A tea refining production traceability method and system

Abstract

The present invention discloses a tea refining production traceability method and system, and relates to the technical field of tea production. The present invention collects tea information of each link of tea refining production by setting a production information collection module, and sets a classification interaction module to screen out tea information of several links according to a preset classification information list for plain text transmission, and sets a conversion rule to convert the remaining tea information of all processes into tea refining ciphertext data and tea refining ciphertext sequence for transmission. In this way, tea information is classified, and tea information and privacy information that are relatively well-known and can be easily obtained are split and transmitted. Even if part of the plain text information is obtained, it is difficult to infer the key privacy content. At the same time, for important information such as tea refining process that needs to be kept confidential, it is transmitted in ciphertext form, which greatly improves the security and confidentiality of the information.

Description

Technical Field

[0001] The invention relates to the technical field of tea production, and in particular to a tea refining production traceability method and system. Background Art

[0002] In modern society, consumers are increasingly concerned about food safety and product quality. As a widely consumed beverage, tea's quality and safety have attracted much attention. During the tea refining production process, tea traceability can not only ensure the quality and safety of tea, but also improve consumer trust and satisfaction;

[0003] With the continuous development of information technology, the traceability system of tea refining production has gradually become possible. By collecting and recording data from each link in the tea production process, the whole process of tea can be traced. However, the existing traceability system of tea refining production has some problems;

[0004] First, tea information contains some private information, such as the origin of tea, information about growers, and processing technology. This private information needs to be stored securely to prevent unauthorized access. Existing traceability systems often do not classify private information, resulting in all information being stored and transmitted in the same way, increasing the risk of private information leakage.

[0005] Secondly, the existing traceability system often uses keys for encryption, but there is a risk of key leakage. Once the key is leaked, the security of tea information cannot be guaranteed.

[0006] In order to solve the above problems, the present invention proposes a solution. Summary of the invention

[0007] The purpose of the present invention is to provide a tea refining production traceability method and system, in order to solve the problems raised in the above background technology;

[0008] The purpose of the present invention can be achieved through the following technical solutions:

[0009] A tea refining production traceability method comprises the following steps:

[0010] Step 1: After receiving the transmitted tea refining production data, the classification interaction module extracts tea information of several links from the tea refining production data according to a preset classification information list, and generates tea refining plaintext traceability data according to the extracted tea information of several links;

[0011] Step 2: generating tea refining data to be processed from the tea information of all processes remaining after the extraction of the tea refining production data, and converting it into tea refining ciphertext data and tea refining ciphertext sequence according to a preset conversion rule;

[0012] Step three: After receiving the transmitted tea refining plaintext traceability data, the cloud storage module stores it. After receiving the transmitted tea refining ciphertext data and tea refining ciphertext sequence, the cloud storage module restores the tea refining ciphertext data according to the tea refining ciphertext sequence to obtain the tea refining data to be processed, and stores the tea refining data to be processed.

[0013] Preferably, the following steps need to be performed before completing step 1:

[0014] The production information collection module collects tea information from each link of tea refining production, generates tea refining production data according to the collected tea information from each link of tea refining production, and transmits the tea refining production data to the classification interaction module.

[0015] Preferably, a tea refining production traceability system comprises:

[0016] The production information collection module is used to collect tea information from each link of tea refining production. The production information collection module collects tea information from each link of tea refining production and generates tea refining production data based on the collected tea information from each link of tea refining production;

[0017] A classification interaction module is used to transmit tea information of each link in tea refining production by type, extract tea information of several links from the tea refining production data according to a preset classification information list, generate tea refining plaintext traceability data according to the extracted tea information of several links, and transmit it to the cloud storage module;

[0018] The tea information of all processes remaining after the extraction of the tea refining production data is generated into tea refining to-be-processed data, and converted into tea refining ciphertext data and tea refining ciphertext sequence according to a preset conversion rule, and transmitted them to the cloud storage module;

[0019] The cloud storage module is used to store tea information of each link of tea refining production in the cloud.

[0020] Beneficial effects of the present invention:

[0021] (1) The present invention collects tea information from various links of tea refining production by setting a production information collection module, sets a classification interaction module to screen out tea information from several links according to a preset classification information list for plain text transmission, sets a conversion rule to convert the remaining tea information of all processes into tea refining ciphertext data and tea refining ciphertext sequence for transmission. In this way, tea information is classified, and tea information that is relatively well-known and can be easily obtained and private information are split and transmitted. Even if part of the plain text information is obtained, it is difficult to infer the key private content. At the same time, important information such as tea refining process that needs to be kept confidential is transmitted in ciphertext form, which greatly improves the security and confidentiality of the information;

[0022] (2) The present invention combines a preset base weight table and a frequency weight table, matches the corresponding frequency weight of each binary number in the tea refining data to be processed based on the frequency of occurrence thereof, and performs several rounds of training in combination with the corresponding basic weight. During the training process, several indication lists are introduced, and the training conversion index of all four-bit binary numbers is calculated based on the index subscript of the binary number in multiple indication lists each time and the corresponding type of indication list added. Based on the training conversion index, the binary numbers mapped to each other are determined in pairs based on the training conversion index. In this way, on the one hand, the data processing process is more unpredictable, thereby increasing the difficulty of cracking the data. On the other hand, the introduced indication list further increases the security of the data. Different types of indication lists provide more dimensions for binary numbers, making data transmission more secure. In addition, each time a binary number is added to the indication list during the training process, its basic weight will be updated accordingly, which greatly ensures the dynamic nature of the mapping conversion and provides an extra layer of protection for the security of the data. In addition, encryption logic is used instead of keys to manage tea information, thereby avoiding the occurrence of key leakage. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The present invention will be further described below in conjunction with the accompanying drawings.

[0024] Figure 1 is a flow chart of the method of the present invention;

[0025] Figure 2 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] like Figure 1 , 2 As shown, a tea refining production traceability method and system includes a production information collection module, a classification interaction module and a cloud storage module;

[0028] The production information collection module is used to collect tea information from various links of tea refining production, including joint picking, processing, packaging and storage, and the tea information includes tea varieties, origins, picking time, processing technology, packaging information and storage conditions;

[0029] The production information collection module generates tea refining production data according to the collected tea information of each link of tea refining production, and transmits the tea refining production data to the classification interaction module;

[0030] The classification interaction module is used to transmit tea information of each link in tea refining production by type. The classification interaction module pre-stores a classification information list, and the classification information list stores the names of several links;

[0031] After receiving the transmitted tea refining production data, the classification interaction module extracts tea information of corresponding links from the tea refining production data according to the names of several links included in the classification information list, generates tea refining plaintext traceability data according to the extracted tea information of several links, and transmits it to the cloud storage module;

[0032] The cloud storage module is used to store tea information at all stages of tea refining production in the cloud, which is convenient for later query and traceability;

[0033] The classification interaction module generates tea refining data to be processed by extracting the tea refining production data from the tea information of all processes remaining;

[0034] The classification interaction module pre-stores a base weight table, which contains binary numbers from 0 to 15 and their basic weights;

[0035] The classification interaction module converts the tea refining to-be-processed data into tea refining ciphertext data and tea refining ciphertext sequence according to the preset conversion rules. The conversion rules are as follows:

[0036] S11: performing binary conversion on the tea refining data to be processed, and recalibrating the converted data into tea refining data;

[0037] S12: Mark the binary numbers of digits 0 to 15 as A0, A1...A15 in sequence, then take every four characters in the tea refined base data as a base combination in order from left to right to obtain a plurality of base combinations, and traverse the plurality of base combinations, respectively count the number of base combinations that are consistent with the binary numbers A0, A1...A15, mark them as the indication frequency of the corresponding binary numbers, and mark them as B0, B1...B15, where consistency refers to the same content and the same order of character composition;

[0038] S13: Match B0 with all the numerical intervals included in the indication weight table, obtain the frequency weight corresponding to the matching numerical interval, and mark it as the indication weight C0 of the binary number A0;

[0039] S14: Calculate and obtain the indication weights C1, C2, ... C15 of the binary numbers A1, A2, ... A15 in sequence according to S13:

[0040] S15: creating the first, second, third, fourth, and fifth indication lists D1, D2, D3, D4, and D5 in sequence, and limiting the list lengths of the first, second, third, fourth, and fifth indication lists to 5, 4, 3, 2, and 2, respectively. Explanation: limiting the list length of the first indication list D1 to 5 means that at most 5 elements are added to the first indication list D1, and the list lengths of other indication lists are similar;

[0041] S16: Perform the first round of training on the binary numbers A0, A1...A15 according to the preset round training comparison rule to obtain the round identifiers and round digits of all binary numbers after one round. The round training comparison rule is as follows:

[0042] S161: Using formula Calculate and obtain the additional evaluation index F0 of the binary number A0, where E0 is the basic weight of the binary number A0, and ɑ1 is the preset dimension adjustment factor;

[0043] S162: according to S161, the additional evaluation indicators F1, F2...F15 of the binary numbers A1, A2...A15 are calculated in sequence, and the binary number corresponding to the additional evaluation indicator with the largest value is selected and added to the first indication list D1, and after the addition is completed, the basic weight of the corresponding binary number is updated to the selected additional evaluation indicator with the largest value according to the selected additional evaluation indicator with the largest value;

[0044] S163: adding the corresponding binary numbers of the evaluation indicators F1, F2, ... F15 in the order of large to small to the first, second, third, fourth, and fifth indication lists in sequence, and updating the basic weight of the binary number from the base weight table each time a binary number is added;

[0045] It should be noted here that when the total number of binary numbers added to the first indicator list reaches the list length limited thereto, binary numbers will start to be added to the second indicator list, and the rest of the indicator lists will be added in the same manner;

[0046] S164: For all binary numbers belonging to the first index list D1, their round identifiers are all 1, and the subscript indexes of all binary numbers in the first index list D1 are the corresponding round digits;

[0047] S165: For all binary numbers belonging to the second index list D2, their round identifiers are all 2, and the subscript indexes of all binary numbers in the second index list D2 are the corresponding round digits;

[0048] S166: Obtain the round identifiers and the round digits of all binary numbers after one round according to S164 to S165, wherein the round identifiers of all binary numbers in the third, fourth and fifth index lists are 3, 4 and 5 respectively;

[0049] S17: performing the second, third, fourth and fifth rounds of training on the binary numbers A0, A1...A15 in sequence according to S16 to obtain the second, third, fourth and fifth rounds of identification and the second, third, fourth and fifth rounds of digits;

[0050] S18: Calculate the sum of the first, second, third, fourth and fifth round identifiers of the binary number A0 and use it as the round training identifier H1 of the binary number A0, traverse the first, second, third, fourth and fifth round digits of the binary number A0, obtain the numbers of which are 0, 1, 2, 3, 4 respectively, and mark them as I1, I2, I3, I4 and I5;

[0051] Using the formula Calculate and obtain the round-robin conversion index J0 of the binary number A0 after round-robin training, where β1β2 are the preset first and second adjustment factors, and ⋋1, ⋋2, ⋋3, ⋋4, ⋋5 are the preset first, second, third, fourth and fifth proportion weights, respectively;

[0052] S19: according to S18, the round-robin conversion indexes J1, J2 ... J15 of the binary numbers A1, A2 ... A15 after round-robin are calculated in sequence, the binary numbers A0, A1 ... A15 are sorted from large to small according to the round-robin conversion indexes from large to small, and all the sorted binary numbers are recalibrated as K0, K1 ... K15;

[0053] S110: According to the binary numbers K0, K1...K15, the binary numbers K0, K1...K7 are mapped to binary numbers K8, K9...K15 respectively;

[0054] S111: Mark all the system combinations obtained in S12 as L1, L2, ..., L1 in order according to the order in which they are obtained, obtain a binary number consistent with the system combination L1, obtain a mapping system of the binary number, and use the mapping system as a conversion system of the system combination L1;

[0055] S112: according to S111, the conversion bases of base combinations L2, L3 ... L1 are calculated in sequence, and the conversion bases are spliced ​​in the order of base combinations L1, L2 ... L1 to obtain the tea refined ciphertext data;

[0056] At the same time, in the order of indication frequencies B0, B1...B15, the indication frequencies B0, B1...B15 are concatenated to obtain a tea refining ciphertext sequence;

[0057] The classification interaction module transmits the tea refining ciphertext data and the tea refining ciphertext sequence to the cloud storage module;

[0058] After receiving the transmitted tea refining ciphertext data and tea refining ciphertext sequence, the cloud storage module restores the tea refining ciphertext data according to the tea refining ciphertext sequence to obtain tea refining data to be processed, and stores the tea refining data to be processed;

[0059] In the description of the specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0060] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.

[0061] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A tea refining production traceability method, characterized in that: The steps include: Step 1: After receiving the transmitted tea refining production data, the classification interaction module extracts tea information of several links from the tea refining production data according to a preset classification information list, and generates tea refining plaintext traceability data according to the extracted tea information of several links; Step 2: generating tea refining data to be processed from the tea information of all processes remaining after the extraction of the tea refining production data, and converting it into tea refining ciphertext data and tea refining ciphertext sequence according to a preset conversion rule; Step 3: After receiving the transmitted tea refining plaintext traceability data, the cloud storage module stores it; after receiving the transmitted tea refining ciphertext data and tea refining ciphertext sequence, the cloud storage module restores the tea refining ciphertext data according to the tea refining ciphertext sequence to obtain tea refining data to be processed, and stores the tea refining data to be processed; The steps to convert and generate tea refining ciphertext data are as follows: S11: performing binary conversion on the tea refining data to be processed, and recalibrating the converted data into tea refining data; S12: Mark the binary numbers of digits 0 to 15 as A0, A1...A15 in sequence, then take every four characters in the tea refined base data as a base combination from left to right to obtain a plurality of base combinations, and traverse the plurality of base combinations, respectively count the number of base combinations that are consistent with the binary numbers A0, A1...A15, mark them as the indication frequency of the corresponding binary numbers, and mark them as B0, B1...B15 accordingly; S13: Match B0 with all the numerical intervals included in the indication weight table, obtain the frequency weight corresponding to the matching numerical interval, and mark it as the indication weight C0 of the binary number A0; S14: Calculate and obtain the indication weights C1, C2, ... C15 of the binary numbers A1, A2, ... A15 in sequence according to S13: S15: creating a first, second, third, fourth, and fifth indication list D1, D2, D3, D4, and D5 in sequence, and limiting the list lengths of the first, second, third, fourth, and fifth indication lists to be 5, 4, 3, 2, and 2, respectively; S16: Performing a first round of training on the binary numbers A0, A1, ...A15 according to a preset round training comparison rule to obtain a round identifier of all binary numbers after a round and a round number of bits; S17: performing the second, third, fourth and fifth rounds of training on the binary numbers A0, A1...A15 in sequence according to S16 to obtain the second, third, fourth and fifth rounds of identification and the second, third, fourth and fifth rounds of digits; S18: Calculate the sum of the first, second, third, fourth and fifth round identifiers of the binary number A0 and use it as the round training identifier H1 of the binary number A0, traverse the first, second, third, fourth and fifth round digits of the binary number A0, obtain the numbers of which are 0, 1, 2, 3, 4 respectively, and mark them as I1, I2, I3, I4 and I5; Using the formula Calculate and obtain the round-robin conversion index J0 of the binary number A0 after round-robin training, where β1 and β2 are the preset first and second adjustment factors, and ⋋1, ⋋2, ⋋3, ⋋4, and ⋋5 are the preset first, second, third, fourth, and fifth weights, respectively; S19: according to S18, the round-robin conversion indexes J1, J2 ... J15 of the binary numbers A1, A2 ... A15 after round-robin are calculated in sequence, the binary numbers A0, A1 ... A15 are sorted from large to small according to the round-robin conversion indexes from large to small, and all the sorted binary numbers are recalibrated as K0, K1 ... K15; S110: According to the binary numbers K0, K1...K15, the binary numbers K0, K1...K7 are mapped to binary numbers K8, K9...K15 respectively; S111: Mark all the system combinations obtained in S12 as L1, L2, ..., L1 in order according to the order in which they are obtained, obtain a binary number consistent with the system combination L1, obtain a mapping system of the binary number, and use the mapping system as a conversion system of the system combination L1; S112: according to S111, the conversion bases of base combinations L2, L3 ... L1 are calculated in sequence, and the conversion bases are spliced ​​in the order of base combinations L1, L2 ... L1 to obtain the tea refined ciphertext data; In the order of indication frequencies B0, B1...B15, the indication frequencies B0, B1...B15 are concatenated to obtain a tea refining ciphertext sequence.

2. A tea refining production traceability method according to claim 1, characterized in that: Before completing step 1, you need to do the following: The production information collection module collects tea information from each link of tea refining production, generates tea refining production data according to the collected tea information from each link of tea refining production, and transmits the tea refining production data to the classification interaction module.

3. A tea refining production traceability method according to claim 2, characterized in that: The classification interaction module pre-stores a base weight table and a frequency weight table. The base weight table contains binary numbers from 0 to 15 and their basic weights, and the frequency weight table contains several numerical intervals and their frequency weights.

4. A tea refining production traceability method according to claim 1, characterized in that: The round-by-round comparison rules for obtaining the round-by-round identifiers of all binary numbers after one round and the number of digits in one round are as follows: S161: Using formula Calculate and obtain the additional evaluation index F0 of the binary number A0, where E0 is the basic weight of the binary number A0, and ɑ1 is the preset dimension adjustment factor; S162: according to S161, the additional evaluation indicators F1, F2...F15 of the binary numbers A1, A2...A15 are calculated in sequence, and the binary number corresponding to the additional evaluation indicator with the largest value is selected and added to the first indication list D1, and after the addition is completed, the basic weight of the corresponding binary number is updated to the selected additional evaluation indicator with the largest value according to the selected additional evaluation indicator with the largest value; S163: adding the corresponding binary numbers of the evaluation indicators F1, F2, ... F15 in the order of large to small to the first, second, third, fourth, and fifth indication lists in sequence, and updating the basic weight of the binary number from the base weight table each time a binary number is added; S164: For all binary numbers belonging to the first index list D1, their round identifiers are all 1, and the subscript indexes of all binary numbers in the first index list D1 are the corresponding round digits; S165: For all binary numbers belonging to the second index list D2, their round identifiers are all 2, and the subscript indexes of all binary numbers in the second index list D2 are the corresponding round digits; S166: Obtain the round identifiers and round digits of all binary numbers after one round according to S164 to S165, wherein the round identifiers of all binary numbers in the third, fourth and fifth index lists are 3, 4 and 5 respectively.

5. A tea refining production traceability system, characterized in that: include: The production information collection module is used to collect tea information from each link of tea refining production. The production information collection module collects tea information from each link of tea refining production and generates tea refining production data based on the collected tea information from each link of tea refining production; A classification interaction module is used to transmit tea information of each link in tea refining production by type, extract tea information of several links from the tea refining production data according to a preset classification information list, generate tea refining plaintext traceability data according to the extracted tea information of several links, and transmit it to the cloud storage module; The tea information of all processes remaining after the extraction of the tea refining production data is generated into tea refining to-be-processed data, and converted into tea refining ciphertext data and tea refining ciphertext sequence according to a preset conversion rule, and transmitted them to the cloud storage module; A cloud storage module is used to store tea information at all stages of tea refining production in the cloud; The steps to convert and generate tea refining ciphertext data are as follows: S11: performing binary conversion on the tea refining data to be processed, and recalibrating the converted data into tea refining data; S12: Mark the binary numbers of digits 0 to 15 as A0, A1...A15 in sequence, then take every four characters in the tea refined base data as a base combination from left to right to obtain a plurality of base combinations, and traverse the plurality of base combinations, respectively count the number of base combinations that are consistent with the binary numbers A0, A1...A15, mark them as the indication frequency of the corresponding binary numbers, and mark them as B0, B1...B15 accordingly; S13: Match B0 with all the numerical intervals included in the indication weight table, obtain the frequency weight corresponding to the matching numerical interval, and mark it as the indication weight C0 of the binary number A0; S14: Calculate and obtain the indication weights C1, C2, ... C15 of the binary numbers A1, A2, ... A15 in sequence according to S13: S15: creating a first, second, third, fourth, and fifth indication list D1, D2, D3, D4, and D5 in sequence, and limiting the list lengths of the first, second, third, fourth, and fifth indication lists to be 5, 4, 3, 2, and 2, respectively; S16: Performing a first round of training on the binary numbers A0, A1, ...A15 according to a preset round training comparison rule to obtain a round identifier of all binary numbers after a round and a round number of bits; S17: performing the second, third, fourth and fifth rounds of training on the binary numbers A0, A1...A15 in sequence according to S16 to obtain the second, third, fourth and fifth rounds of identification and the second, third, fourth and fifth rounds of digits; S18: Calculate the sum of the first, second, third, fourth and fifth round identifiers of the binary number A0 and use it as the round training identifier H1 of the binary number A0, traverse the first, second, third, fourth and fifth round digits of the binary number A0, obtain the numbers of which are 0, 1, 2, 3, 4 respectively, and mark them as I1, I2, I3, I4 and I5; Using the formula Calculate and obtain the round-robin conversion index J0 of the binary number A0 after round-robin training, where β1 and β2 are the preset first and second adjustment factors, and ⋋1, ⋋2, ⋋3, ⋋4, and ⋋5 are the preset first, second, third, fourth, and fifth weights, respectively; S19: according to S18, the round-robin conversion indexes J1, J2 ... J15 of the binary numbers A1, A2 ... A15 after round-robin are calculated in sequence, the binary numbers A0, A1 ... A15 are sorted from large to small according to the round-robin conversion indexes from large to small, and all the sorted binary numbers are recalibrated as K0, K1 ... K15; S110: According to the binary numbers K0, K1...K15, the binary numbers K0, K1...K7 are mapped to binary numbers K8, K9...K15 respectively; S111: Mark all the system combinations obtained in S12 as L1, L2, ..., L1 in order according to the order in which they are obtained, obtain a binary number consistent with the system combination L1, obtain a mapping system of the binary number, and use the mapping system as a conversion system of the system combination L1; S112: according to S111, the conversion bases of base combinations L2, L3 ... L1 are calculated in sequence, and the conversion bases are spliced ​​in the order of base combinations L1, L2 ... L1 to obtain the tea refined ciphertext data; In the order of indication frequencies B0, B1...B15, the indication frequencies B0, B1...B15 are concatenated to obtain a tea refining ciphertext sequence.

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