, sequence number, and corresponding batch number of the successful records are extracted and written to the qualified archive area. The fields of the qualified archive area include bucket number, sequence number, batch number, and archive time, etc. The archive time is stored in date and time format. A correspondence between index number and batch number is established and stored in a unified index database. The fields of the unified index database include index number, batch number, batch generation time, etc. An index is created for the batch number field to ensure the efficiency of record query and generate a batch archive mapping set.

[0087] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for generating and managing CPE nameplate data, characterized in that, Includes the following steps: S1: The IMEI field, MAC address and serial number generated by the client are converted into integers and then compared with the prefix character set bit by bit. The results are stored in the corresponding buckets of encrypted ciphertext and written into the identifier table to generate a bucketed encrypted tag set. S2: Based on the bucketed encrypted tag set, call the bucketed index table and compare the fields item by item, perform duplicate detection and record the sequence number position, match the comparison results with the rule table item by item and output the status to obtain the bucketed key rule status index table. S3: Based on the bucket key rule status index table, bind the batch number and order number and set the token triggering condition, determine the index status value and generate an upload permit, and write the permit, batch number and order number into the control table to form a batch upload token; S4: Based on the batch upload token, upload the nameplate data file through the client and call the corresponding encrypted comparison, compare the IMEI field, MAC address and serial number position character by character and mark the differences, write the results into the verification table to form a plaintext verification status set; S5: Based on the plaintext verification status set, call the abnormal path table and write the failure record, bucket number, and sequence number into the abnormal archive area. After the successful record is archived, it is added to the qualified archive area along with the batch number. Establish the correspondence between the index number and the batch number and construct the batch archive index table.

2. The method for generating and managing CPE nameplate data according to claim 1, characterized in that, The bucket encryption tag set includes bucket number, encrypted ciphertext, and field index number; the bucket key rule status index table includes bucket number, sequence number position, and field comparison status; the batch upload token includes batch number, order number, and upload permission; the plaintext verification status set includes IMEI field difference marker, MAC address difference marker, and serial number difference marker; and the batch archive index table includes index number, batch number, and archive area number.

3. The method for generating and managing CPE nameplate data according to claim 1, characterized in that, The specific steps for generating the bucketed encrypted tag set are as follows: The system reads characters from the IMEI field, MAC address and serial number generated by the client and converts them into integers. It then compares the integers with the prefix character set and records the comparison values. The numerical results are written to a temporary index table to generate a field comparison index table. Based on the field comparison index table, the comparison results are extracted one by one and located to the corresponding bucket. The bucket mapping relationship between the comparison results and the encrypted ciphertext is established. The corresponding relationship content is synchronized to the identifier table and a batch index is generated. After generating the bucket index data, a reference is established, and a bucket encryption tag set is generated.

4. The method for generating and managing CPE nameplate data according to claim 1, characterized in that, The specific steps to obtain the bucket key rule status index table are as follows: Based on the aforementioned bucketed encrypted tag set, the bucketed index table is called and the field content is read. The comparison values ​​of IMEI, MAC, and serial number are extracted item by item and the positions are recorded. The comparison values ​​are encrypted using a homomorphic encryption algorithm and written into the index table. An entry identifier is established, and a field comparison record set is generated. Based on the field comparison record set, duplicate values ​​are marked after each field is detected, the corresponding serial number position of the duplicate field is recorded and mapped, the serial number and the marked data are integrated and written into the result table to generate a duplicate detection result set. Based on the duplicate detection result set, the detection data is extracted item by item and matched with the rule table in terms of prefix, length, and character range. The status of each comparison is output and recorded in the status table. The status and bucketing information are integrated and stored to generate a bucketing key rule status index table.

5. The method for generating and managing CPE nameplate data according to claim 4, characterized in that, The specific execution process of the homomorphic encryption algorithm is as follows: Based on the bucketed encryption tag set, a server public and private key is generated and stored on the server. The public key is sent to the authorized client. The IMEI comparison value, MAC comparison value, and serial number comparison value are concatenated with the bucket number and batch number according to the field position order to form a plaintext block using fixed-length integer encoding. An independent random factor is generated for each plaintext block using a random seed. The blocks are encrypted one by one to generate a ciphertext vector. The correspondence between the ciphertext vector and the entry identifier, field position order, bucket number, and batch number is recorded. The ciphertext digest is calculated and the timestamp is recorded. The digest is written to the corresponding row and column of the bucketed index table. All ciphertexts under the same bucket are read on the server side. The numerical summation operation is performed on each item to obtain the total value. The total value is compared with a preset threshold. After confirming the comparison result, a count item and a matching identifier record are generated. The operation product and the item identifier are associated with the item and placed in the state cache.

6. The method for generating and managing CPE nameplate data according to claim 1, characterized in that, The specific method of integrating and storing status and bucket information involves writing each status value obtained from prefix matching, length verification, and character range comparison, along with the corresponding bucket number and field order, into the same structured storage table. The table includes a bucket number field, a field order field, a status value field, and a record time field. During the writing process, an index is established using the bucket number and field order as a composite primary key, so that subsequent retrievals can accurately locate the corresponding status value and associated fields based on the bucket number.

7. The method for generating and managing CPE nameplate data according to claim 1, characterized in that, The specific steps for constructing the batch upload token are as follows: Based on the bucket key rule status index table, batch number and order number are bound and corresponding fields are established. Trigger conditions are set and index status values ​​are read. The corresponding contents of batch number, order number and status value are recorded and written into a temporary control table to generate a batch trigger judgment table. Based on the batch trigger determination table, the index status value is read and compared with the trigger conditions item by item. If the comparison result meets the conditions, an upload license record is generated. The corresponding entries of the license, batch number and order number are written and stored in the control table. A batch index is established and recorded, and a batch upload token is generated.

8. The method for generating and managing CPE nameplate data according to claim 1, characterized in that, The specific steps for forming the plaintext verification state set are as follows: Based on the batch upload token, upload the nameplate data file to the server and separate the file content. Read the IMEI field, MAC address and serial number in the file, record each piece of data and store it in the cache table to generate a batch data cache table. Based on the batch data cache table, each record is extracted and the corresponding ciphertext is called. The IMEI field, MAC address and serial number position are compared character by character. Different characters are marked and difference records are established. An isolated forest is introduced to identify anomalies in the difference records and output anomaly labels to generate a field difference record table. Based on the field difference record table, each difference result and the corresponding entry of the original data are written to the verification table, the comparison status is integrated and stored in the order of the entries to form a unified result set and generate a plaintext verification status set.

9. The method for generating and managing CPE nameplate data according to claim 8, characterized in that, The specific execution process of the isolated forest is as follows: based on the set of differential records, field features are extracted and a splitting threshold is generated within the numerical range. Multiple random partitioning trees are constructed and records are split layer by layer. The path length of each record to the leaf node in each tree is recorded. The average path length of each tree is calculated and converted into a score. Based on the comparison result of the score and the set threshold, abnormal and normal indicators are output. The indicator, along with the row number, field position, and bucket number of the corresponding record, are stored in the original set of differential records.

10. The method for generating and managing CPE nameplate data according to claim 1, characterized in that, The specific steps for constructing the batch archive index table are as follows: Based on the plaintext verification status set, the abnormal path table is called and the failure record is retrieved. The corresponding bucket number and sequence number of the failure record are extracted and written into the abnormal archive area. After establishing the record index, an abnormal list is formed and an abnormal archive record table is generated. Based on the abnormal archive record table, the successfully archived record is written to the qualified archive area with an appended batch number, the correspondence between the index number and the batch number is established and stored in the unified index library, forming a batch archive mapping set and generating a batch archive index table.

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