CN116074062A - Internet-based network security test tube control system - Google Patents
Internet-based network security test tube control system Download PDFInfo
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Abstract
The invention discloses a network security test tube control system based on the Internet, which particularly relates to the field of network security and is used for solving the problems that the existing network node test does not well judge the overall network security according to different states of each network node, so that a certain inaccuracy and surface property exist in a test result; the system comprises a main control module, a data acquisition module, a node analysis module, an output judgment module and a data storage module; when the network security is tested, the risk assessment is firstly carried out on each network node, the security state of the whole network is determined according to the importance degree of different network nodes and the distribution of the risk network nodes, and whether the determined network security state can be normally output is judged according to the testing time and times so as to ensure the accuracy of the whole network security test.
Description
Technical Field
The invention relates to the technical field of network security, in particular to a network security test tube control system based on the Internet.
Background
With the advent of the network age, the scale and application field of the internet have been continuously developed, so that the internet has been penetrated into the fields of daily life, economy, military, science and technology, education and the like, the basic and global status and effect are increasingly enhanced, and as an important basic technology, the network security problem has become an important factor for influencing the social and economic development;
because the importance degrees of different network nodes are different, the existing network node test does not well judge the overall network security according to the different states of each network node, and the overall network security judging process is aimed at, and the feedback type backtracking test content is not provided, so that the test result has certain inaccuracy and surface property;
the present invention proposes a solution to the above-mentioned problems.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, an embodiment of the present invention provides an internet-based network security test and control system, in which when testing network security, risk assessment is performed on each network node, the security state of the whole network is determined according to the importance degree of different network nodes and the distribution of risk network nodes, and then whether the determined network security state can be normally output is determined according to the testing time and times, so as to ensure the accuracy of the whole network security test, and solve the problems set forth in the background art.
In order to achieve the above purpose, the present invention provides the following technical solutions:
the network security test tube control system based on the Internet comprises a main control module, a data acquisition module, a node analysis module and a data storage module;
the main control module is in signal connection with the data acquisition module, the node analysis module and the data storage module and is used for issuing control instructions and receiving related data results;
the data storage module is used for storing data generated by the network security test tube control system in the whole management process;
the data acquisition module is used for acquiring node attribute data of the network nodes, sending the node attribute data to the data storage module for storage through the main control module, and sending the node attribute data to the node analysis module for analysis through the main control module, wherein the node analysis module calculates and obtains risk assessment coefficients of the network nodes;
the node analysis module determines risk network nodes according to the risk assessment coefficients of the network nodes, namely, node importance degree information of the risk network nodes in the data storage module is called, the importance degree of the risk network nodes is obtained through processing, and the overall network security coefficient is obtained through analyzing by combining the importance degrees of the risk network nodes and the risk network nodes.
In a preferred embodiment, the node attribute data includes node risk information, where the node risk information includes node attack frequency, node average memory utilization, node average CPU occupancy, node update time, and node average network speed;
after the node analysis module receives the node risk information, carrying out risk assessment on each network node, wherein the specific steps are as follows:
acquiring the attacked frequency of the node, the average memory utilization rate of the node, the average CPU occupancy rate of the node, the node update time and the average network speed of the node, and calculating to obtain a risk assessment coefficient RA of the network node through a formula;
comparing the risk assessment coefficient RA of the network node with a nominal risk threshold:
if the risk assessment coefficient RA of the network node is larger than or equal to the rated risk threshold value, generating a risk network node signal by a node analysis module at the moment;
if the risk assessment coefficient RA of the network node is smaller than the rated risk threshold, the node analysis module generates a normal network node signal.
In a preferred embodiment, the node attribute data further includes node importance information of the network node, the node importance information including a node communication value, a node function value, and a node asset value;
after the node analysis module analyzes the risk states of all the network nodes, acquiring risk state information of all the network nodes, and simultaneously, the node analysis module invokes node importance degree information of the risk network nodes in the data storage module and analyzes the importance degree of the risk network nodes, wherein the specific analysis process is as follows:
the node analysis module acquires node importance degree information of the risk network node, and calculates an importance degree evaluation coefficient I of the network node through a formula;
the node analysis module compares the importance assessment coefficient I with a standard importance threshold value:
if the importance degree evaluation coefficient I is larger than or equal to the standard importance degree threshold, generating an important risk network node by the node analysis module at the moment, otherwise, not generating any signal data;
and after the node analysis module analyzes the importance degrees of all the risk network nodes, calculating to obtain the number of all the important risk network nodes, and sending the number to the data storage module for storage.
In a preferred embodiment, after the node analysis module analyzes the risk status of each network node, the node analysis module further analyzes the regional distribution of each risk network node, and the specific analysis process is as follows:
acquiring the number of risk network nodes connected with the important risk network nodes, and calculating to obtain the discrete degree of the risk network nodes around each important risk network node σ i ；
The node analysis module adds and averages the discrete degree of the risk network nodes around each important risk network node, calculates the discrete degree of the risk network nodes around the average important risk network node, and marks the discrete degree as
Meanwhile, the node analysis module calculates the ratio of the risk network nodes to all network nodes, marks the ratio as the risk node ratio, and calculates the overall network security coefficient SF through a formula;
comparing the integral network security factor SF with a standard security threshold value to generate integral network security state information, wherein the integral network security state information specifically comprises:
if the integral network safety factor SF is greater than or equal to the standard safety threshold, the node analysis module generates an integral network safety signal and sends the integral network safety signal to the output judgment module and the data storage module, and the data storage module stores the integral network safety signal;
if the integral network safety factor SF is smaller than the standard safety threshold, the node analysis module generates an integral network dangerous signal and sends the integral network dangerous signal to the output judging module and the data storage module, and the data storage module stores the integral network dangerous signal;
and the output judging module is connected with the main control module through signals and is used for judging whether the network testing process meets the progress requirement.
In a preferred embodiment, the data acquisition module is further configured to acquire node test information of a network node, and send the node test information to the output determination module for analysis through the main control module; the node test information comprises node test duration and node test times;
after receiving the overall network security state information sent by the node analysis module, the output judgment module analyzes the overall network test process, and the specific analysis process is as follows:
node test information in the whole network test process is obtained, and a test precision coefficient Ka is obtained through formula calculation;
comparing the test accuracy factor Ka with a standard accuracy threshold:
if the test accuracy coefficient Ka is greater than or equal to the standard accuracy threshold value, outputting an integral network safety signal or an integral network danger signal by an output judging module at the moment;
if the test accuracy coefficient Ka is smaller than the standard accuracy threshold, the output judging module does not output the whole network security state information at the moment, generates a retest signal and sends the retest signal to the main control module, and the main control module retests the whole network security.
In a preferred embodiment, after the output determination module generates the retest signal, when the output determination module receives the global network security status information again, it compares it with the previous global network security status information stored in the data storage module:
if the safety state information of the whole network is the same, overlapping the two node testing time lengths, adding one node testing times, substituting the node testing times into a formula again to calculate and obtain a testing precision coefficient Ka, and comparing the testing precision coefficient Ka with a standard precision threshold again to judge the precision of the testing process:
if the test accuracy coefficient Ka is larger than or equal to the standard accuracy threshold value, outputting the overall network security state information, otherwise, continuously re-determining the overall network security until the accuracy of the test process meets the requirement.
In a preferred embodiment, after the output determination module generates the retest signal, when the output determination module receives the global network security status information again, it compares it with the previous global network security status information stored in the data storage module:
if the overall network security state information received by the output judging module is changed, setting the node testing duration and the node testing times as data acquired in the latest testing process based on the latest overall network security state information, and judging the accuracy of the testing process again.
The invention has the technical effects and advantages that:
when the network security is tested, the risk assessment is firstly carried out on each network node, the security state of the whole network is determined according to the importance degree of different network nodes and the distribution of the risk network nodes, and whether the determined network security state can be normally output is judged according to the testing time and times so as to ensure the accuracy of the whole network security test.
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Fig. 1 is a schematic structural diagram of a network security test tube control system based on the internet of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention relates to an internet-based network security test control system, which firstly carries out risk assessment on each network node when testing network security, and determining the security state of the whole network according to the importance degree of different network nodes and the distribution of risk network nodes, and judging whether the determined network security state can be normally output according to the time and the times of the test so as to ensure the accuracy of the whole network security test.
FIG. 1 shows a schematic diagram of a network security test tube control system based on the Internet, which specifically comprises a main control module, a data acquisition module, a node analysis module, an output judgment module and a data storage module;
the main control module is in signal connection with the data acquisition module, the node analysis module, the output judgment module and the data storage module, and is used for issuing control instructions and receiving related data results.
The data storage module is used for storing data generated by the network security test management system in the whole management process.
The data acquisition module is used for acquiring node attribute data of the network node, sending the node attribute data to the node analysis module for analysis through the main control module, and sending the node attribute data to the data storage module for storage.
The node attribute data of the network node comprises node risk information and node importance degree information:
the node risk information comprises node attacked frequency, node average memory utilization rate, node average CPU occupancy rate, node update time and node average network speed; the attacked frequency of the node refers to the frequency of the intrusion event in the running time period of the network node, and the greater the frequency of the intrusion event, the greater the risk of the network node is indicated; the average memory utilization rate of the node refers to the average utilization rate of the memory in the operation time period of the network node, and the larger the average utilization rate of the memory in the operation time period of the network node is, the more easily the blocking is caused, so that the risk is higher; the average CPU occupancy rate of the node refers to the average utilization rate of the CPU in the running time period of the network node, and the larger the value is, the longer the value influences the running service life of the network node on one hand, and the slower the running speed of the network node on the other hand, so that the larger the value is, the higher the risk is; the node update time refers to the interval duration of the last update of the network node, and the larger the value is, the older the version of the network node is, and the risk is correspondingly increased; the average network speed of the nodes refers to the average value of the network speed of the nodes in the running time period of the network nodes, and the higher the value is, the higher the running speed of the network nodes is, and the lower the risk is correspondingly.
After the node analysis module receives the node risk information, carrying out risk assessment on each network node, wherein the specific steps are as follows:
the node attacked frequency, the node average memory utilization rate, the node average CPU occupancy rate, the node update time and the node average network speed are respectively calibrated to F, PF, cur, LUT and Bps, and a risk assessment coefficient RA of the network node is obtained through formula calculation, wherein the specific calculation expression is as follows:
wherein a1, a2, a3, a4 and a5 are respectively preset proportionality coefficients of node attacked frequency, node average memory utilization, node average CPU occupancy rate, node update time and node average network speed, and a1 is more than a3 and more than a4 and more than a2 and more than a5 and more than 0;
comparing the risk assessment coefficient RA of the network nodes with a rated risk threshold value, and judging whether each network node is in a risk state:
if the risk assessment coefficient RA of the network node is larger than or equal to the rated risk threshold value, the comprehensive risk of the network node is larger, and a risk network node signal is generated for the network node by the node analysis module;
if the risk assessment coefficient RA of the network node is smaller than the rated risk threshold, the comprehensive risk of the network node at the moment is in a safe range, and the node analysis module at the moment generates a normal network node signal for the network node;
and after the node analysis module carries out risk assessment on each network node, calculating to obtain the total number of all risk network nodes.
The node importance degree information of the network nodes acquired by the data acquisition module comprises node communication values, node function values and node asset values; the node communication value refers to how many other network nodes the network node is in communication connection with, and the more other network nodes the network node is connected with, the more the node is at the central position of the whole network structure, namely the higher the importance degree is; the node function value refers to how many network nodes in the whole network play the same function as the network node, and the more network nodes with the same function as the network node, the higher the substitutability of the network node is, namely the lower the importance degree is; the node asset value is the sum of the hardware cost and the software benefit of the network node, the higher the hardware cost is, the higher the replacement cost is, namely the higher the importance degree is, the higher the software benefit is, the greater the damaged loss is, and therefore the greater the node asset value is, the higher the importance degree is.
After the node analysis module analyzes the risk states of all the network nodes, acquiring risk state information of all the network nodes, wherein the risk state information refers to risk network node signals and normal network node signals, and analyzing importance of the network nodes with high comprehensive risk, namely the risk network nodes, wherein the specific analysis process is as follows:
the node analysis module obtains node importance degree information of the risk network node, and respectively marks the node communication value, the node function value and the node asset value as CO, fn and GL, and the importance degree evaluation coefficient I of the network node is obtained through formula calculation, wherein the specific calculation expression is as follows:
wherein b1, b2 and b3 are respectively preset proportionality coefficients of node communication values, node function values and node asset values, and b2 is more than b1 and more than b3 is more than 0;
the node analysis module compares the importance degree evaluation coefficient I with a standard importance degree threshold value to determine whether each risk network node is an important network node or not:
if the importance degree evaluation coefficient I is greater than or equal to the standard importance degree threshold value, the importance degree of the risk network node at the moment is higher, and the node analysis module at the moment generates an important risk network node for the network node;
if the importance evaluation coefficient I is smaller than the standard importance threshold, it indicates that the importance of the risk network node is lower at this time, and the node analysis module does not generate any signal data at this time.
And after the node analysis module analyzes the importance degrees of all the risk network nodes, calculating to obtain the number of all the important risk network nodes, and sending the number to the data storage module for storage.
Because the network internal nodes are numerous, the whole network cannot be judged from the single state of each node, and therefore the whole network safety needs to be judged according to the comprehensive analysis of the operation states of all network nodes, the specific process is as follows:
after the node analysis module analyzes the risk states of all the network nodes, the node analysis module also analyzes the regional distribution of all the risk network nodes, and the specific analysis process is as follows:
acquiring the number of risk network nodes connected with the important risk network nodes, and calculating to obtain the discrete degree sigma of the peripheral risk network nodes of each important risk network node i The specific calculation expression is as follows:
wherein m is the total number of important risk network nodes, and Ni is the number of risk network nodes around each important risk network node;
when the degree of dispersion of the risk network nodes around the important risk network node is smaller, the larger the number of the risk network nodes around the important risk network node is, namely the larger the risk influence of the important risk network node is, the larger the overall network risk is, and otherwise, the risk influence of the important risk network node is smaller.
The node analysis module also analyzes each important windAdding and averaging the discrete degrees of the risk network nodes around the risk network nodes, calculating to obtain the discrete degrees of the risk network nodes around the average important risk network nodes, and calibrating the discrete degrees as
Meanwhile, the node analysis module calculates the ratio of the risk network nodes to all network nodes, namely, the ratio of the risk nodes is obtained, the ratio is calibrated as RR, the number of important risk network nodes is calibrated as S, the integral network safety coefficient SF is obtained through formula calculation, and the specific calculation expression is as follows:
wherein c1, c2 and c3 are respectively preset proportionality coefficients of the degree of dispersion of risk network nodes around the average important risk network node, the duty ratio of the risk nodes and the number of the important risk network nodes, and c1 is more than c3 is more than c2 is more than 0;
comparing the integral network security factor SF with a standard security threshold value to determine integral network security state information:
if the integral network safety factor SF is greater than or equal to the standard safety threshold, the integral network safety state is in accordance with the requirement, and the node analysis module generates an integral network safety signal and sends the integral network safety signal to the output judgment module and the data storage module, and the data storage module stores the integral network safety signal;
if the integral network safety factor SF is smaller than the standard safety threshold, the integral network safety state is not in accordance with the requirement, and the node analysis module generates an integral network dangerous signal and sends the integral network dangerous signal to the output judgment module and the data storage module, and the data storage module stores the integral network dangerous signal.
The data acquisition module is also used for acquiring node test information and sending the node test information to the output judgment module for analysis:
the node test information comprises node test duration and node test times; the node test duration refers to the duration used by all network node tests, and the longer the duration is, the longer the test is, the state of the network node is easy to change in the initial test, so that the possibility that the running states of the network nodes are different in the test is increased, and the inaccuracy of the test result is easy to cause; the node test times are how many times the network nodes are tested together, when the number of the network node test times is larger, the probability of misjudgment is smaller, the test result is more accurate, and it is required to be explained that all the network nodes are tested in each time;
after receiving the overall network security state information, the output judging module analyzes the overall network testing process, and the specific analysis process is as follows:
node test information is obtained, node test time length and node test times are respectively calibrated to be t and Fr, a test accurate coefficient Ka is obtained through formula calculation, and a specific calculation expression is as follows:
Ks＝d 1 Fr/d 2 t
wherein d1 and d2 are preset proportionality coefficients of node test times and node test duration respectively, and d1 is more than d2 is more than 0; t is more than 0, fr is a positive integer;
comparing the test precision coefficient Ka with a standard precision threshold value, and judging that the test process character does not meet the precision requirement:
if the test accuracy coefficient Ka is greater than or equal to the standard accuracy threshold, the test process is indicated to meet the accuracy requirement, and the output judging module outputs the overall network safety state information, namely the overall network safety signal or the overall network danger signal.
If the test accuracy coefficient Ka is smaller than the standard accuracy threshold, the test process is not in accordance with the accuracy requirement, the output judging module does not output the whole network security state information at the moment, a retest signal is generated and sent to the main control module, and the main control module retests the whole network security.
To explain further, when the test process does not meet the accuracy requirement, the integral network node retests, the output judging module receives the integral network security state information again, compares the integral network security state information with the previous integral network security state information stored by the data storage module, if the integral network security state information is the same, superimposes the test time length of the two nodes, adds one node test time, substitutes the node test time again into the formula to calculate the test accuracy coefficient Ka, compares the test accuracy coefficient Ka with the standard accuracy threshold again, judges the test process accuracy, if the test accuracy coefficient Ka is greater than or equal to the standard accuracy threshold at the moment, outputs the integral network security state information, otherwise, continues retesting the integral network security until the test process accuracy meets the requirement;
it should be noted that, if the overall network security state information received by the output determination module is changed after the retest, the pre-test result is cleared, and the accuracy of the testing process is determined for the first time, that is, the node test duration is the duration used by all the node tests, and the node test times is 1.
In summary, the invention comprehensively analyzes the risk states and the importance degrees of the network nodes, thereby evaluating the overall network security state, judging whether the testing process meets the precision requirement, further determining whether the tested overall network security result has significance, further enabling the network security test to be more accurate and meeting the actual requirements.
The above-mentioned preset scaling factor is used for balancing the duty ratio weight of each item of data in formula calculation so as to promote the accuracy of calculation results, the size of the factor is a specific numerical value obtained by quantizing each parameter, the subsequent comparison is convenient, and regarding the size of the factor, the corresponding weight factor coefficient is primarily set according to the number of sample data and the sample data of each group of sample data of a person skilled in the art, so long as the proportional relation between the parameter and the quantized numerical value is not affected.
The following points are also needed to be described:
firstly, in the drawings of the disclosed embodiments, only the structures related to the embodiments of the present disclosure are referred to, other structures can refer to the common design, and the same embodiment and different embodiments of the present disclosure can be combined with each other without conflict;
second, the application may be described in the general context of computer-executable instructions that are executed by a computer, and may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network, and where program modules may be located in both local and remote computer storage media, including storage devices;
finally, the foregoing is only illustrative of the present invention and is not to be construed as limiting thereof, and any modifications, equivalent arrangements, improvements or the like which fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (7)
1. The utility model provides a network security test tube control system based on internet which characterized in that: the system comprises a main control module, a data acquisition module, a node analysis module and a data storage module;
the main control module is in signal connection with the data acquisition module, the node analysis module and the data storage module and is used for issuing control instructions and receiving related data results;
the data storage module is used for storing data generated by the network security test tube control system in the whole management process;
the data acquisition module is used for acquiring node attribute data of the network nodes, sending the node attribute data to the data storage module for storage through the main control module, and sending the node attribute data to the node analysis module for analysis through the main control module, wherein the node analysis module calculates and obtains risk assessment coefficients of the network nodes;
the node analysis module determines risk network nodes according to the risk assessment coefficients of the network nodes, namely, node importance degree information of the risk network nodes in the data storage module is called, the importance degree of the risk network nodes is obtained through processing, and the overall network security coefficient is obtained through analyzing by combining the importance degrees of the risk network nodes and the risk network nodes.
2. An internet-based network security test tube control system according to claim 1, wherein: the node attribute data comprises node risk information, wherein the node risk information comprises node attacked frequency, node average memory utilization rate, node average CPU occupancy rate, node update time and node average network speed;
after the node analysis module receives the node risk information, carrying out risk assessment on each network node, wherein the specific steps are as follows:
acquiring the attacked frequency of the node, the average memory utilization rate of the node, the average CPU occupancy rate of the node, the node update time and the average network speed of the node, and calculating to obtain a risk assessment coefficient RA of the network node through a formula;
comparing the risk assessment coefficient RA of the network node with a nominal risk threshold:
if the risk assessment coefficient RA of the network node is larger than or equal to the rated risk threshold value, generating a risk network node signal by a node analysis module at the moment;
if the risk assessment coefficient RA of the network node is smaller than the rated risk threshold, the node analysis module generates a normal network node signal.
3. An internet-based network security test tube control system according to claim 1, wherein: the node attribute data also comprises node importance degree information of the network nodes, wherein the node importance degree information comprises node communication values, node function values and node asset values;
after the node analysis module analyzes the risk states of all the network nodes, acquiring risk state information of all the network nodes, and simultaneously, the node analysis module invokes node importance degree information of the risk network nodes in the data storage module and analyzes the importance degree of the risk network nodes, wherein the specific analysis process is as follows:
the node analysis module acquires node importance degree information of the risk network node, and calculates an importance degree evaluation coefficient I of the network node through a formula;
the node analysis module compares the importance assessment coefficient I with a standard importance threshold value:
if the importance degree evaluation coefficient I is larger than or equal to the standard importance degree threshold, generating an important risk network node by the node analysis module at the moment, otherwise, not generating any signal data;
and after the node analysis module analyzes the importance degrees of all the risk network nodes, calculating to obtain the number of all the important risk network nodes, and sending the number to the data storage module for storage.
4. An internet-based network security test tube control system according to claim 3, wherein: after the node analysis module analyzes the risk states of the network nodes, the node analysis module also analyzes the regional distribution of the risk network nodes, and the specific analysis process is as follows:
acquiring the number of risk network nodes connected with the important risk network nodes, and calculating to obtain the discrete degree of the risk network nodes around each important risk network node σ i ；
The node analysis module adds and averages the discrete degree of the risk network nodes around each important risk network node, calculates the discrete degree of the risk network nodes around the average important risk network node, and marks the discrete degree as sigma;
meanwhile, the node analysis module calculates the ratio of the risk network nodes to all network nodes, marks the ratio as the risk node ratio, and calculates the overall network security coefficient SF through a formula;
comparing the integral network security factor SF with a standard security threshold value to generate integral network security state information, wherein the integral network security state information specifically comprises:
if the integral network safety factor SF is greater than or equal to the standard safety threshold, the node analysis module generates an integral network safety signal and sends the integral network safety signal to the output judgment module and the data storage module, and the data storage module stores the integral network safety signal;
if the integral network safety factor SF is smaller than the standard safety threshold, the node analysis module generates an integral network dangerous signal and sends the integral network dangerous signal to the output judging module and the data storage module, and the data storage module stores the integral network dangerous signal;
and the output judging module is connected with the main control module through signals and is used for judging whether the network testing process meets the progress requirement.
5. An internet-based network security test tube control system according to claim 4, wherein: the data acquisition module is also used for acquiring node test information of the network node and sending the node test information to the output judgment module for analysis through the main control module; the node test information comprises node test duration and node test times;
after receiving the overall network security state information sent by the node analysis module, the output judgment module analyzes the overall network test process, and the specific analysis process is as follows:
node test information in the whole network test process is obtained, and a test precision coefficient Ka is obtained through formula calculation;
comparing the test accuracy factor Ka with a standard accuracy threshold:
if the test accuracy coefficient Ka is greater than or equal to the standard accuracy threshold value, outputting an integral network safety signal or an integral network danger signal by an output judging module at the moment;
if the test accuracy coefficient Ka is smaller than the standard accuracy threshold, the output judging module does not output the whole network security state information at the moment, generates a retest signal and sends the retest signal to the main control module, and the main control module retests the whole network security.
6. An internet-based network security test tube control system according to claim 5, wherein: after the output judging module generates a retest signal, when the output judging module receives the whole network security state information again, the whole network security state information is compared with the previous whole network security state information stored in the data storage module:
if the safety state information of the whole network is the same, overlapping the two node testing time lengths, adding one node testing times, substituting the node testing times into a formula again to calculate and obtain a testing precision coefficient Ka, and comparing the testing precision coefficient Ka with a standard precision threshold again to judge the precision of the testing process:
if the test accuracy coefficient Ka is larger than or equal to the standard accuracy threshold value, outputting the overall network security state information, otherwise, continuously re-determining the overall network security until the accuracy of the test process meets the requirement.
7. An internet-based network security test tube control system according to claim 5, wherein: after the output judging module generates a retest signal, when the output judging module receives the whole network security state information again, the whole network security state information is compared with the previous whole network security state information stored in the data storage module:
if the overall network security state information received by the output judging module is changed, setting the node testing duration and the node testing times as data acquired in the latest testing process based on the latest overall network security state information, and judging the accuracy of the testing process again.
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| CN116566688B (en) * | 2023-05-18 | 2023-10-17 | 天云融创数据科技（北京）有限公司 | Network security analysis method and system based on big data |
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