Data connector evaluation method and device, storage medium and computer program product

Abstract

The embodiment of the invention provides a data connector evaluation method and device, a storage medium and a computer program product. The method comprises the steps of collecting first data of one or more data connectors based on a preset collection strategy; wherein the preset acquisition strategy comprises one or more of a safety dimension, a performance dimension and an expansion dimension of the data connector; for each data connector, determining a first credibility score for the data connector based on the first data, and determining a second credibility score for the data connector; wherein the first credibility score represents the credibility of the data connector, and the second credibility score represents the credibility of the data connector in the transmission link; and dynamically evaluating the data connector based on the first credibility score and the second credibility score, thereby improving the accuracy and comprehensiveness of the evaluation result.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to a data connector evaluation method, device, storage medium and computer program product. BACKGROUND

[0002] In the networking environment where data flow is increasingly frequent, data connectors, as an important component for realizing data interaction between heterogeneous systems, have a key impact on the stability and reliability of the entire data transmission system in terms of performance, security and compatibility. In order to ensure the quality of data transmission, it is necessary to scientifically and reasonably evaluate the data connectors to ensure their stable operation in complex and variable network environments.

[0003] In related technologies, a common method is to evaluate based on static features, such as analyzing the brand, model and other attributes of the connector and setting a scoring standard combined with artificial experience; another method focuses on evaluating a specific dimension (such as transmission speed). In addition, there are centralized management platforms for formulating and implementing evaluation rules, but these solutions usually rely on manual intervention and are difficult to adapt to dynamic changes in actual running states.

[0004] In summary, the above evaluation methods lack consideration of the dynamic behavior of the connectors in actual operation, and fail to comprehensively evaluate the credibility of the connectors themselves and the credibility in the transmission link, resulting in evaluation results that are not comprehensive and accurate, and are difficult to meet the real-time and reliability requirements in the networking environment. SUMMARY

[0005] To solve the above technical problems, the embodiments of the present application provide a data connector evaluation method, device, storage medium and computer program product, which can improve the accuracy and comprehensiveness of the evaluation results.

[0006] The technical solutions of the embodiments of the present application are implemented as follows: In a first aspect, the embodiments of the present application provide a data connector evaluation method, which comprises: acquiring first data of one or more data connectors based on a preset acquisition strategy; wherein the preset acquisition strategy includes one or more of a security dimension, a performance dimension and an extension dimension of the data connector; For each data connector, determining a first credibility score of the data connector based on the first data, and determining a second credibility score of the data connector; wherein the first credibility score represents the credibility of the data connector itself, and the second credibility score represents the credibility of the data connector in the transmission link; dynamically evaluating the data connector based on the first credibility score and the second credibility score.

[0007] In a second aspect, an embodiment of the present application provides a data connector evaluation device, the data connector evaluation device comprising: an acquisition unit, a determination unit, and an evaluation unit; wherein The acquisition unit is configured to acquire first data of one or more data connectors based on a preset acquisition strategy; wherein the preset acquisition strategy comprises one or more of a security dimension, a performance dimension, and an expansion dimension of the data connector; The determination unit is configured to, for each data connector, determine a first trust score of the data connector based on the first data, and determine a second trust score of the data connector; wherein the first trust score represents a trustworthiness of the data connector itself, and the second trust score represents a trustworthiness of the data connector in a transmission link; The evaluation unit is configured to perform dynamic evaluation on the data connector based on the first trust score and the second trust score.

[0008] In a third aspect, an embodiment of the present application provides a data connector evaluation device, the data connector evaluation device comprising: a processor and a memory; wherein The memory is configured to store a computer program capable of running on the processor; The processor is configured to, when running the computer program, execute the data connector evaluation method as described above.

[0009] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, the storage medium storing computer program code, when the computer program code is executed by a computer, the data connector evaluation method as described above is implemented.

[0010] In a fifth aspect, an embodiment of the present application provides a computer program product comprising a computer program, when the computer program is executed by a processor, the data connector evaluation method as described above is implemented.

[0011] The embodiment of the present application provides an evaluation method, device, storage medium and computer program product of a data connector, the method comprises the following steps: collecting first data of one or more data connectors based on a preset collection strategy; wherein the preset collection strategy comprises one or more of a security dimension, a performance dimension and an expansion dimension of the data connector; for each data connector, determining a first credibility score of the data connector based on the first data, and determining a second credibility score of the data connector; wherein the first credibility score represents the credibility of the data connector itself, and the second credibility score represents the credibility of the data connector in the transmission link; and dynamically evaluating the data connector based on the first credibility score and the second credibility score. As can be seen, the embodiment of the present application can first collect the running data of the data connector in the security, performance and expansion dimensions through the preset collection strategy, secondly calculate the self credibility score (i.e. the first credibility score) and the full-link collaborative efficiency score (i.e. the second credibility score), and finally comprehensively evaluate the two. In this way, on the one hand, by introducing a multi-dimensional index system such as the onion model, the performance of the data connector in different dimensions can be comprehensively reflected, and the one-sidedness problem caused by only focusing on a single dimension in the related art is avoided; on the other hand, through the real-time collection and dynamic evaluation mechanism, the evaluation result can be timely responded when the state of the data connector changes, and the timeliness and accuracy of the evaluation result are improved; in addition, combined with the full-link collaborative efficiency score, the evaluation perspective is expanded from a single component to a system link level, so that the role and influence of the data connector in the whole data flow process are more truly reflected, and the accuracy and comprehensiveness of the evaluation result are improved. BRIEF DESCRIPTION OF DRAWINGS

[0012] Figure 1 The evaluation method of the data connector provided by the embodiment of the present application is illustrated Figure One ; Figure 2 The connector evaluation technology architecture provided by the embodiment of the present application is illustrated Figure 3 The evaluation method of the data connector provided by the embodiment of the present application is illustrated Figure Two ; Figure 4 The onion model evaluation system architecture provided by the embodiment of the present application is illustrated Figure 5 The composition structure of the evaluation device of the data connector provided by the embodiment of the present application is illustrated Figure One ; Figure 6 The composition structure of the evaluation device of the data connector provided by the embodiment of the present application is illustrated Figure Two . DETAILED DESCRIPTION

[0013] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. It can be understood that the specific embodiments described herein are only used to explain the related application, and not to limit the application. In addition, it should be noted that, in order to facilitate description, only the parts related to the application are shown in the drawings.

[0014] In the networking environment where data flows frequently, the data connector, as an important component for realizing data interaction between heterogeneous systems, its performance, security and compatibility have a key impact on the stability and reliability of the entire data transmission system. In order to guarantee the quality of data transmission, it is necessary to scientifically and reasonably evaluate the data connector to ensure that it can still run stably in the complex and changeable network environment.

[0015] In the related art, a common method is to evaluate based on static features, such as analyzing the brand, model and other attributes of the connector and setting the scoring standard combined with artificial experience; another method focuses on evaluating a certain specific dimension (such as transmission speed). In addition, there are centralized management platforms for formulating and executing evaluation rules, but these schemes usually rely on manual intervention and are difficult to adapt to the dynamic changes of the actual running state.

[0016] In summary, the above evaluation methods lack consideration of the dynamic behavior of the connector in actual operation, and fail to comprehensively evaluate its own credibility and the credibility in the transmission link, resulting in that the evaluation results are not comprehensive and accurate, and it is difficult to meet the real-time and reliability requirements in the networking environment.

[0017] To solve the problem that the current evaluation method leads to an incomplete and inaccurate evaluation result, the embodiments of the present application provide an evaluation method, device, storage medium and computer program product of a data connector, which comprises: collecting first data of one or more data connectors based on a preset collection strategy; wherein the preset collection strategy comprises one or more of a security dimension, a performance dimension and an expansion dimension of the data connector; for each data connector, determining a first trust score of the data connector based on the first data, and determining a second trust score of the data connector; wherein the first trust score represents the trust of the data connector itself, and the second trust score represents the trust of the data connector in the transmission link; and dynamically evaluating the data connector based on the first trust score and the second trust score. As can be seen, the embodiments of the present application can first collect the running data of the data connector in the security, performance and expansion dimensions through the preset collection strategy, secondly calculate the trust score of itself (i.e. the first trust score) and the full-link collaborative efficiency score (i.e. the second trust score), and finally comprehensively evaluate the two. In this way, on the one hand, by introducing a multi-dimensional index system such as the onion model, the performance of the data connector in different dimensions can be fully reflected, avoiding the one-sidedness problem of the related art which only focuses on a single dimension; on the other hand, through the real-time collection and dynamic evaluation mechanism, the evaluation result can be timely responded when the state of the data connector changes, improving the timeliness and accuracy of the evaluation result; in addition, combined with the full-link collaborative efficiency score, the evaluation perspective is expanded from a single component to the system link level, so that the role and influence of the data connector in the whole data flow process can be more truly reflected, and the accuracy and comprehensiveness of the evaluation result are improved.

[0018] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application.

[0019] The embodiments of the present application provide an evaluation method of a data connector, Figure 1 The evaluation method of the data connector provided in the embodiments of the present application is shown in Figure One As Figure 1 indicated, the evaluation method of the data connector can comprise the following steps: Step 101, collecting first data of one or more data connectors based on a preset collection strategy; wherein the preset collection strategy comprises one or more of a security dimension, a performance dimension and an expansion dimension of the data connector.

[0020] In the embodiments of the present application, the evaluation device of the data connector can collect first data of one or more data connectors based on a preset collection strategy.

[0021] It should be noted that in the embodiments of the present application, the evaluation device of the data connector can be a server or any other device, and the evaluation device can deploy a data security platform (DSP), and the type of the evaluation device is not limited in the present application.

[0022] It should be noted that in the embodiments of the present application, the data connector can refer to a middleware component used to realize data transmission between different data sources in a data networking environment, responsible for data format conversion, protocol adaptation, security verification and other functions, and is a key node in the data flow process.

[0023] It should be noted that in the embodiments of the present application, the first data can be basic operation data for evaluating the trustworthiness of the data connector, covering three dimensions of security, performance and expansion, and the specific collection content can be dynamically adjusted according to the preset collection strategy. For example, in the performance dimension, transmission rate, concurrent connection number, delay time and other indicators can be collected; in the security dimension, encryption algorithm type, key update period, vulnerability scanning result and the like can be collected; in the expansion dimension, protocol adaptation capability, system compatibility and the like can be collected, and the data types and data quantities included in the first data are not limited in the present application.

[0024] It should be noted that in the embodiments of the present application, the preset collection strategy can be automatically adjusted according to different scenarios, for example, in the financial high-frequency trading scenario, the performance dimension has a higher weight, and in the government data sharing scenario, the security dimension has a significantly improved weight. The collection frequency can also be set according to the importance of the indicators, such as collecting key performance indicators every hour, collecting security audit logs every day, and collecting expansion test reports every week. The preset collection strategy ensures the real-time and accuracy of the evaluation data, and the setting of the preset collection strategy is not limited in the present application.

[0025] In step 102, for each data connector, a first trust score of the data connector is determined based on the first data, and a second trust score of the data connector is determined; wherein the first trust score represents the trustworthiness of the data connector itself, and the second trust score represents the trustworthiness of the data connector in the transmission link.

[0026] In the embodiments of the present application, after the evaluation device of the data connector collects the first data of one or more data connectors based on the preset collection strategy, the evaluation device can determine, for each data connector, a first trust score of the data connector based on the first data, and determine a second trust score of the data connector.

[0027] It should be noted that in the embodiments of the present application, the first credibility score can represent a data connector self-score (SelfScore), which can refer to a comprehensive score obtained by quantitatively analyzing the performance of the data connector in terms of security, performance, scalability, etc. The score is used to evaluate the quality and reliability of the data connector itself. SelfScore can usually be calculated in a weighted summation manner, wherein the weights can be dynamically adjusted according to different evaluation scenarios. For example, in a scenario with high security requirements, the weight of the security indicator can be correspondingly increased.

[0028] It should be noted that in the embodiments of the present application, the second credibility score can represent a full-link coordination efficiency score (CoScore), which is an indicator for measuring the coordination capability of the data connector in the entire data flow link. The specific content measured by the indicator includes link delay proportion, data format adaptation rate, fault conduction rate and other performance parameters. For example, if the average delay of the data connector itself is 10 ms, and the total delay of the entire link is 50 ms, the link delay proportion is 20%, and the lower the better. The calculation of CoScore can adopt a weighted product model to avoid the influence of single indicator deviation on the overall judgment.

[0029] It should be noted that in the embodiments of the present application, the full-link coordination efficiency score (CoScore) refers to the score obtained by evaluating the coordination capability of the data connector with other components in the system in the overall environment of the data transmission link. CoScore focuses on the performance of the data connector in the data flow path, such as whether it causes delay increase, whether it affects data format conversion efficiency, etc. CoScore can help identify potential problems of the data connector at the system level and provide basis for optimizing the link structure.

[0030] It should be noted that in the embodiments of the present application, the first data can include one or more first primary indicators corresponding to the security dimension, one or more second primary indicators corresponding to the performance dimension, and one or more third primary indicators corresponding to the expansion dimension. The present application does not specifically limit the types and quantities of data included in the first data.

[0031] It should be noted that in the embodiments of the present application, the expansion dimension can refer to evaluating the adaptability and expansion capability of the data connector between different scenarios, different protocols and different devices. In particular, in the Internet of Data environment, the data connector needs to have good compatibility and adaptability to cope with changing business demands and technical environments.

[0032] It should be noted that in the embodiments of the present application, the security dimension refers to evaluating whether the data connector has basic security capabilities such as data encryption, access control, vulnerability response, etc. The first primary indicators corresponding to the security dimension include but are not limited to data security protection, basic reliability, etc. The first primary indicators are used to measure the defense and recovery capabilities of the data connector when facing potential attacks or abnormal operations. The number and types of indicators included in the first primary indicators are not specifically limited.

[0033] It should be noted that in the embodiments of the present application, the performance dimension can refer to evaluating the efficiency and stability of the data connector in the data transmission process, including transmission rate, concurrent processing capability, delay rate and other key performance indicators. The second primary indicators corresponding to the performance dimension include but are not limited to data transmission performance, fault tolerance and error correction capability, compatibility foundation, etc. The second primary indicators can be used to measure whether the data connector can stably run and maintain high data transmission efficiency under high load and complex network environment. The types and numbers of indicators included in the second primary indicators are not specifically limited.

[0034] It should be noted that in the embodiments of the present application, the expansion dimension can refer to evaluating the adaptability and expansion capability of the data connector between different scenarios, different protocols and different devices. The third primary indicators corresponding to the expansion dimension include but are not limited to dynamic evaluation response, scalability, scenario adaptability, etc. The third primary indicators are used to measure whether the data connector can flexibly adjust the configuration, support multiple protocols and adapt to different sizes of data traffic in actual application. The types and numbers of indicators included in the third primary indicators are not specifically limited.

[0035] Optionally, in the embodiments of the present application, for each data connector, when determining the first trust score of the data connector based on the first data, the first secondary indicators corresponding to each first primary indicator, the second secondary indicators corresponding to each second primary indicator, and the third secondary indicators corresponding to each third primary indicator can be determined. Then, the first trust score can be determined based on each first secondary indicator, each second secondary indicator and each third secondary indicator.

[0036] For example, in the embodiments of the present application, as shown in Table 1 below, assuming that the first primary indicators include data security protection and basic reliability, the first secondary indicators corresponding to the data security protection can include encryption strength, access control granularity, security audit integrity, etc. The first secondary indicators corresponding to the basic reliability can include whether to include valid certificates, identity authentication strength, vulnerability response speed, and fault-free running time, etc. The number and types of indicators included in the first secondary indicators are not specifically limited.

[0037]

[0038] Exemplarily, in the embodiments of the present application, as shown in Table 2 below, it is assumed that the second primary indicators include data transmission performance, fault tolerance and error correction capability, compatibility basis, etc.; the second secondary indicators corresponding to the data transmission performance can include transmission rate, concurrent processing capability, delay rate, etc.; the second secondary indicators corresponding to the fault tolerance and error correction capability can include fault tolerance rate, data consistency guarantee, etc.; the second secondary indicators corresponding to the compatibility basis can include protocol compatibility type, cross-vendor directory query, system / data source adaptation range, and the present application does not make specific limitation on the number and types of indicators included in the second secondary indicators.

[0039]

[0040] Exemplarily, in the embodiments of the present application, as shown in Table 3 below, it is assumed that the third primary indicators include dynamic evaluation response, scalability, scene adaptability, etc.; the third secondary indicators corresponding to the dynamic evaluation response can include real-time monitoring accuracy, abnormal response speed, etc.; the third secondary indicators corresponding to the scalability can include access device growth support, data volume expansion capability, etc.; the third secondary indicators corresponding to the scene adaptability can include parameter adjustment flexibility, customization support degree, etc., and the present application does not make specific limitation on the number and types of indicators included in the third secondary indicators.

[0041]

[0042] It should be noted that in the embodiments of the present application, by dividing the first data into three dimensions of security, performance and expansion, and setting corresponding primary indicators and secondary indicators for each dimension, a multi-dimensional and hierarchical evaluation system is constructed. The evaluation system can comprehensively cover the capabilities of the data connector in different aspects, so as to more accurately reflect the overall credibility of the data connector, and thus can improve the security and stability in the data flow process.

[0043] It should be noted that in the embodiments of the present application, after determining the first secondary indicators corresponding to each first primary indicator, the second secondary indicators corresponding to each second primary indicator, and the third secondary indicators corresponding to each third primary indicator, the evaluation device of the data connector can determine the first credibility score based on each first secondary indicator, each second secondary indicator and each third secondary indicator.

[0044] Optionally, in the embodiments of the present application, when the evaluation device of the data connector determines the first credibility score based on each first secondary indicator, each second secondary indicator and each third secondary indicator, it can determine the first score corresponding to each first secondary indicator, the second score corresponding to each second secondary indicator and the third score corresponding to each third secondary indicator based on the score mapping rule; and then the first pre-set budget processing can be performed on each first score, each second score and each third score to obtain the first credibility score.

[0045] It should be noted that in the embodiments of the present application, the score mapping rule refers to a mapping mechanism for converting the actual performance of the evaluation indicator into a quantitative score according to a pre-set standard. The score mapping rule is usually composed of multiple dimensions, including but not limited to performance, security, scalability, etc., and the present application does not make specific limitations on the score mapping rule.

[0046] It should be noted that in the embodiments of the present application, the first pre-set budget processing refers to that after obtaining the scores of various secondary indicators, the scores can be weighted and summed, and certain correction processing is performed, so as to obtain the final credibility score. The first pre-set budget processing can include historical score calibration, outlier rejection, weight adjustment and other means. For example, when it is detected that the current score of a certain indicator deviates significantly from the historical distribution range of the indicator, quantile mapping method or probability density weighting method can be used to correct the score of the indicator, so as to reduce the influence of extreme cases on the overall evaluation result.

[0047] Exemplarily, in the embodiments of the present application, when the evaluation device of the data connector determines the first score corresponding to each first secondary indicator based on the score mapping rule, it is assumed that the first secondary indicators corresponding to the first primary indicator (such as data security guarantee) include encryption strength, access control granularity and security audit integrity; taking the calculation of the first score corresponding to the encryption strength as an example, as shown in Table 4 below, the quantization dimensions of the encryption strength can include transmission encryption algorithm, storage encryption algorithm and key dynamic update period, and according to the score mapping rule, the scores corresponding to each quantization dimension can be determined, such as 80 points for SM4 block cipher algorithm (SM4) / SM9 identification cipher algorithm (SM9), 60 points for AES-256, etc., the scores corresponding to different quantization dimensions can be determined, then the average value of the score corresponding to the transmission encryption algorithm and the score corresponding to the storage encryption algorithm is alg_score, and the score corresponding to the key dynamic update period is key_score; and then the first score corresponding to the encryption strength can be calculated by the following formula (1), and the first score corresponding to each first secondary indicator, the second score corresponding to each second secondary indicator and the third score corresponding to each third secondary indicator can be calculated in the same way.

[0048] (1) wherein the final score represents the first score, represents the average value of the score corresponding to the transmission encryption algorithm and the score corresponding to the storage encryption algorithm, represents the score of the key dynamic update period, and min represents the minimum function.

[0049]

[0050] Further, in the embodiment of the present application, when the evaluation device of the data connector performs the first preset budget processing on each first score, each second score and each third score to obtain the first credibility score, the evaluation device of the data connector can perform weighted summation on the first score, the second score and the third score to obtain the first credibility score, and the calculation formula can be as shown in the following formula (2).

[0051] (2) wherein the credibility score represents the first credibility score, the index score represents the score corresponding to each secondary index, and the index weight represents the weight corresponding to each secondary index.

[0052] It should be noted that in the embodiment of the present application, the weight of the secondary index can be assigned according to different scenarios, for example, for different scenarios, different weights can be assigned to each primary index, for example, the index weight can be assigned by combining the analytic hierarchy process (AHP) and the entropy weight method; for example, in the financial high-frequency trading scenario, the performance index (i.e., the second primary index) weight is 40%, the security index (i.e., the first primary index) is 35%, and the extensibility index (i.e., the third primary index) is 25%. In the government data sharing scenario, the security index weight is increased to 45%, the performance index is 30%, and the extensibility index is 25%; then the weight of each secondary index corresponding to the weight of each primary index can be distributed, and the weight of each secondary index is not specifically limited in the present application.

[0053] It should be noted that in the embodiment of the present application, for each data connector, the evaluation device of the data connector can determine the first credibility score of the data connector based on the first data, and can also determine the second credibility score of the data connector.

[0054] Optionally, in the embodiments of the present application, when determining the second trust score of the data connector, the evaluation device of the data connector can determine the time delay proportion information corresponding to the data connector based on the first delay information of the data connector and the second delay information of the transmission link, wherein the second delay information is greater than the first delay information; the adaptation rate information of the data connector can also be determined, and the conduction rate information of the data connector can also be determined; wherein the adaptation rate information is used to measure the native adaptation capability of the data connector to the upstream and downstream data formats, and the conduction rate information is used to evaluate the potential impact of the data connector failure on the upstream and downstream data sources; and then the second trust score can be determined based on the time delay proportion information, the adaptation rate information and the conduction rate information.

[0055] It should be noted that, in the embodiments of the present application, the first delay information can refer to the delay time generated when the data connector processes data, such as the time required for data analysis, protocol conversion, format adaptation and the like. The first delay information reflects the processing capability of the data connector to the data stream, and is one of the important indicators for evaluating the performance of the data connector.

[0056] It should be noted that, in the embodiments of the present application, the second delay information refers to the delay of data on the transmission link; wherein the transmission link can include the link of the supplier data source-supplier connector-DSP-requirement connector-requirement data source, and the size of the second delay information is not specifically limited in the present application.

[0057] For example, in the embodiments of the present application, the time delay proportion information corresponding to the data connector is used to measure the delay contribution proportion of the data connector in the entire data transmission link. The calculation method of the time delay proportion information can be: the first delay information of the data connector divided by the total delay (i.e. the second delay information). When the time delay proportion of the data connector is lower, it means that the influence of the data connector in the link is smaller, and the overall synergy efficiency of the system is higher. For example, assuming that the total link delay is 50ms (i.e. the second delay information), the connector delay is 10ms (i.e. the first delay information), and the time delay proportion information is 20%.

[0058] It should be noted that, in the embodiments of the present application, by comparing the first delay information of the data connector with the second delay information of the transmission link and calculating the time delay proportion, it can be judged whether the data connector becomes a bottleneck link in the link, so as to provide a basis for subsequent scoring based on the judgment result.

[0059] It should be noted that in the embodiments of the present application, the adaptation rate information refers to the proportion of the data connector that can support the upstream and downstream data formats without additional conversion. For example, if the upstream data source outputs JSON format and the downstream system receives Parquet format, and the data connector can directly complete the format conversion, the adaptation rate is 100%. The higher the adaptation rate, the better the compatibility of the data connector, thereby reducing additional configuration and resource consumption.

[0060] It should be noted that in the embodiments of the present application, the conductivity information can refer to whether the failure of the data connector will be transmitted to the upstream and downstream components and further cause more extensive system problems when the data connector fails. For example, if the data connector is disconnected, causing the data source buffer to overflow or the target end to block, the conductivity is high. The lower the conductivity, the stronger the fault isolation capability of the data connector, and the higher the fault tolerance of the system.

[0061] Optionally, in the embodiments of the present application, when the evaluation device of the data connector determines the second confidence score based on the time delay ratio information, the adaptation rate information and the conductivity information, it can be calculated by the following formula (3).

[0062] (3) Among them, the second confidence score, , , the weight value, the first delay information, the second delay information, the adaptation rate information of the data connector, the conductivity information of the data connector.

[0063] That is, in the embodiments of the present application, the time delay ratio information is calculated based on the first delay information of the data connector and the second delay information of the transmission link, and the adaptation rate information and the conductivity information are combined to comprehensively obtain the second confidence score, so that the performance and coordination capability of the data connector in the data transmission link can be accurately evaluated. That is, the embodiments of the present application realize multi-dimensional evaluation of the full-link coordination efficiency of the data connector by introducing three dimensions of time delay ratio, adaptation rate and conductivity. Compared with the traditional evaluation method which only focuses on single-point performance, the multi-dimensional scoring mechanism is more scientific and reasonable, and can fully reflect the real performance of the data connector in complex environment.

[0064] Step 103, dynamically evaluating the data connector based on the first confidence score and the second confidence score.

[0065] In the embodiments of the present application, after determining the first trust score of the data connector based on the first data and determining the second trust score of the data connector, the evaluation device of the data connector can perform dynamic evaluation on the data connector based on the first trust score and the second trust score.

[0066] It should be noted that in the embodiments of the present application, when the evaluation device of the data connector performs dynamic evaluation on the data connector based on the first trust score and the second trust score, the evaluation device of the data connector can determine a first comprehensive score of the data connector based on the first trust score, the second trust score, the weight value corresponding to the first trust score, and the weight value corresponding to the second trust score; and then perform dynamic evaluation on the data connector based on the first comprehensive score.

[0067] It should be noted that in the embodiments of the present application, when the evaluation device of the data connector determines the first comprehensive score of the data connector based on the first trust score, the second trust score, the weight value corresponding to the first trust score, and the weight value corresponding to the second trust score, the evaluation device of the data connector can be calculated by the following formula (4).

[0068] (4) Wherein, the first comprehensive score is represented by S1, the first trust score is represented by S1, the weight value corresponding to the first trust score is represented by w1, the weight value corresponding to the second trust score is represented by w2, the second trust score is represented by S2.

[0069] It should be noted that in the embodiments of the present application, the first comprehensive score is the result of weighting and summing the above two trust scores according to their respective weights, which is used to more comprehensively reflect the comprehensive trust level of the data connector. The first comprehensive score can combine the data connector's own ability and the data connector's performance in the system environment, thereby avoiding the deviation caused by evaluating from a single dimension.

[0070] Optionally, in the embodiments of the present application, the evaluation device of the data connector can automatically update the first trust score and the second trust score based on a preset period to obtain an updated first trust score and an updated second trust score, such as collecting and analyzing the first data in real time, and automatically updating the trust scores of each index periodically (such as every 24 hours); then determine a second comprehensive score of the data connector based on the updated first trust score, the updated second trust score, the weight value corresponding to the updated first trust score, and the weight value corresponding to the updated second trust score, and generate a dynamic evaluation report based on the second comprehensive score.

[0071] It should be noted that in the embodiments of the present application, the preset period can be configured according to different application scenarios, for example, every 24 hours, every 72 hours or once a week. By setting a reasonable preset period, it can be ensured that the evaluation result reflects the latest state of the data connector in actual operation, avoiding evaluation distortion due to long time without updating. For example, in the financial high-frequency trading scenario, due to the high requirements for real-time and stability, the preset period can be set to a shorter 24 hours; while in the government non-core data sharing scenario, the preset period can be appropriately extended to 72 hours to balance the relationship between evaluation frequency and resource consumption.

[0072] It should be noted that in the embodiments of the present application, by automatically updating the credibility score of the connector based on the preset period, and combining the weighted calculation to generate the second comprehensive score and the dynamic evaluation report, the continuous monitoring and dynamic management of the credibility of the connector can be realized, and the stability and security of the data flow process in the data networking environment can be improved. Optionally, in the embodiments of the present application, after the evaluation device of the data connector determines the first comprehensive score, the corresponding first strategy can be determined based on the first comprehensive score; wherein the first strategy includes one or more of the first calling interface permission, the first security verification mechanism, the first data interaction restriction, the first resource access permission between the data connector and the management platform; then the connection state, the permission information between the data connector and the management platform can be adjusted and processed based on one or more of the first calling interface permission, the first security verification mechanism, the first data interaction restriction, the first resource access permission.

[0073] It should be noted that in the embodiments of the present application, the management platform can include a DSP platform, and the type of the management platform is not limited in the present application.

[0074] It should be noted that in the embodiments of the present application, the first strategy can be a group of control strategies generated according to the first comprehensive score, used to adjust the interaction mode and permission configuration between the data connector and the management platform, and the type and number of strategies included in the first strategy are not limited in the present application.

[0075] For example, in the embodiments of the present application, the first calling interface permission can refer to the degree of permission of the data connector to call the application programming interface (Application Programming Interface, API) of the management platform. For example, if the credibility of the data connector is high, the calling permission of the data connector to all interfaces can be opened; if the credibility of the data connector is low, only the basic interface can be called by the data connector.

[0076] Exemplarily, in the embodiments of the present application, the first security verification mechanism can refer to a security verification process required to be performed by the data connector when communicating with the management platform, such as identity authentication, digital signature, access token, etc. The data connector with lower credibility can need more frequent or stricter verification.

[0077] Exemplarily, in the embodiments of the present application, the first data interaction restriction can refer to a restriction on the format, frequency, size, etc. of the data uploaded or downloaded by the data connector. For example, the data connector with high credibility can transmit full-amount data in real time, while the data connector with low credibility can only transmit partial data at a time.

[0078] Exemplarily, in the embodiments of the present application, the first resource access permission can refer to whether the data connector can access specific resources in the management platform, such as computing nodes, storage spaces, databases, etc. The data connector with high credibility can be given higher priority in resource allocation.

[0079] Exemplarily, in the embodiments of the present application, when determining the corresponding first strategy based on the first comprehensive score, the evaluation device of the data connector can determine it through Table 5, in which different comprehensive scores correspond to different strategies.

[0080]

[0081] Optionally, in the embodiments of the present application, after determining the corresponding first strategy based on the first comprehensive score, the evaluation device of the data connector can adjust the connection state, permission information, etc. between the data connector and the management platform based on the first strategy. For example, by adjusting the interface permission, security verification mechanism, data interaction restriction, and resource access permission of the data connector, the behavior of the data connector can be effectively controlled, and it is ensured that the operation of the data connector under different credibility levels meets the system security requirements.

[0082] Exemplarily, in the embodiments of the present application, when the first comprehensive score of a certain data connector falls below a certain threshold, the system will automatically reduce the calling interface permission of the data connector, and limit the data connector to only call basic functions; at the same time, the security verification frequency of the data connector is increased, which can prevent potential security vulnerabilities from being exploited. In addition, the data interaction behavior of the data connector can also be restricted, for example, the system can reduce the data transmission frequency or limit the data type, which can reduce the system load and risk.

[0083] It should be noted that in the embodiments of the present application, by adjusting the connection state and permission information between the data connector and the management platform based on the first strategy, the dynamic control of the data connector can be realized. Through the above adjustment processing mode, the change of the credibility of the data connector can be responded in time, the continuity and safety of system operation are guaranteed, and thus the reliability and controllability of data flow in the data network environment can be improved.

[0084] Optionally, in the embodiments of the present application, the evaluation device of the data connector can also determine a corresponding second strategy based on the second comprehensive score; wherein the second strategy includes one or more of a second calling interface permission, a second security verification mechanism, a second data interaction restriction, and a second resource access permission between the data connector and the management platform; and then the connection state and permission information between the data connector and the management platform can be re-adjusted based on one or more of the second calling interface permission, the second security verification mechanism, the second data interaction restriction, and the second resource access permission.

[0085] It should be noted that in the embodiments of the present application, by determining the second strategy based on the second comprehensive score and adjusting the interface permission, the security verification mechanism, the data interaction restriction, and the resource access permission of the data connector accordingly, the dynamic and accurate management of the data connector can be realized. In this way, potential risks can be effectively prevented, and the security of the data flow process is improved, so that the stable operation of the data connector in the data network environment can be guaranteed.

[0086] Optionally, in the embodiments of the present application, the evaluation device of the data connector can send the first strategy or the second strategy to the target data connector, so that the target data connector executes the first strategy or the second strategy; and then the execution result sent by the target data connector can be received.

[0087] It should be noted that in the embodiments of the present application, the target data connector can include a data provider connector and / or a data demander connector, and the number and type of connectors included in the target data connector are not limited in the present application.

[0088] For example, after receiving the first policy or the second policy, the target data connector may perform a parsing operation to understand the content of the policy, and apply the parsed content to the running logic of the target data connector itself. For example, when receiving a policy that enables a strong encryption mechanism, the target data connector may switch to the SM4 algorithm for data transmission, and update the key management period. In actual application, the target data connector usually performs compatibility checking before executing the first policy or the second policy, to confirm whether the first policy or the second policy is feasible under the current version and deployment environment of the target data connector, thereby preventing service interruption caused by policy conflicts.

[0089] It should be noted that, in the embodiments of the present application, by issuing the first policy or the second policy to the target data connector, and receiving the execution result sent by the target data connector, dynamic intervention and closed-loop control of the running state of the target data connector are realized. Through the above implementation, it can be ensured that the target data connector always operates according to the optimal policy, so as to improve the efficiency and security of data flow, and thus enhance the stability and credibility of the entire data networking system.

[0090] The embodiments of the present application provide an evaluation method of a data connector, which comprises: collecting first data of one or more data connectors based on a preset collection policy; wherein the preset collection policy comprises one or more of a security dimension, a performance dimension and an expansion dimension of the data connector; for each data connector, determining a first trust score of the data connector based on the first data, and determining a second trust score of the data connector; wherein the first trust score represents the trust of the data connector itself, and the second trust score represents the trust of the data connector in the transmission link; and dynamically evaluating the data connector based on the first trust score and the second trust score. As can be seen, the embodiments of the present application can first collect the running data of the data connector in the security, performance and expansion dimensions through the preset collection policy, secondly calculate the self-trust score (i.e. the first trust score) and the full-link cooperation efficiency score (i.e. the second trust score), and finally comprehensively evaluate them. In this way, on the one hand, by introducing a multi-dimensional index system such as the onion model, the performance of the data connector in different dimensions can be fully reflected, avoiding the one-sidedness problem of evaluation caused by only focusing on a single dimension in related technologies; on the other hand, through the real-time collection and dynamic evaluation mechanism, the evaluation result can be timely responded when the state of the data connector changes, improving the timeliness and accuracy of the evaluation result; in addition, combined with the full-link cooperation efficiency score, the evaluation perspective is expanded from a single component to the system link level, so that the role and influence of the data connector in the entire data flow process can be more truly reflected, and the accuracy and comprehensiveness of the evaluation result are improved.

[0091] Based on the above embodiments, another embodiment of the present application provides an evaluation method of a data connector, which can construct a multi-level evaluation index system, adopt an onion model to construct a multi-dimensional evaluation index system of the data connector, comprehensively evaluate the performance, security and scalability of the connector from three dimensions of the core layer, the middle layer and the outer layer, and simultaneously introduce the cooperative efficiency evaluation of the connector in the whole link; meanwhile, by introducing real-time data acquisition and dynamic evaluation method, the state of the data connector in the actual running process can be comprehensively and real-timely evaluated, and problems can be found and responded in time; and the strategy elastic iterative adjustment is supported, according to the connector trust evaluation result, the system can automatically and elastically iteratively adjust the configuration and strategy of the connector, optimize the performance and security thereof, and improve the overall stability of the system.

[0092] It should be noted that in the embodiments of the present application, the evaluation method of the data connector can be implemented based on part of the modules of different network elements of a data flow sharing service network (Data Switching Service Network, DSSN), Figure 2 The connector evaluation technical architecture diagram proposed for the embodiments of the present application is shown in Figure 2 As shown, it mainly involves the data acquisition, index analysis, strategy management, abnormality monitoring modules of the DSP, the data transmission, strategy verification, data processing and log uploading modules of the data provider connector, the data reception, strategy verification, data use and log uploading modules of the data demander connector, etc. It should be noted that in the embodiments of the present application, Figure 3 The evaluation method of the data connector proposed for the embodiments of the present application is shown in Figure Two As shown in Figure 3 The connector trust evaluation process can include the following steps: step 201, first, a hierarchical index system for dynamic evaluation of the data connector can be constructed in combination with the onion model, and the evaluation indexes are divided into the core layer, the middle layer and the outer layer from inside to outside; step 202, real-time data acquisition and comprehensive calculation are performed on the state of the data connector in the data flow process by using the dynamic evaluation method, and the connector self-trust score (i.e. the first trust score) and the whole-link cooperative efficiency score (i.e. the second trust score) are obtained respectively; step 203, the comprehensive trust degree and the running state evaluation result are finally obtained; step 204, the elastic iterative update of the connection strategy is performed according to the evaluation result; step 205, the result evaluation and feedback.

[0093] It should be noted that in the embodiments of the present application, the evaluation equipment of the data connector can scan the networking nodes automatically, identify all the data connectors participating in the data flow, then save the connector basic information (such as the R&D manufacturer, the deployment environment, the version number, the adaptation scene, etc.) into the database, and allocate a unique identifier to each connector to establish a standardized management library.

[0094] It should be noted that in the embodiments of the present application, the evaluation device of the data connector can combine the onion model to construct an index framework from the three core dimensions of security, performance and scalability, refine sub-indices, and define measurable standards for each index, while presetting the index weights of different scenarios; Specifically as follows: (1) Constructing a hierarchical index system based on the onion model The onion model reflects the different levels of things from the inside out, Figure 4 The onion model evaluation system structure diagram proposed for the embodiments of the present application is shown in Figure 4 As shown, the evaluation indexes of the data connector can be divided into the core security layer, the intermediate performance layer and the external expansion layer; wherein the core security layer focuses on the fundamental guarantee of the connector "whether it can be trusted", focuses on security and reliability, is the basis for guaranteeing that the data flow does not occur fundamental risks and dynamic judgment, and the specific indexes are shown in Table 1 above; the intermediate performance layer focuses on the core efficiency of the connector "how to realize the trusted function", focuses on performance and compatibility, measures whether it can efficiently and accurately complete the data flow task under normal scenarios, which is the core of dynamic judgment, and the specific indexes are shown in Table 2 above; the external expansion layer focuses on the adaptability of the connector "whether it can be trusted in dynamic scenarios", focuses on dynamic adaptability and scenario adaptability, measures whether it can continuously maintain a trusted state in a complex and changing data networking environment, which is an extension of dynamic judgment, and the specific indexes are shown in Table 3 above; (2) Different weights are given to each first-level index according to different scenarios, such as using the method of combining the analytic hierarchy process (AHP) and the entropy weight method to assign index weights; For example: in the financial high-frequency trading scenario, the performance index weight is 40%, the security index is 35%, and the scalability index is 25%. In the government data sharing scenario, the security index weight is increased to 45%, the performance index is 30%, and the scalability index is 25%.

[0095] It should be noted that in the embodiments of the present application, after the connector connects the DSP platform, the evaluation device of the data connector can collect the data (i.e. the first data) required for each index evaluation by using an automatic interface and collecting according to a preset strategy; the following data can be collected: (1) Performance data: real-time collection (such as every hour) of transmission rate, concurrent connection number, delay time, etc.; (2) Security data: daily collection of security audit logs (such as abnormal access records, encryption failure times), vulnerability scanning results; (3) Scalability data: weekly collection of protocol adaptation test reports (such as support situation of newly added protocols), cross-system interaction error logs.

[0096] It should be noted that in the embodiments of the present application, each quantitative index defined above is scored in percentage, and the score of each index (i.e., the secondary index) of the connector is calculated according to the "quantitative dimension + judgment rule + score mapping formula", and then the current index score is corrected by using the historical score model in the same scene to avoid statistical deviation caused by extreme cases. Taking the encryption strength index as an example, the calculation rule is shown in Table 4 above.

[0097] Further, in the embodiments of the present application, the evaluation device of the data connector can calculate a comprehensive trust score, which can first calculate the trust score of the connector (i.e., the first trust score) according to the index weight by weighted summation, as shown in the above formula (2), and can also calculate the full-link trust score CoScore of the connector (i.e., the second trust score), and define the "coordination feature index" in the full-link "supplier data source-supplier connector-DSP data delivery platform-recipient connector-recipient data source", as follows: link delay proportion (i.e., delay proportion information): connector delay / full-link total delay (e.g., full-link delay 50ms, connector delay 10ms, then the proportion is 20%, the lower the proportion, the better the coordination); data format adaptation rate (i.e., adaptation rate information): the proportion of the connector that does not need additional conversion to adapt to the upstream and downstream data formats (e.g., data source outputs JSON, target receives Parquet, and the connector directly supports, then the adaptation rate is 100%); fault conduction rate (conduction rate information): the probability of failure of upstream and downstream components (e.g., data source interruption, target congestion) caused by connector failure (e.g., after the connector is disconnected, the data source buffer overflow probability is <5%, then the conduction rate is low), and then the second trust score can be calculated by the above formula (3); finally, the full-link coordination efficiency score of the connector (i.e., the second trust score) is weighted (e.g., the coordination score proportion is 20%) with the connector's own trust index score (i.e., the first trust score) to obtain the final trust score of the connector (i.e., the first comprehensive score).

[0098] It should be noted that in the embodiments of the present application, the first comprehensive score is obtained by weighting and summing the above two trust scores according to their respective weights, which is used to more comprehensively reflect the comprehensive trust level of the data connector. The first comprehensive score can combine the data connector's own ability and the data connector's performance in the system environment, thereby avoiding the deviation caused by evaluating from a single dimension.

[0099] It should be noted that in the embodiments of the present application, the dynamic evaluation and connection strategy elasticity iteration can include the following: dynamic update evaluation: real-time data collection and analysis, automatic update of each index score and comprehensive score at regular intervals (such as every 24 hours), and generation of a dynamic evaluation report; strategy elasticity iteration adjustment: according to the comprehensive trust score of the connector, dynamically update its connection strategy (i.e. the first strategy) with the DSP data flow exchange platform.

[0100] It should be noted that in the embodiments of the present application, according to the real-time data connector trust score (excellent trust ≥ 90 points, good trust 80-89 points, qualified trust 70-79 points, untrustworthy < 70 points), different connection strategies can be issued for different risk levels. The strategy is used to control the connection state between the connector and the DSP, and between the supply and demand connectors. The specific strategy is shown in Table 5 above.

[0101] It should be noted that in the embodiments of the present application, the closed-loop execution process of strategy adjustment can include the following: (1) score triggering: the "index analysis module" of the DSP updates the connector trust score daily, and if the score changes across levels (such as from 82 to 68), it automatically triggers a "strategy adjustment event"; (2) strategy generation: the "strategy management module" of the DSP generates specific adjustment instructions (such as "disconnect all links with supply and demand connectors") according to the score level by calling the preset strategy template (such as untrustworthy → block connection); (3) strategy delivery: push the instructions to the "local strategy execution module" of the target connector through the "evaluation strategy delivery channel"; (4) execution feedback: after the supply and demand connectors execute the strategy, synchronize the execution results (such as "connection has been disconnected, configuration has been cleaned up") to the DSP through the "state feedback module".

[0102] It should be noted that in the embodiments of the present application, the evaluation equipment of the data connector can also generate a visual report of the connector trust score (such as including single index score, comprehensive ranking, strengths / weaknesses analysis, etc.), and support PDF, Excel format export. At the same time, it can also provide users with connector selection suggestions (such as "in the financial scenario, recommend connectors with comprehensive score ≥ 90 points and delay rate ≤ 10 ms").

[0103] It should be noted that in the embodiments of the present application, a complete connector dynamic signal judgment system based on data flow of the Internet of Things is also proposed, which can include an evaluation object management module, an evaluation index system construction and management module, a data acquisition module, a data processing and analysis module, a dynamic evaluation and abnormal processing module, and an evaluation result application and feedback module; wherein 1. the evaluation object management module can be used to define the evaluation range, support the entry of basic information of data connectors of different types, brands and versions, and establish a unique identification library; 2. the evaluation index system construction and management module is mainly used for the construction of evaluation indexes, and an index system is constructed from three core dimensions of performance, security and compatibility by using an onion model, and each index is configured with a quantifiable standard, such as “fault tolerance rate” defined as the number of error automatic recovery times in 1000 consecutive data transmissions; “encryption strength” is graded according to the compliance of the national encryption algorithm and the dynamic update frequency of the key; 3. the data acquisition module can be connected to the DSP platform through an automatic interface, and real-time acquisition of connector performance running data (such as hourly transmission rate, concurrent connection number), security log (such as daily audit record), compatibility test result (such as weekly adaptation detection), and storage of data; 4. the data processing and analysis module mainly calculates the connector full-link cooperation efficiency score and the connector itself trust score according to each index and mapping rule, so as to finally obtain the comprehensive trust score and risk level of the connector; 5. the dynamic evaluation and abnormal processing module mainly performs real-time analysis of data, and updates the comprehensive trust score and risk level of each connector regularly (such as every 24 hours); it also supports preset index threshold (such as 50% transmission delay surge), triggers abnormal early warning to start a hierarchical processing mechanism (such as automatic retry for slight abnormality, block connection and notify operation and maintenance for serious abnormality), adjusts the connection strategy between the connector and the DSP data flow utilization platform through elastic iteration; 6. the evaluation result application and feedback module is mainly used to output the evaluation report of the connector, provide the connector selection suggestion for the user, and feedback the optimization direction (such as pushing improvement scheme for low-score index) to the R&D party.

[0104] The embodiment of the present application provides an evaluation method of a data connector, which comprises the following steps: collecting first data of one or more data connectors based on a preset collection strategy; wherein the preset collection strategy comprises one or more of a security dimension, a performance dimension and an expansion dimension of the data connector; determining, for each data connector, a first credibility score of the data connector based on the first data, and determining a second credibility score of the data connector; wherein the first credibility score represents the credibility of the data connector itself, and the second credibility score represents the credibility of the data connector in a transmission link; and dynamically evaluating the data connector based on the first credibility score and the second credibility score. As can be seen, the embodiment of the present application can first collect the running data of the data connector in the security, performance and expansion dimensions through the preset collection strategy, secondly calculate the self credibility score (i.e. the first credibility score) and the full-link collaborative efficiency score (i.e. the second credibility score), and finally comprehensively evaluate the two. In this way, on the one hand, by introducing a multi-dimensional index system such as an onion model, the performance of the data connector in different dimensions can be comprehensively reflected, and the one-sidedness problem caused by only focusing on a single dimension in the related art is avoided; on the other hand, by means of the real-time collection and dynamic evaluation mechanism, the evaluation result can be timely responded when the state of the data connector changes, and the timeliness and accuracy of the evaluation result are improved; in addition, in combination with the full-link collaborative efficiency score, the evaluation perspective is expanded from a single component to a system link level, so that the role and influence of the data connector in the whole data flow process are more truly reflected, and the accuracy and comprehensiveness of the evaluation result are improved.

[0105] Based on the above embodiment, the embodiment of the present application provides an evaluation device of a data connector, Figure 5 The composition structure of the evaluation device of the data connector is shown in the figure Figure One As shown in the figure Figure 5 The device 10 comprises a collection unit 11, a determination unit 12 and an evaluation unit 13; wherein The collection unit 11 is configured to collect first data of one or more data connectors based on a preset collection strategy; wherein the preset collection strategy comprises one or more of a security dimension, a performance dimension and an expansion dimension of the data connector; The determination unit 12 is configured to determine, for each data connector, a first credibility score of the data connector based on the first data, and determine a second credibility score of the data connector; wherein the first credibility score represents the credibility of the data connector itself, and the second credibility score represents the credibility of the data connector in a transmission link; The evaluation unit 13 is configured to dynamically evaluate the data connector based on the first credibility score and the second credibility score.

[0106] In the embodiments of the present application, further, Figure 6 The schematic structure of the evaluation device for the data connector Figure Two As Figure 6 As shown in the figure, the evaluation device 10 for the data connector provided by the embodiments of the present application can further include a processor 14, a memory 15 storing executable instructions of the processor 14, further, the device 10 can further include a communication interface 16, and a bus 17 for connecting the processor 14, the memory 15 and the communication interface 16.

[0107] In the embodiments of the present application, the processor 14 can be at least one of an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a ProgRAMmable Logic Device (PLD), a Field ProgRAMmable Gate Array (FPGA), a Central Processing Unit (CPU), a controller, a microcontroller, and a microprocessor. It can be understood that for different devices, the electronic device for realizing the function of the processor can also be other, and the embodiments of the present application are not limited specifically. The device 10 can further include a memory 15, which can be connected with the processor 14, wherein the memory 15 is used to store executable program codes, the program codes include computer operation instructions, the memory 15 can include a high-speed RAM memory, and can also include a non-volatile memory, for example, at least two disk memories.

[0108] In the embodiments of the present application, the bus 17 is used to connect the communication interface 16, the processor 14 and the memory 15 and the mutual communication among these devices.

[0109] In the embodiments of the present application, the memory 15 is used to store instructions and data.

[0110] Further, in the embodiments of the present application, the processor 14 is configured to collect first data of one or more data connectors based on a preset collection strategy, wherein the preset collection strategy comprises one or more of a security dimension, a performance dimension, and an expansion dimension of the data connectors; for each data connector, determine a first trustworthiness score of the data connector based on the first data, and determine a second trustworthiness score of the data connector; wherein the first trustworthiness score represents a trustworthiness of the data connector itself, and the second trustworthiness score represents a trustworthiness of the data connector in a transmission link; and perform dynamic evaluation on the data connector based on the first trustworthiness score and the second trustworthiness score.

[0111] In practical applications, the memory 15 can be a volatile memory, such as a Random-Access Memory (RAM), or a non-volatile memory, such as a Read-Only Memory (ROM), a flash memory, a Hard Disk Drive (HDD), or a Solid-State Drive (SSD), or a combination of the above types of memories, and provides instructions and data to the processor 14.

[0112] The embodiment of the present application provides an evaluation device of a data connector, which collects first data of one or more data connectors based on a preset collection strategy; wherein the preset collection strategy comprises one or more of a security dimension, a performance dimension and an expansion dimension of the data connector; for each data connector, a first credibility score of the data connector is determined based on the first data, and a second credibility score of the data connector is determined; wherein the first credibility score represents the credibility of the data connector itself, and the second credibility score represents the credibility of the data connector in a transmission link; and the data connector is dynamically evaluated based on the first credibility score and the second credibility score. As can be seen, the embodiment of the present application can first collect the running data of the data connector in the security, performance and expansion dimensions through the preset collection strategy, secondly calculate the self credibility score (i.e. the first credibility score) and the full-link collaborative efficiency score (i.e. the second credibility score), and finally comprehensively evaluate the two. In this way, on the one hand, by introducing a multi-dimensional index system such as an onion model, the performance of the data connector in different dimensions can be comprehensively reflected, and the one-sidedness problem of the evaluation caused by only focusing on a single dimension in the related art is avoided; on the other hand, through the real-time collection and dynamic evaluation mechanism, the evaluation result can be timely responded when the state of the data connector changes, and the timeliness and accuracy of the evaluation result are improved; in addition, combined with the full-link collaborative efficiency score, the evaluation perspective is expanded from a single component to a system link level, so that the role and influence of the data connector in the whole data flow process are more truly reflected, and the accuracy and comprehensiveness of the evaluation result are improved.

[0113] The embodiment of the present application provides a computer readable storage medium, which stores a program, and the program is executed by a processor to realize the evaluation method of the data connector.

[0114] Specifically, the program instructions corresponding to the evaluation method of the data connector in the embodiment can be stored on a storage medium such as an optical disc, a hard disk, a U disk, etc., and when the program instructions corresponding to the evaluation method of the data connector in the storage medium are read or executed by an electronic device, the following steps are included: collecting first data of one or more data connectors based on a preset collection strategy; wherein the preset collection strategy comprises one or more of a security dimension, a performance dimension and an expansion dimension of the data connector; for each data connector, determining a first credibility score of the data connector based on the first data, and determining a second credibility score of the data connector; wherein the first credibility score represents the credibility of the data connector itself, and the second credibility score represents the credibility of the data connector in a transmission link; dynamically assess the data connector based on the first trust score and the second trust score.

[0115] The embodiments of the present application also provide a computer program product, comprising a computer program, which can be executed by the processor 14 of the assessment device 10 of the data connector to complete the steps of any of the foregoing methods.

[0116] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage, etc.) containing computer-usable program code.

[0117] The present application is described with reference to the implementation flowcharts and / or block diagrams of the method, device (system), and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams and the combination of the flows and / or blocks can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus generate a means for implementing the functions specified in the flowcharts and / or block diagrams. Figure One one or more flows and / or blocks Figure One an apparatus that performs the functions specified in the flowcharts and / or block diagrams.

[0118] These computer program instructions can also be stored in a computer-readable memory that can direct the computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including instruction apparatus, which implements the functions specified in the flowcharts and / or block diagrams. Figure One one or more flows and / or blocks Figure One an apparatus that performs the functions specified in the flowcharts and / or block diagrams.

[0119] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are performed on the computer or other programmable data processing apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable data processing apparatus provide steps for implementing the functions specified in the flowcharts and / or block diagrams. Figure One one or more flows and / or blocks Figure One Figure One an apparatus that performs the functions specified in the flowcharts and / or block diagrams.

[0120] The above descriptions are merely some example embodiments of the present application, not intended to limit the protective scope of the present application.

Claims

1. A method for evaluating a data connector, characterized in that, The method includes: First data from one or more data connectors is collected based on a preset collection strategy; wherein, the preset collection strategy includes one or more of the security dimension, performance dimension, and expansion dimension of the data connector; For each data connector, a first reliability score is determined based on the first data, and a second reliability score is determined for the data connector; wherein, the first reliability score characterizes the reliability of the data connector itself, and the second reliability score characterizes the reliability of the data connector in the transmission link; The data connector is dynamically evaluated based on the first credibility score and the second credibility score.

2. The method according to claim 1, characterized in that, The first data includes one or more first-level indicators corresponding to the security dimension, one or more second-level indicators corresponding to the performance dimension, and one or more third-level indicators corresponding to the extended dimension. The extended dimension is at least used to measure the trust status of the data connector in a dynamic network environment. The step of determining a first credibility score for each data connector based on the first data includes: Determine the first secondary indicator corresponding to each first primary indicator, the second secondary indicator corresponding to each second primary indicator, and the third secondary indicator corresponding to each third primary indicator; The first credibility score is determined based on each of the first secondary indicator, each of the second secondary indicator, and each of the third secondary indicator.

3. The method according to claim 2, characterized in that, The determination of the first credibility score based on each of the first secondary indicator, each of the second secondary indicator, and each of the third secondary indicator includes: Based on the score mapping rule, determine the first score corresponding to each of the first secondary indicators, the second score corresponding to each of the second secondary indicators, and the third score corresponding to each of the third secondary indicators; A first preset budget processing is performed on each of the first score, each of the second score, and each of the third scores to obtain the first credibility score.

4. The method according to claim 1, characterized in that, The determination of the second credibility score of the data connector includes: The latency ratio information corresponding to the data connector is determined based on the first latency information of the data connector and the second latency information of the transmission link; wherein, the second latency information is greater than the first latency information; The adaptation rate information of the data connector is determined, and the transmission rate information of the data connector is determined; wherein, the adaptation rate information is used to measure the native adaptation capability of the data connector to upstream and downstream data formats, and the transmission rate information is used to assess the potential impact of the data connector failure on upstream and downstream data sources. The second credibility score is determined based on the latency ratio information, the adaptation rate information, and the conduction rate information.

5. The method according to claim 1, characterized in that, The dynamic evaluation of the data connector based on the first credibility score and the second credibility score includes: The first comprehensive score of the data connector is determined based on the first credibility score, the second credibility score, the weight value corresponding to the first credibility score, and the weight value corresponding to the second credibility score. The data connector is dynamically evaluated based on the first comprehensive score.

6. The method according to claim 1, characterized in that, The method further includes: The first credibility score and the second credibility score are automatically updated based on a preset period to obtain the updated first credibility score and the updated second credibility score. The second comprehensive score of the data connector is determined based on the updated first credibility score, the updated second credibility score, the weight value corresponding to the updated first credibility score, and the weight value corresponding to the updated second credibility score, and a dynamic evaluation report is generated based on the second comprehensive score.

7. The method according to claim 5, characterized in that, The method further includes: A first strategy is determined based on the first comprehensive score; wherein, the first strategy includes one or more of the following: first call interface permission between the data connector and the management platform, first security verification mechanism, first data interaction restriction, and first resource access permission. The connection status and permission information between the data connector and the management platform are adjusted based on one or more of the first call interface permission, the first security verification mechanism, the first data interaction restriction, and the first resource access permission.

8. The method according to claim 6, characterized in that, The method further includes: The second strategy is determined based on the second comprehensive score; wherein, the second strategy includes one or more of the following: second call interface permissions between the data connector and the management platform, second security verification mechanism, second data interaction restrictions, and second resource access permissions; Based on one or more of the second call interface permissions, the second security verification mechanism, the second data interaction restrictions, and the second resource access permissions, the connection status and permission information between the data connector and the management platform are readjusted.

9. The method according to claim 7 or 8, characterized in that, The method further includes: Send a first strategy or a second strategy to the target data connector so that the target data connector executes the first strategy or the second strategy; Receive the execution result sent by the target data connector.

10. An evaluation device for a data connector, characterized in that, The evaluation device for the data connector includes: an acquisition unit, a determination unit, and an evaluation unit; wherein, The acquisition unit is used to acquire first data from one or more data connectors based on a preset acquisition strategy; wherein the preset acquisition strategy includes one or more of the security dimension, performance dimension, and expansion dimension of the data connector; The determining unit is configured to, for each data connector, determine a first reliability score of the data connector based on the first data, and determine a second reliability score of the data connector; wherein, the first reliability score characterizes the reliability of the data connector itself, and the second reliability score characterizes the reliability of the data connector in the transmission link; The evaluation unit is used to dynamically evaluate the data connector based on the first confidence score and the second confidence score.

11. An evaluation device for a data connector, characterized in that, The evaluation device for the connector includes: a processor and a memory; wherein, The memory is used to store computer programs that can run on the processor; The processor is configured to perform the method as described in any one of claims 1-9 when running the computer program.

12. A computer-readable storage medium, characterized in that, The storage medium stores computer program code, which, when executed by a computer, performs the method described in any one of claims 1-9.

13. A computer program product, comprising a computer program, characterized in that, The computer program, when executed by a processor, implements the method according to any one of claims 1-9.

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