CN117034361A - Gene detection and inspection laboratory information management method and system - Google Patents
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Abstract
The application is applicable to the technical field of data processing, and provides a method and a system for managing information of a gene detection and inspection laboratory, wherein the method comprises the following steps: collecting relevant information of gene detection and inspection; each related information is associated, encrypted and uploaded to a blockchain, and is used for tracing and inquiring; and constructing a network security situation model to evaluate the blockchain network. The application not only can provide complete data support for tracing inquiry, but also can ensure confidentiality, privacy and safety of gene detection and inspection information.
Description
Technical Field
The application belongs to the technical field of data processing, and particularly relates to a method and a system for managing information of a gene detection laboratory.
Background
Currently, genetic testing techniques are becoming mature, and according to statistics genetic testing is usually performed in a laboratory. With the increasing demand for genetic testing, a great deal of data and important information are continuously generated and recorded.
Huge data information relies on manual filling, statistics, calculation and report programming, is difficult to record, track and control the whole circulation and processing flow of samples, is difficult to trace when quality problems occur, and trojans, viruses and software programs with threat are silently immersed in a gene detection and inspection laboratory to steal information and spread bad information.
Disclosure of Invention
In view of the above, the embodiments of the present application provide a method and a system for managing information in a genetic testing laboratory, so as to solve the above technical problems.
A first aspect of an embodiment of the present application provides a method for managing information in a genetic testing laboratory, including:
collecting relevant information of gene detection and inspection;
each related information is associated, encrypted and uploaded to a blockchain, and is used for tracing and inquiring, and the method specifically comprises the following steps:
marking each gene to be tested to generate a unique ID;
carrying out association and encryption calculation on the related information and ID of each gene to be detected together to generate a corresponding secret key L;
storing the key L and the corresponding ID in the blockchain;
when tracing inquiry is carried out, searching a secret key L through the ID;
after inquiring to obtain the key L, decrypting the key L through a decryption algorithm to obtain the related information of the gene to be detected, so as to realize retrospective inquiry;
constructing a network security posture model to evaluate the blockchain network, wherein:
each related information is associated, encrypted and uploaded to the blockchain for traceability and inquiry, and the method further comprises the following steps:
and correlating the relevant information, encrypting and uploading the information to a blockchain, monitoring the load information of each node in the blockchain in real time, constructing a decision matrix according to the node load information, and evaluating the load of each node according to the decision matrix so as to realize dynamic balancing of the load of each node and further improve the tracing inquiry response speed.
Preferably, the load information of each node in the blockchain comprises node CPU, memory and bandwidth information; the decision moment M constructed by the load information is as follows:
in the above formula, M is a decision matrix, n is a cycle number, and CUR, MUR and BUR are the utilization rates of CPU, memory and bandwidth respectively.
A second aspect of an embodiment of the present application provides a gene detection test laboratory information management system, comprising:
the acquisition module is used for acquiring related information of gene detection and inspection;
the management module is used for carrying out association, encryption and uploading on each related information to the blockchain and for tracing and inquiring, and specifically:
marking each gene to be tested to generate a unique ID;
carrying out association and encryption calculation on the related information and ID of each gene to be detected together to generate a corresponding secret key L;
storing the key L and the corresponding ID in the blockchain;
when tracing inquiry is carried out, searching a secret key L through the ID;
after inquiring to obtain the key L, decrypting the key L through a decryption algorithm to obtain the related information of the gene to be detected, so as to realize retrospective inquiry;
each related information is associated, encrypted and uploaded to the blockchain for traceability and inquiry, and the method further comprises the following steps:
the method comprises the steps of associating each relevant information, encrypting and uploading the relevant information to a block chain, monitoring load information of each node in the block chain in real time, constructing a decision matrix according to the node load information, and evaluating the load of each node according to the decision matrix so as to realize dynamic balancing of the load of each node, thereby improving the retrospective query response speed;
the load information of each node in the block chain comprises node CPU, memory and bandwidth information; the decision moment M constructed by the load information is as follows:
in the above formula, M is a decision matrix, n is a cycle number, and CUR, MUR and BUR are the utilization rates of CPU, memory and bandwidth respectively;
and the evaluation module is used for constructing a network security situation model so as to evaluate the blockchain network.
A third aspect of an embodiment of the application provides an electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the method according to the first aspect when executing the computer program.
A fourth aspect of the embodiments of the present application provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the method according to the first aspect.
From the above, compared with the prior art, the application has at least the following advantages:
1. according to the application, by correlating each related information of gene detection and inspection, complete data support can be provided for tracing and inquiring, so that information such as sample acquisition information, patient information, sample experiment progress information, use reagent information, detection result, detection report and the like can be traced, when quality problems occur, problem points can be determined at the first time, and the correlated data are encrypted and uploaded to a blockchain, so that confidentiality, privacy and safety of the gene detection and inspection information can be ensured.
2. The application can ensure the safety and reliability of the gene detection and inspection information because the safety situation evaluation is carried out on the blockchain network stored with the gene detection and inspection information.
3. According to the application, as the related information is detected and inspected through the two-dimension code acquisition gene, manual input is avoided, and the information acquisition efficiency and accuracy can be effectively improved.
4. The method and the device upload the case number of the gene to be tested and the encrypted secret key to the blockchain, so that the information can be stored on the chain under the condition that any information of the gene to be tested is not exposed, and the safety and privacy of the information can be effectively ensured.
5. According to the application, the network security situation model is constructed through the important characteristic data in the block chain network selected by screening, so that the model prediction or evaluation precision can be effectively improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for managing information in a genetic testing laboratory according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a system for managing information of a genetic testing laboratory according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
As used in this specification and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]".
In particular implementations, the electronic devices described in embodiments of the application include, but are not limited to, other portable devices such as mobile phones, laptop computers, or tablet computers having touch-sensitive surfaces (e.g., touch screen displays and/or touchpads). It should also be appreciated that in some embodiments, the device is not a portable communication device, but a desktop computer having a touch-sensitive surface (e.g., a touch screen display and/or a touch pad).
In the following discussion, an electronic device including a display and a touch-sensitive surface is described. However, it should be understood that the electronic device may include one or more other physical user interface devices such as a physical keyboard, mouse, and/or joystick.
The electronic device supports various applications, such as one or more of the following: drawing applications, presentation applications, word processing applications, website creation applications, disk burning applications, spreadsheet applications, gaming applications, telephony applications, video conferencing applications, email applications, instant messaging applications, workout support applications, photo management applications, digital camera applications, digital video camera applications, web browsing applications, digital music player applications, and/or digital video player applications.
Various applications that may be executed on the electronic device may use at least one common physical user interface device such as a touch-sensitive surface. One or more functions of the touch-sensitive surface and corresponding information displayed on the electronic device may be adjusted and/or changed between applications and/or within the corresponding applications. In this way, a common physical architecture (e.g., touch-sensitive surface) of the electronic device may support various applications with user interfaces that are intuitive and transparent to the user.
It should be understood that, the sequence number of each step in this embodiment does not mean the execution sequence, and the execution sequence of each process should be determined by its function and internal logic, and should not limit the implementation process of the embodiment of the present application in any way.
In order to illustrate the technical scheme of the application, the following description is made by specific examples.
Referring to fig. 1, fig. 1 is a flow chart of a method for managing information of a genetic testing laboratory according to an embodiment of the present application, as shown in fig. 1, a method for managing information of a genetic testing laboratory includes the following steps:
collecting relevant information of gene detection and inspection;
each related information is associated, encrypted and uploaded to a blockchain, and is used for tracing and inquiring;
and constructing a network security situation model to evaluate the blockchain network.
Obviously, through correlating each relevant information of gene detection inspection, can provide complete data support for tracing inquiry to can trace back information such as sample collection information, patient information, sample experiment progress information, use reagent information, testing result and detection report, and then when the quality problem appears, can confirm the problem point in the very first time, and upload the relevant data encryption to the blockchain moreover, can ensure confidentiality, privacy and the security of gene detection inspection information.
Meanwhile, since the blockchain network storing the gene detection and inspection information is subjected to security situation assessment, the security and reliability of the gene detection and inspection information can be ensured.
In some embodiments, the collection of genetic testing examines various relevant information, including the following:
and (5) detecting and checking each relevant information through two-dimension code acquisition genes.
Because each relevant information is detected and inspected through the two-dimension code acquisition genes, manual input is avoided, and the information acquisition efficiency and accuracy can be effectively improved.
In this embodiment, the relevant information data of the genetic test includes genetic test application form data, sample collection data, sample quality test data, library quality test data, sequencing machine-on-the-fly data, sequencing data quality index data, test result record data, test report data and abnormal condition data.
In some embodiments, each related information is associated, encrypted up to the blockchain, and provided for retrospective querying, including the following:
generating a unique identification code for the current gene to be detected as a specific case number;
performing association and encryption calculation on each piece of relevant information corresponding to each gene to be tested to obtain a key belonging to the gene to be tested;
wherein, after correlating each relevant information corresponding to each gene to be tested, the correlation of the relevant information can be calculated;
the calculation formula of the correlation is as follows:
wherein K is a correlation, D 1 Is the total word number of any one data in the related information, Y 1 X is the average value of all data in the related information 1 For the total number of words of any one data in the similar information, C 1 For the average value of all data in the similar information, j is the search times of the data number, t 1 To retrieve the time mean value, t 2 To retrieve the total time;
the similar information is obtained by searching all information through a big data technology, extracting keywords in all information, wherein at least two groups of data with the keyword repetition rate reaching 1/3 of the total word number of all information are set as the similar information; and the related information is sequenced from big to small according to the correlation size, so that the subsequent tracing is convenient.
The case number and key are uploaded to the blockchain.
Obviously, by uploading the case number of the gene to be detected and the encrypted secret key to the blockchain, the information can be stored on the chain under the condition that any information of the gene to be detected is not exposed, and the safety and privacy of the information can be effectively ensured. During the trace back process. The tracing is started from the related information with the largest correlation, so that the tracing efficiency can be greatly improved, the tracing occupied time is saved, and the tracing accuracy is enhanced. The accuracy of correlation calculation is greatly enhanced by calculating correlation of the related information and the similar information.
In this embodiment, each relevant information is associated, encrypted and uploaded to the blockchain, and is used for traceback query, which may further include the following contents:
inquiring a secret key corresponding to the gene to be tested according to the gene to be tested case number;
and decrypting each piece of related information of the encrypted gene to be tested according to the secret key so as to realize the traceability query.
Specifically, each relevant information is associated, encrypted and uploaded to the blockchain, and is used for retrospective inquiry, and the method comprises the following steps:
marking each gene to be tested to generate a unique ID;
carrying out association and encryption calculation on the related information and ID of each gene to be detected together to generate a corresponding secret key L;
storing the key L and the corresponding ID in the blockchain;
when tracing inquiry is carried out, searching a secret key L through the ID;
after the key L is obtained by inquiry, the key L is decrypted through a decryption algorithm to obtain the related information of the gene to be detected, so that the retrospective inquiry is realized.
Obviously, the privacy and the integrity of the gene inspection detection information can be ensured through the scheme; meanwhile, based on the characteristic of distributed storage of the block chain, the information storage pressure can be effectively reduced, and the cost is saved.
In some embodiments, each related information is associated, encrypted up to the blockchain, and provided for retrospective querying, including the following:
the method comprises the steps of associating each relevant information, encrypting and uploading the relevant information to a block chain, monitoring load information of each node in the block chain in real time, constructing a decision matrix according to the node load information, and evaluating the load of each node according to the decision matrix so as to realize dynamic balancing of the load of each node, thereby improving the retrospective query response speed;
the load information of each node in the block chain comprises information such as a node CPU, a memory, a bandwidth and the like; the decision moment M constructed from the load information is as follows:
in the above formula, M is a decision matrix, n is a cycle number, and CUR, MUR and BUR are the utilization rates of CPU, memory and bandwidth respectively;
obviously, the blockchain has the distributed storage characteristic, and the distributed storage environment has the isomerism of node resources, so that the transmission of data among nodes is reduced in the data analysis and calculation process, the node calculation resources are fully utilized, and the response speed of retrospective query can be improved through dynamic adjustment of load balancing.
In some embodiments, a network security posture model is built to evaluate a blockchain network, including the following:
and screening important characteristic data in the blockchain network, and constructing a network security situation model according to the important characteristic data so as to evaluate the blockchain network.
Obviously, the network security situation model constructed by the screened important characteristic data in the blockchain network can effectively improve the model prediction or evaluation precision.
In this embodiment, important feature data in a blockchain network is screened, and a network security situation model is constructed according to the important feature data to evaluate the blockchain network, where the important feature data in the blockchain network is screened, and includes the following contents:
training and acquiring a verification model by using characteristic data in the current all block chain network;
verifying the verification model effect through the verification set, and further calculating loss raw ；
The data corresponding to one feature f of the verification set is disturbed, and loss is predicted again and obtained f ；
The scores are subjected to difference to obtain the importance imp of the feature f to the prediction f ＝|loss f -loss raw |；
Each feature data in the block chain network is executed according to the method in sequence, and the importance of each feature to prediction is obtained;
and screening out important characteristic data in the blockchain network according to the importance obtained by calculation.
Obviously, the above-mentioned important characteristic data screening scheme is implemented after model training is completed, and no other models need to be trained, so that time can be effectively saved.
Meanwhile, the scheme can obtain the numerical measurement of the importance of each feature to the model, so that the importance of which feature is visually obtained and the importance of the feature is greatly beneficial to improving the accuracy of the model evaluation result.
In this embodiment, a network security situation model is constructed to evaluate a blockchain network, including the following:
capturing network data and preprocessing to obtain data items and index values;
classifying the data items and the index values through a support vector machine;
and calculating and outputting an evaluation result of the blockchain network according to the evaluation result and the weight strategy.
In order to make the data item and index value meet the parameter requirement of the support vector machine, the data normalization is performed in a unified mode, so that the range is within the range of [0,1], and the normalization formula of the data item and index value is as follows:
in the above formula, F (i) is the index value after normalization; d (D) i Is the current index value.
Specifically, security situation levels are divided, wherein the security indexes are classified as relative security between 0.0 and 0.2; 0.2-0.5 is a mild hazard; 0.5-0.8 is moderate danger; 0.8-1.0 is a high risk.
Based on the same inventive concept, the gene detection test laboratory information management system provided in the embodiment of the application, as shown in fig. 2, includes:
an acquisition module 21 for acquiring information about each of the genetic tests;
the management module 22 is used for associating each related information, encrypting and uploading the related information to the blockchain, and providing for tracing and inquiring;
and the evaluation module 23 is used for constructing a network security situation model so as to evaluate the blockchain network.
Obviously, through correlating each relevant information of gene detection inspection, can provide complete data support for tracing inquiry to can trace back information such as sample collection information, patient information, sample experiment progress information, use reagent information, testing result and detection report, and then when the quality problem appears, can confirm the problem point in the very first time, and upload the relevant data encryption to the blockchain moreover, can ensure confidentiality, privacy and the security of gene detection inspection information.
Meanwhile, since the blockchain network storing the gene detection and inspection information is subjected to security situation assessment, the security and reliability of the gene detection and inspection information can be ensured.
Fig. 3 is a structural diagram of an electronic device according to an embodiment of the present application, and as shown in the drawing, the electronic device 4 of the embodiment includes: at least one processor 40 (only one is shown in fig. 3), a memory 41 and a computer program 42 stored in the memory 41 and executable on the at least one processor 40, the processor 40 implementing the steps in any of the various method embodiments described above when executing the computer program 42.
The electronic device 4 may be a computing device such as a desktop computer, a notebook computer, a palm computer, a cloud server, etc. The electronic device 4 may include, but is not limited to, a processor 40, a memory 41. It will be appreciated by those skilled in the art that fig. 3 is merely an example of the electronic device 4 and is not meant to be limiting of the electronic device 4, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., the electronic device may also include input-output devices, network access devices, buses, etc.
The processor 40 may be a central processing unit (CentralProcessingUnit, CPU), but may also be other general purpose processors, digital signal processors (DigitalSignalProcessor, DSP), application specific integrated circuits (ApplicationSpecificIntegratedCircuit, ASIC), field programmable gate arrays (Field-ProgrammableGateArray, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 41 may be an internal storage unit of the electronic device 4, such as a hard disk or a memory of the electronic device 4. The memory 41 may also be an external storage device of the electronic device 4, such as a plug-in hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (SecureDigital, SD) card, a flash card (FlashCard), etc. provided on the electronic device 4. Further, the memory 41 may also include both an internal storage unit and an external storage device of the electronic device 4. The memory 41 is used for storing the computer program and other programs and data required by the electronic device. The memory 41 may also be used for temporarily storing data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/electronic device and method may be implemented in other manners. For example, the apparatus/electronic device embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical function division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a Read-only memory (ROM), a random access memory (RAM, randomAccessMemory), an electrical carrier signal, a telecommunication signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
The present application may also be implemented as a computer program product for implementing all or part of the steps of the method embodiments described above, when the computer program product is run on an electronic device, causing the electronic device to execute the steps of the method embodiments described above.
The above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (10)
1. A method for managing information in a genetic testing laboratory, comprising:
collecting relevant information of gene detection and inspection;
each related information is associated, encrypted and uploaded to a blockchain and is used for tracing and inquiring, and the method specifically comprises the following steps:
marking each gene to be tested to generate a unique ID;
carrying out association and encryption calculation on the related information and ID of each gene to be detected together to generate a corresponding secret key L;
storing the key L and the corresponding ID in the blockchain;
when tracing inquiry is carried out, searching a secret key L through the ID;
after inquiring to obtain the key L, decrypting the key L through a decryption algorithm to obtain the related information of the gene to be detected, so as to realize retrospective inquiry;
constructing a network security posture model to evaluate the blockchain network, wherein:
each related information is associated, encrypted and uploaded to the blockchain for traceability and inquiry, and the method further comprises the following steps:
and correlating the relevant information, encrypting and uploading the information to a blockchain, monitoring the load information of each node in the blockchain in real time, constructing a decision matrix according to the node load information, and evaluating the load of each node according to the decision matrix so as to realize dynamic balancing of the load of each node and further improve the tracing inquiry response speed.
2. The method of claim 1, wherein the associating, encrypting and uploading the relevant information to the blockchain, and providing for the traceback query, comprises:
generating a unique identification code for the current gene to be detected as a specific case number;
performing association and encryption calculation on each piece of relevant information corresponding to each gene to be tested to obtain a key belonging to the gene to be tested;
the case number and key are uploaded to the blockchain.
3. The method as recited in claim 2, further comprising:
inquiring a secret key corresponding to the gene to be tested according to the gene to be tested case number;
and decrypting each piece of related information of the encrypted gene to be tested according to the secret key so as to realize the traceability query.
4. The method of claim 1, wherein constructing a network security posture model to evaluate a blockchain network comprises:
and screening important characteristic data in the blockchain network, and constructing a network security situation model according to the important characteristic data so as to evaluate the blockchain network.
5. The method of claim 4, wherein filtering out important feature data in the blockchain network comprises:
training and acquiring a verification model by using characteristic data in the current all block chain network;
verifying the verification model effect through the verification set, and further calculating loss raw ；
The data corresponding to one feature f of the verification set is disturbed, and loss is predicted again and obtained f ；
The scores are subjected to difference to obtain the importance impf= |loss of the feature f on prediction f -loss raw |；
Sequentially executing the steps on each characteristic data in the block chain network to obtain the importance of each characteristic to prediction;
and screening out important characteristic data in the blockchain network according to the importance obtained by calculation.
6. The method of claim 1, wherein constructing a network security posture model to evaluate a blockchain network comprises:
capturing network data and preprocessing to obtain data items and index values;
classifying the data items and the index values through a support vector machine;
and calculating and outputting an evaluation result of the blockchain network according to the evaluation result and the weight strategy.
7. The method as recited in claim 6, further comprising: data normalization is carried out on the data items and the index values in a unified mode, so that the range of the data items and the index values is within the range of [0,1], and the normalization formulas of the data items and the index values are as follows:
in the above formula, F (i) is the index value after normalization; d (D) i Is the current index value.
8. The method of claim 1, wherein the load information of each node in the blockchain includes node CPU, memory, bandwidth information; the decision moment M constructed by the load information is as follows:
in the above formula, M is a decision matrix, n is a cycle number, and CUR, MUR and BUR are the utilization rates of CPU, memory and bandwidth respectively.
9. The method of claim 8, wherein the genetic testing examines each associated information, comprising: the method comprises the steps of gene detection application form data, sample acquisition data, sample quality inspection data, library quality inspection data, sequencing machine-on data, sequencing data quality index data, detection result record data, detection report data and abnormal condition data.
10. A genetic testing laboratory information management system, comprising:
the acquisition module is used for acquiring related information of gene detection and inspection;
the management module is used for carrying out association, encryption and uploading on each related information to the blockchain and for tracing and inquiring, and specifically:
marking each gene to be tested to generate a unique ID;
carrying out association and encryption calculation on the related information and ID of each gene to be detected together to generate a corresponding secret key L;
storing the key L and the corresponding ID in the blockchain;
when tracing inquiry is carried out, searching a secret key L through the ID;
after inquiring to obtain the key L, decrypting the key L through a decryption algorithm to obtain the related information of the gene to be detected, so as to realize retrospective inquiry;
each related information is associated, encrypted and uploaded to the blockchain for traceability and inquiry, and the method further comprises the following steps:
the method comprises the steps of associating each relevant information, encrypting and uploading the relevant information to a block chain, monitoring load information of each node in the block chain in real time, constructing a decision matrix according to the node load information, and evaluating the load of each node according to the decision matrix so as to realize dynamic balancing of the load of each node, thereby improving the retrospective query response speed;
and the evaluation module is used for constructing a network security situation model so as to evaluate the blockchain network.
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