Bioengineering data summarization method and system
By collecting and classifying data in the bioengineering data aggregation system, identifying data types and generating security levels, the problem of insufficient data leakage prevention capabilities in bioengineering data aggregation is solved, and safe aggregation and encryption of data are achieved.
Patent Information
- Application Number
- CN202411206831.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-30
- Publication Date
- 2025-01-24
AI Technical Summary
During the bioengineering research process, there is a problem of poor data leakage prevention capabilities after data aggregation, which leads to possible leakage of important aggregated data.
By collecting and classifying the target data, a sub-database is established, the target data type is identified and a security level is generated, encryption is performed according to the security level, and finally summary results are generated.
It achieves effective classification and identification of bioengineering data, and performs encryption processing according to the data security level, which improves data security and prevents data leakage.
Smart Images
Figure CN119358012A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the field of computers, and in particular to a bioengineering data aggregation method and system. Background Art
[0002] Bioengineering is generally considered to be an emerging technology that is based on the theories and techniques of biology, combined with modern engineering technologies such as chemical engineering, machinery, and electronic computers, and fully utilizes the latest achievements of molecular biology to consciously manipulate genetic material, directionally transform organisms or their functions, and create new species with ultra-distant traits in a short period of time. This type of "engineered bacteria" or "engineered cell lines" is then cultured on a large scale through suitable bioreactors to produce a large number of useful metabolites or exert their unique physiological functions.
[0003] In the process of bioengineering research, a large amount of data will be generated. In order to achieve the research objectives and improve the effectiveness of the data, various types of data will be summarized and counted. However, after the data are summarized, some important summary data may be generated. At present, the ability to prevent data leakage is poor when summarizing data. In view of the above problems, it is urgent to develop a bioengineering data summary method and system. Summary of the invention
[0004] The purpose of the embodiments of the present invention is to provide a bioengineering data aggregation method and system, aiming to solve the problems raised in the above background technology.
[0005] The embodiment of the present invention is implemented as follows: on the one hand, a bioengineering data aggregation method, the method comprising: Collect and classify targeted data for import; Establishment of sub-item database; Identify the target data type and generate the target data security level; Upload and store targeted data into the item database; Select the target data type and target summary model, and generate summary calculation execution instructions; Retrieve and identify the security level of targeted data and generate encryption execution instructions; Based on the summary calculation execution instructions and the encryption execution instructions, a targeted data summary result is generated.
[0006] As a further solution of the present invention, the identifying of the target data type and generating the target data security level specifically includes: Determine whether the target data type is within the range of safe data types; If the target data type is within the safe data type range; Generate a first-level security level and mark the targeted data; If the target data type is not within the range of safe data types; Generate secondary security levels and label targeted data.
[0007] As a further solution of the present invention, the selecting of the target data type and the target summary model and the generating of the summary calculation execution instruction specifically include: Input target data type encoding and target summary model; Calling targeted data from the item database; Generates summary calculation execution instructions.
[0008] As a further solution of the present invention, the retrieving and identifying the target data security level and generating the encryption execution instruction specifically includes: If the first security level is retrieved, an encrypted negative selection instruction is generated; If the secondary security level is retrieved, an encrypted positive selection instruction is generated.
[0009] As a further solution of the present invention, the generation of the targeted data summary result based on the summary calculation execution instruction and the encryption execution instruction specifically includes: Based on the first-level security level and the target summary model, run the summary calculation execution instruction to generate the plaintext target data summary result; Based on the secondary security level and the target summary model, the RSA algorithm and summary calculation execution instructions are run to calculate the target data summary results and generate the ciphertext target data summary results.
[0010] As a further solution of the present invention, on the other hand, a bioengineering data aggregation system comprises: A collection module, used for collecting targeted data; Classification import module, used to import targeted data by classification; Itemized database module, used to establish itemized database; A first identification module, used to identify the target data type; A first generating module, used to generate a targeted data security level; An upload storage module is used to upload and store targeted data to a sub-item database; A target aggregation module is used to establish a target aggregation model; A second generating module is used to generate summary calculation execution instructions; A retrieval module, used to retrieve the security level of targeted data; A second identification module is used to identify the security level of the target data; A third generating module is used to generate an encrypted execution instruction; The fourth generation module is used to generate targeted data summary results.
[0011] As a further solution of the present invention, the second generating module specifically includes: An input unit, used to input a target data type encoding and a target summary model; A calling unit, used for calling the targeted data in the item database; The first sub-generation unit is used to generate summary calculation execution instructions.
[0012] As a further solution of the present invention, the third generation module specifically includes: A second sub-generation unit, used to generate an encrypted negative selection instruction; The third sub-generation unit is used to generate an encrypted positive selection instruction.
[0013] As a further solution of the present invention, the fourth generation module specifically includes: A running unit, used to run summary calculation execution instructions; RSA algorithm unit, used to run the RSA algorithm.
[0014] The embodiments of the present invention provide a bioengineering data aggregation method and system. The system and method can classify and identify targeted data, and perform multi-type aggregation of different categories of targeted data according to a target aggregation model. At the same time, different levels of encryption measures can be implemented according to the security level of the targeted data, thereby further improving data security and preventing data leakage. BRIEF DESCRIPTION OF THE DRAWINGS
[0015] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0016] Figure 1 It is a main flow chart of a bioengineering data aggregation method; Figure 2 It is a flow chart for identifying target data types and generating target data security levels in a bioengineering data aggregation method; Figure 3 The invention relates to a flow chart of a bioengineering data aggregation method for selecting a target data type and a target aggregation model to generate aggregation calculation execution instructions; Figure 4 It is a flow chart for retrieving and identifying the security level of targeted data in a bioengineering data aggregation method to generate encrypted execution instructions; Figure 5The invention relates to a flow chart of generating a targeted data summary result based on summary calculation execution instructions and encryption execution instructions in a bioengineering data summary method; Figure 6 It is a main structure diagram of a bioengineering data aggregation system; Figure 7 It is a structural block diagram of the second generation module in a bioengineering data aggregation system; Figure 8 It is a structural block diagram of the third generation module in a bioengineering data aggregation system; Fig. 9 It is a structural block diagram of the fourth generation module in a bioengineering data aggregation system. DETAILED DESCRIPTION
[0017] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.
[0018] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.
[0019] The present invention provides a bioengineering data aggregation method and system, which solves the technical problems in the background technology.
[0020] like Figure 1 FIG. 1 is a main flow chart of a bioengineering data aggregation method provided by an embodiment of the present invention, wherein the bioengineering data aggregation method comprises: Step S100: collecting and classifying and importing targeted data; Step S200: Establishing a sub-item database; Step S300: Identify the target data type and generate the target data security level; Step S400: Upload and store the targeted data to the item database; Step S500: Select a target data type and a target summary model, and generate a summary calculation execution instruction; Step S600: Retrieve and identify the target data security level, and generate encryption execution instructions; Step S700: Generate a targeted data summary result based on the summary calculation execution instruction and the encryption execution instruction.
[0021] When the present embodiment is applied, the bioengineering targeted data to be summarized is first classified and imported into the system. The system is provided with a sub-item database. Various types of data are classified and coded in the sub-item database. Various types of targeted data can be classified and stored, and the targeted data type is identified. According to the identification result of the targeted data type, the targeted data is uploaded and stored in the sub-item database, waiting to be called during the subsequent summary calculation. After the targeted data type is identified, the security level of the targeted data is also generated according to the identification result. The administrator presets an encryption password. When the data security level is level one, the subsequent targeted data summary result can be directly displayed. When the data security level is level two, the targeted data summary result will be encrypted. When the targeted data summary result needs to be displayed, the preset encryption password needs to be entered, and the targeted data summary result will be displayed. Then, a target summary model is selected. According to the required summary result of the data, an appropriate target summary model can be selected, such as calculation models such as addition, subtraction, multiplication, division, and function operation. Then, based on the selected The system selects the target data type and target summary model, generates summary calculation execution instructions, and then retrieves and identifies the security level of the target data, generates encryption execution instructions, based on the summary calculation execution instructions and the encryption execution instructions, the system calls the target data in a directionally manner according to the selected target data type and target summary model, and performs summary calculation on the target data called in a directionally manner through the selected target summary model, and finally generates the required data summary result, if the security level of the target data is level one, generates an encryption negative selection instruction, and does not need to encrypt the target data summary result, if the security level of the target data summary result is level two, generates a positive encryption selection instruction, and encrypts the target data summary result; the system and method can classify and identify the target data, and perform multi-type summarization of different categories of target data according to the target summary model, and at the same time, can implement different levels of encryption measures according to the security level of the target data, further improving data security and preventing data leakage.
[0022] like Figure 2 As shown, as a preferred embodiment of the present invention, the identifying of the target data type and generating the target data security level specifically includes: Step S301: Determine whether the target data type is within the range of safe data types; Step S302: If the target data type is within the safe data type range; Step S303: Generate a first-level security level and mark the targeted data; Step S304: If the target data type is not within the range of the safe data type; Step S305: Generate a secondary security level and mark the targeted data.
[0023] When this embodiment is applied, the bioengineering data type is limited, and the system presets several types of security data. After the targeted data is classified and imported, the system will identify the type of the targeted data, and then determine whether the targeted data type is within the range of the security data type. If the targeted data type is within the range of the security data type, a first-level security level is generated, and the input targeted data is marked. The target data summary result can be directly displayed. If the targeted data type is not within the range of the security data type, a second-level security level is generated to prove that the targeted data needs to be encrypted to prevent leakage, and the input targeted data is marked. The target data summary result can be displayed after the encryption password is entered.
[0024] like Figure 3 As shown, as a preferred embodiment of the present invention, the selection of the target data type and the target summary model and the generation of the summary calculation execution instruction specifically include: Step S501: input the target data type code and target summary model; Step S502: calling the targeted data in the item database; Step S503: Generate summary calculation execution instructions.
[0025] When this embodiment is applied, after all the target data are input, the various types of data are classified and encoded in the sub-item database, and the target data type code and the target summary model are input. According to the target data type code, the target data in the sub-item database is called, and then a summary calculation execution instruction is generated, waiting for the next step of summary calculation through the target summary model.
[0026] like Figure 4 As shown, as a preferred embodiment of the present invention, the retrieving and identifying the target data security level and generating the encryption execution instruction specifically includes: Step S601: if the first-level security level is retrieved, an encrypted negative selection instruction is generated; Step S602: If the second-level security level is retrieved, an encrypted positive selection instruction is generated.
[0027] It should be understood that by retrieving and identifying the security level of the targeted data, if the first-level security level is retrieved, an encrypted negative selection instruction is generated, and there is no need to encrypt the subsequent targeted data summary results. If the second-level security level is retrieved, an encrypted positive selection instruction is generated, and the subsequent targeted data summary results need to be encrypted. The encryption method can use the RSA algorithm for asymmetric encryption, and then input the key for decryption to obtain plaintext data.
[0028] like Figure 5 As shown, as a preferred embodiment of the present invention, the generation of the targeted data summary result based on the summary calculation execution instruction and the encryption execution instruction specifically includes: Step S701: Based on the first-level security level and the target summary model, run the summary calculation execution instruction to generate a plaintext targeted data summary result; Step S702: Based on the secondary security level and the target summary model, run the RSA algorithm and summary calculation execution instructions, calculate the target data summary result, and generate a ciphertext target data summary result.
[0029] When this embodiment is applied, if the target data is at the first level security level, the summary calculation execution instruction is run, and the plaintext target data summary result is calculated and generated through the target summary model. If the target data is at the second level security level, the RSA algorithm and the summary calculation execution instruction are run, and the target data summary result is encrypted through the target summary model, and the ciphertext target data summary result is calculated and generated.
[0030] like Figure 6 As shown, as another preferred embodiment of the present invention, on the other hand, a bioengineering data aggregation system, the system comprises: The acquisition module 100 is used to acquire the targeting data; A classification import module 200 is used to classify and import targeted data; The sub-item database module 300 is used to establish a sub-item database; A first identification module 400 is used to identify the target data type; A first generating module 500, for generating a targeted data security level; The upload storage module 600 is used to upload and store the targeted data to the item database; A target aggregation model 700 is used to establish a target aggregation model; The second generating module 800 is used to generate a summary calculation execution instruction; A retrieval module 900 is used to retrieve the security level of the targeted data; The second identification module 1000 is used to identify the security level of the target data; The third generating module 1100 is used to generate an encrypted execution instruction; The fourth generating module 1200 is used to generate a targeted data summary result.
[0031] When this embodiment is applied, the acquisition module 100 acquires the targeted data, the classification import module 200 classifies and imports the targeted data, the sub-item database module 300 establishes the sub-item database, the first identification module 400 identifies the type of the targeted data, the first generation module 500 generates the security level of the targeted data, the upload storage module 600 uploads and stores the targeted data to the sub-item database, the target summary module 700 establishes the target summary model, the second generation module 800 generates the summary calculation execution instruction, the retrieval module 900 retrieves the security level of the targeted data, the second identification module 1000 identifies the security level of the targeted data, the third generation module 1100 generates the encryption execution instruction, and the fourth generation module 1200 generates the targeted data summary result.
[0032] like Figure 7 As shown, as another preferred embodiment of the present invention, the second generating module 800 specifically includes: An input unit 801 is used to input a target data type code and a target summary model; A calling unit 802 is used to call the target data in the item database; The first sub-generation unit 803 is used to generate a summary calculation execution instruction.
[0033] When this embodiment is applied, the target data type code and the target summary model are input through the input unit 801, the calling unit 802 calls the target data in the sub-item database, and the first sub-generation unit 803 generates a summary calculation execution instruction.
[0034] like Figure 8 As shown, as another preferred embodiment of the present invention, the third generating module 1100 specifically includes: The second sub-generation unit 1101 is used to generate an encrypted negative selection instruction; The third sub-generation unit 1102 is used to generate an encrypted positive selection instruction.
[0035] When this embodiment is applied, if the first-level security level is retrieved, the second sub-generation unit 1101 generates an encrypted negative selection instruction, and if the second-level security level is retrieved, the third sub-generation unit 1102 generates an encrypted positive selection instruction.
[0036] like Fig. 9 As shown, as another preferred embodiment of the present invention, the fourth generating module 1200 specifically includes: An execution unit 1201 is used to execute the summary calculation execution instruction; The RSA algorithm unit 1202 is used to run the RSA algorithm.
[0037] When this embodiment is applied, based on the first-level security level and the target summary model, the operation unit runs the summary calculation execution instruction, based on the second-level security level and the target summary model, the operation unit runs the summary calculation execution instruction, and the RSA algorithm unit runs the RSA algorithm.
[0038] The above embodiment of the present invention provides a bioengineering data aggregation method and a bioengineering data aggregation system. First, the bioengineering targeted data to be aggregated are classified and imported into the system. The system is provided with a sub-item database. Various types of data are classified and coded in the sub-item database. Various types of targeted data can be classified and stored. The targeted data type is identified. According to the identification result of the targeted data type, the targeted data is uploaded and stored in the sub-item database, waiting to be called during subsequent aggregation calculation. After the targeted data type is identified, the security level of the targeted data is also generated according to the identification result. The administrator presets an encryption password. When the data security level is level one, the subsequent targeted data aggregation result can be directly displayed. When the data security level is level two, the targeted data aggregation result will be encrypted. When the targeted data aggregation result needs to be displayed, the preset encryption password needs to be entered. The targeted data aggregation result will be displayed, and then the target aggregation model is selected. According to the required aggregation result of the data, an appropriate target aggregation model can be selected, such as addition, subtraction, multiplication and division. , function operation and other calculation models, and then based on the selected target data type and target summary model, generate summary calculation execution instructions, and then retrieve and identify the target data security level, generate encryption execution instructions, based on the summary calculation execution instructions and encryption execution instructions, the system calls the target data in a targeted manner according to the selected target data type and target summary model, and summarizes and calculates the targeted data called in a targeted manner through the selected target summary model, and finally generates the required data summary result, if the security level of the target data is level one, an encryption negative selection instruction is generated, and there is no need to encrypt the target data summary result, if the security level of the target data summary result is level two, a positive encryption selection instruction is generated to encrypt the target data summary result; the system and method can classify and identify the target data, and perform multi-type summarization of different categories of target data according to the target summary model, and at the same time, different levels of encryption measures can be implemented according to the security level of the target data, further improving data security and preventing data leakage.
[0039] In order to load the above-mentioned method and system and enable it to run smoothly, the system, in addition to the various modules mentioned above, may also include more or fewer components than described above, or a combination of certain components, or different components, for example, it may include input and output devices, network access devices, buses, processors and memories, etc.
[0040] The processor may be a central processing unit, or other general-purpose processors, digital signal processors, application-specific integrated circuits, off-the-shelf programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the system, and various interfaces and lines are used to connect various parts.
[0041] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0042] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.
[0043] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.
Claims
1. A bioengineering data aggregation method, characterized in that: The method comprises: Collect, classify and import targeted data; Establishment of sub-item database; Identify the target data type and generate the target data security level; Upload and store targeted data into the item database; Select the target data type and target summary model, and generate summary calculation execution instructions; Retrieve and identify the security level of targeted data and generate encryption execution instructions; Based on the summary calculation execution instructions and the encryption execution instructions, a targeted data summary result is generated.
2. The bioengineering data aggregation method according to claim 1, characterized in that: The identifying of the target data type and generating the target data security level specifically includes: Determine whether the target data type is within the range of safe data types; If the target data type is within the safe data type range; Generate a first-level security level and mark the targeted data; If the target data type is not within the range of safe data types; Generate secondary security levels and label targeted data.
3. The bioengineering data aggregation method according to claim 1, characterized in that: The selecting of the target data type and the target summary model and the generating of the summary calculation execution instruction specifically include: Input target data type encoding and target summary model; Calling targeted data from the item database; Generates summary calculation execution instructions.
4. The bioengineering data aggregation method according to claim 3, characterized in that: The retrieving and identifying the target data security level and generating the encryption execution instruction specifically includes: If the first security level is retrieved, an encrypted negative selection instruction is generated; If the secondary security level is retrieved, an encrypted positive selection instruction is generated.
5. The bioengineering data aggregation method according to claim 1, characterized in that: The generating of the targeted data summary result based on the summary calculation execution instruction and the encryption execution instruction specifically includes: Based on the first-level security level and the target summary model, run the summary calculation execution instruction to generate the plaintext target data summary result; Based on the secondary security level and the target summary model, the RSA algorithm and summary calculation execution instructions are run to calculate the target data summary results and generate the ciphertext target data summary results.
6. A bioengineering data aggregation system, characterized in that: The system comprises: A collection module, used for collecting targeted data; Classification import module, used to import targeted data by classification; Itemized database module, used to establish itemized database; A first identification module, used to identify the target data type; A first generating module, used to generate a targeted data security level; An upload storage module is used to upload and store targeted data to a sub-item database; A target aggregation module is used to establish a target aggregation model; A second generating module is used to generate summary calculation execution instructions; A retrieval module, used to retrieve the security level of targeted data; A second identification module is used to identify the security level of the target data; A third generating module is used to generate an encrypted execution instruction; The fourth generation module is used to generate targeted data summary results.
7. The bioengineering data aggregation system according to claim 6, characterized in that: The second generation module specifically includes: An input unit, used to input a target data type encoding and a target summary model; A calling unit, used for calling the targeted data in the item database; The first sub-generation unit is used to generate summary calculation execution instructions.
8. The bioengineering data aggregation system according to claim 6, characterized in that: The third generation module specifically includes: A second sub-generation unit, used to generate an encrypted negative selection instruction; The third sub-generation unit is used to generate an encrypted positive selection instruction.
9. The bioengineering data aggregation system according to claim 6, characterized in that: The fourth generation module specifically includes: A running unit, used to run summary calculation execution instructions; RSA algorithm unit, used to run the RSA algorithm.