A blockchain-based software development integrated control system

Abstract

The present invention belongs to the technical field of software development. The present invention provides a software development integrated control system based on blockchain, including: obtaining single-point failure data of a centralized identity authentication system in which software development integrated user information is stored in multiple historical operation cycles, and processing and analyzing to obtain a failure risk performance value, judging the operation risk of the centralized identity authentication system, obtaining time data of single-point failures of the centralized identity authentication system in multiple historical operation cycles, and analyzing in combination with the single-point failure data to obtain a single-point failure regular performance value, judging whether there is a regular change in the single-point failure of the centralized identity authentication system, obtaining the single-point failure period in the software development cycle, and comparing it with the current time point of verification, and controlling the verification process of user information in software development integration. The present invention improves the security of software development user information verification and ensures the efficiency of software development.

Description

Technical Field

[0001] The present invention belongs to the technical field of software development, and specifically is a software development integrated control system based on blockchain. Background Art

[0002] With the rapid development of information technology, software development has become an important force in promoting social progress. However, there are many problems in the traditional software development process, such as poor data security and sharing, cumbersome data management, etc. Solving these problems in the software development process is of great significance to promoting software development.

[0003] In the prior art, the management of development data plays an important role in the software development process, such as data sharing, storage, writing, deletion, etc. However, in data security management, the traditional centralized identity authentication system has many disadvantages and cannot guarantee the security of data management. For example, single point failure of the centralized identity authentication system causes data leakage, loss, intrusion and tampering, etc. In addition, when authenticating software development users in the prior art, there is a lack of assessment and control of the verification risk of the centralized identity authentication system, which further increases the risk of data security management and reduces the efficiency of software development.

[0004] To this end, the present invention provides a software development integrated control system based on blockchain. Summary of the invention

[0005] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0006] The technical solution adopted by the present invention to solve the technical problem is: a software development integrated control system based on blockchain, comprising:

[0007] Risk assessment module: obtains single point failure data of the centralized identity authentication system where the software development integrated user information is stored in multiple historical operation cycles, obtains the failure risk performance value based on the processing and analysis of the single point failure data, judges the operation risk of the centralized identity authentication system based on the failure risk performance value, and generates risk signals, wherein the signals include high risk signals and low risk signals;

[0008] comparing the failure risk representation value to a failure risk representation threshold;

[0009] If the fault risk manifestation value is greater than the fault risk manifestation threshold, a high risk signal is generated;

[0010] If the fault risk performance value is less than or equal to the fault risk performance threshold, a low risk signal is generated;

[0011] Fault pattern analysis module: Based on high-risk signals, the time data of single-point failures of the centralized identity authentication system in multiple historical operation cycles is obtained, and the single-point failure regularity performance value is obtained based on the combined analysis of the time data and the single-point failure data. Based on the single-point failure regularity performance value, it is determined whether there is a regular change in the single-point failure of the centralized identity authentication system. If so, a regularity signal is generated;

[0012] The time data of the single point failure includes the time point of the single point failure;

[0013] Verification and evaluation module: Based on regular signals, obtain the single-point failure period in the software development cycle and compare it with the current time point of verification. According to the comparison results, control the verification process of user information in the software development integration and generate control signals, where the control signals include control stop signals and verification continuation signals.

[0014] As a further technical solution of the present invention, the single point failure data includes the number of single point failures and the duration of single point failures.

[0015] Based on the analysis of the number of single-point failures and the duration of single-point failures, the single-point failure frequency performance value and the single-point failure time performance value are obtained respectively;

[0016] The single point failure frequency performance value and the single point failure time performance value are summed to obtain the failure risk performance value.

[0017] As a further technical solution of the present invention, the number of single-point failures of the centralized identity authentication system in all historical operation cycles is summed up and averaged to obtain the average number of single-point failures, the average number of single-point failures is ratioed with the length of the historical operation cycle to obtain the single-point failure frequency, and the single-point failure frequency is ratioed with the single-point failure frequency threshold to obtain the single-point failure frequency performance value.

[0018] As a further technical solution of the present invention, the single-point failure duration of the centralized identity authentication system in all historical operation cycles is summed up to obtain the total single-point failure duration, the total single-point failure duration is ratioed with the number of historical operation cycles to obtain the average single-point failure duration in the historical operation cycle, the average single-point failure duration in the historical operation cycle is ratioed with the historical operation cycle duration to obtain the single-point failure time performance value.

[0019] As a further technical solution of the present invention, the single point fault regularity performance value is obtained by:

[0020] The first law performance value is marked as DY;

[0021] The second rule performance value is marked as DR;

[0022] By formula: The single-point fault law performance value DGZ is obtained, where s1 and s2 are both preset proportional coefficients.

[0023] As a further technical solution of the present invention, the first regularity performance value and the second regularity performance value are obtained by:

[0024] Obtain the number of normal historical operation cycles and the duration of normal historical operation cycles, mark the historical operation cycles that are both the number of normal historical operation cycles and the duration of normal historical operation cycles as overlapping normal historical operation cycles, and number and mark the single point failure time points in each overlapping normal historical operation cycle in chronological order;

[0025] Based on the processing and analysis of the single point failure time points marked with numbers, the time deviation is obtained;

[0026] The obtained time deviation is compared with the time deviation threshold respectively. If the time deviation is less than or equal to the time deviation threshold, the time deviation is marked as a normal time deviation;

[0027] The number of normal time deviations is obtained, and the number of normal time deviations is processed by ratio processing to the number of time deviations to obtain a normal time deviation number ratio, and the normal time deviation number ratio is compared with a normal time deviation number ratio threshold. If the normal time deviation number ratio is greater than the normal time deviation number ratio threshold, the coincident normal historical operation cycle is marked as a comprehensive normal historical operation cycle;

[0028] The number of comprehensive normal historical operation cycles is obtained, and the ratio is processed with the number of historical operation cycles to obtain the first regularity performance value;

[0029] Obtain all interval reference times within the comprehensive normal historical operation cycle and integrate them into interval reference time groups, obtain the variance values ​​of all interval reference time groups and sum and average them to obtain the variance mean, and mark the variance mean as the second rule performance value.

[0030] As a further technical solution of the present invention, the method for obtaining the number of abnormal historical operation cycles is:

[0031] The single point failure times of the centralized identity authentication system in all historical operation cycles are integrated into a single point failure times data group, the mode of the single point failure times data group is obtained, and it is marked as the single point failure reference times, and the single point failure times in the single point failure times data group are compared with the single point failure reference times. If the single point failure times are equal to the single point failure reference times, the historical operation cycle corresponding to the single point failure times is marked as the normal historical operation cycle times; if the single point failure times are not equal to the single point failure reference times, the historical operation cycle corresponding to the single point failure times is marked as the abnormal historical operation cycle times;

[0032] The method for obtaining the historical operation cycle of duration anomalies is the same as the method for obtaining the historical operation cycle of number anomalies.

[0033] As a further technical solution of the present invention, the single point fault regularity performance value DGZ is compared with the single point fault regularity performance threshold;

[0034] If the single-point fault regularity performance value DGZ is greater than the single-point fault regularity performance threshold, a regularity signal is generated;

[0035] If the single point failure regularity performance value DGZ is less than or equal to the single point failure regularity performance threshold, no operation is performed.

[0036] As a further technical solution of the present invention, the method for obtaining the single point failure period in the software development cycle is:

[0037] Get the start and end time points of the software development cycle and mark them on the X-axis. Get the time point of the most recent single point failure of the centralized identity authentication system before the start time point of the software development cycle and mark it on the X-axis as a reference point.

[0038] The interval times in all interval reference time groups are summed and averaged to obtain the interval reference time reference value. The reference point is used as the starting point, and the interval reference time reference value is used as the interval distance. The intervals are marked on the X-axis, and the marked points are marked as the starting points of the single point failure.

[0039] After each single point failure start point, mark the interval on the X-axis with the single point failure reference duration as the interval distance, and mark the marked point as the single point failure end point;

[0040] The period corresponding to the starting point of a single point failure and the end point of the adjacent single point failure is marked as the single point failure period, the period corresponding to the starting time point and the end time point of the software development cycle is marked as the software development period, and the overlapping period between the single point failure period and the software development period is marked as the single point failure period within the software development cycle.

[0041] As a further technical solution of the present invention, when a software development user needs to perform identity authentication, the current time point of the verification is obtained, and the current time point of the verification is compared with the single point failure period in the software development cycle. If the current time point of the verification is within the single point failure period in the software development cycle, a control stop signal is generated; if the current time point of the verification is not within the single point failure period in the software development cycle, a signal to be analyzed is generated;

[0042] Based on the signal to be analyzed, the current time point of verification is marked on the X-axis, and based on the X-axis, the single point fault starting point that is behind the current time point of verification and closest to the current time point of verification is obtained, and the corresponding interval time between the single point fault starting points closest to the current time point of verification is obtained, and it is marked as the verification limit time, and the verification limit time is compared with the verification reference time;

[0043] If the verification limit time is greater than or equal to the verification reference time, a verification continuation signal is generated;

[0044] If the verification limit time is less than the verification reference time, a control stop signal is generated.

[0045] The beneficial effects of the present invention are as follows:

[0046] The single point failure data of the centralized identity authentication system in which the software development integrated user information is stored in multiple historical operation cycles are obtained, and based on the processing and analysis of the single point failure data, the failure risk performance value is obtained to judge the operation risk of the centralized identity authentication system. Based on the high risk signal, the time data of the single point failure of the centralized identity authentication system in multiple historical operation cycles is obtained, and based on the combined analysis of the time data and the single point failure data, the single point failure regularity performance value is obtained to judge whether there is a regular change in the single point failure of the centralized identity authentication system. If so, a regularity signal is generated. Based on the regularity signal, the single point failure period in the software development cycle is obtained, and it is compared with the current time point of the verification. According to the comparison result, the verification process of the user information in the software development integration is controlled, and a control signal is generated, wherein the control signal includes a control stop signal and a verification continuation signal. The present invention analyzes the operation risk of the centralized identity authentication system. In the case of high operation risk, it is analyzed whether there is regularity in the single point failure of the centralized identity authentication system. If so, when verifying the information of the software development user, an advance verification evaluation is performed, and effective control is performed according to the evaluation result, which is conducive to improving the security of the software development user information verification and ensuring the efficiency of software development. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The present invention will be further described below in conjunction with the accompanying drawings.

[0048] Figure 1 is a system module diagram of Embodiment 1 of the present invention;

[0049] Figure 2 It is a system module diagram of embodiment 2 of the present invention. DETAILED DESCRIPTION

[0050] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0051] Example 1

[0052] like Figure 1 As shown, a blockchain-based software development integrated control system according to an embodiment of the present invention includes:

[0053] Risk assessment module: obtains single point failure data of the centralized identity authentication system where the software development integrated user information is stored in multiple historical operation cycles, obtains the failure risk performance value based on the processing and analysis of the single point failure data, judges the operation risk of the centralized identity authentication system based on the failure risk performance value, and generates risk signals, wherein the signals include high risk signals and low risk signals;

[0054] It should be noted that the centralized identity authentication system includes centralized institutions or platforms, including but not limited to financial institutions and Internet companies; the historical operation cycle includes but is not limited to one month, three months and five months; it should also be noted that the term explanation: a single point of failure refers to the failure of a key node or component in the centralized identity authentication system, including but not limited to database failure and server failure;

[0055] Specifically, single point failure data includes the number of single point failures and the duration of single point failures;

[0056] In some embodiments, the number of single point failures of the centralized identity authentication system in all historical operation cycles is summed and averaged to obtain the average number of single point failures, the average number of single point failures is compared with the length of the historical operation cycle to obtain the single point failure frequency, and the single point failure frequency is compared with the single point failure frequency threshold to obtain the single point failure frequency performance value;

[0057] It should be noted that the single point failure frequency threshold is set by technicians in this field based on historical data;

[0058] The single point failure duration of the centralized identity authentication system in all historical operation cycles is summed up to obtain the total single point failure duration, the total single point failure duration is ratioed with the number of historical operation cycles to obtain the average single point failure duration in the historical operation cycle, and the average single point failure duration in the historical operation cycle is ratioed with the duration of the historical operation cycle to obtain the single point failure time performance value;

[0059] The single point failure frequency performance value and the single point failure time performance value are summed to obtain the failure risk performance value;

[0060] In some embodiments, the failure risk representation value is compared to a failure risk representation threshold;

[0061] If the fault risk manifestation value is greater than the fault risk manifestation threshold, a high risk signal is generated;

[0062] If the fault risk performance value is less than or equal to the fault risk performance threshold, a low risk signal is generated;

[0063] Fault pattern analysis module: Based on high-risk signals, the time data of single-point failures of the centralized identity authentication system in multiple historical operation cycles is obtained, and the single-point failure regularity performance value is obtained based on the combined analysis of the time data and the single-point failure data. Based on the single-point failure regularity performance value, it is determined whether there is a regular change in the single-point failure of the centralized identity authentication system. If so, a regularity signal is generated;

[0064] The time data of the single point failure includes the time point of the single point failure;

[0065] It should be noted that the time point of a single point failure indicates the time when the single point failure begins;

[0066] In some embodiments, the number of single point failures of the centralized identity authentication system in all historical operation cycles is integrated into a single point failure number data group, the mode of the single point failure number data group is obtained, and it is marked as a single point failure reference number, and the number of single point failures in the single point failure number data group is compared with the single point failure reference number. If the number of single point failures is equal to the single point failure reference number, the historical operation cycle corresponding to the single point failure number is marked as a normal historical operation cycle; if the number of single point failures is not equal to the single point failure reference number, the historical operation cycle corresponding to the single point failure number is marked as an abnormal historical operation cycle;

[0067] Similarly, the single point failure duration of the centralized identity authentication system in all historical operation cycles is integrated into a single point failure duration data group, the mode of the single point failure duration data group is obtained, and it is marked as the single point failure reference duration, and the single point failure duration in the single point failure duration data group is compared with the single point failure reference duration. If the single point failure duration is equal to the single point failure reference duration, the historical operation cycle corresponding to the single point failure duration is marked as a normal historical operation cycle; if the single point failure duration is not equal to the single point failure reference duration, the historical operation cycle corresponding to the single point failure duration is marked as an abnormal historical operation cycle;

[0068] Mark the historical operation cycle that is both the normal historical operation cycle in terms of number and the normal historical operation cycle in terms of duration as an overlapping normal historical operation cycle;

[0069] Each single point failure time point in the normal historical operation cycle of the overlap is numbered and marked in chronological order, and marked as the first time point, the second time point, and the Nth time point, where N represents the single point failure time point number;

[0070] Obtain the earliest first time point and the latest first time point among all first time points, and take the middle time point therebetween as the first reference time point; obtain the earliest second time point and the latest second time point among all second time points, and take the middle time point therebetween as the second reference time point; similarly, obtain the third reference time point, the fourth reference time point, and so on, the Nth reference time point;

[0071] Perform difference processing on the first time point, the second time point, ... the Nth time point in the overlapping normal historical operation cycle and the corresponding first reference time point, the second reference time point, ... the Nth reference time point, respectively, to obtain a time deviation, wherein the time deviation includes the first time deviation, the second time deviation, ... the Nth time deviation;

[0072] The obtained time deviation is compared with the time deviation threshold. If the time deviation is greater than the time deviation threshold, the time deviation is marked as abnormal time deviation. If the time deviation is less than or equal to the time deviation threshold, the time deviation is marked as normal time deviation.

[0073] Obtain the number of normal time deviations, perform ratio processing on the number of normal time deviations and the number of time deviations to obtain a normal time deviation number ratio, compare the normal time deviation number ratio with a normal time deviation number ratio threshold, if the normal time deviation number ratio is greater than the normal time deviation number ratio threshold, mark the coincident normal historical operation cycle as a comprehensive normal historical operation cycle, if the normal time deviation number ratio is less than or equal to the normal time deviation number ratio threshold, do not perform any operation;

[0074] The number of comprehensive normal historical operation cycles is obtained, and the ratio is processed with the number of historical operation cycles to obtain the first regularity performance value;

[0075] Obtain all interval reference times within the comprehensive normal historical operation cycle and integrate them into an interval reference time group, obtain the variance values ​​of all interval reference time groups and sum and average them to obtain the variance mean, and mark the variance mean as the second regularity performance value;

[0076] It should be noted that the interval reference time is the time difference between adjacent reference time points, and the reference time points include the first reference time point, the second reference time point ... the Nth reference time point;

[0077] The first regularity performance value is marked as DY;

[0078] The second regularity performance value is marked as DR;

[0079] By formula: The single-point fault law performance value DGZ is obtained, where s1 and s2 are both preset proportional coefficients;

[0080] In some embodiments, the single point failure regularity performance value DGZ is compared with a single point failure regularity performance threshold;

[0081] If the single-point fault regularity performance value DGZ is greater than the single-point fault regularity performance threshold, a regularity signal is generated;

[0082] If the single point fault regularity performance value DGZ is less than or equal to the single point fault regularity performance threshold, no operation is performed;

[0083] It should be noted that the regular signal means that: within multiple historical operation cycles, the change of single-point failures has a certain regularity, and the specific number of failures, failure duration and failure time have a certain regularity;

[0084] Verification and evaluation module: Based on regular signals, obtain the single point failure period in the software development cycle, and compare it with the current time point of verification, control the verification process of user information in software development integration according to the comparison results, and generate control signals, where the control signals include control stop signals and verification continuation signals;

[0085] Specifically, the start time point and the end time point of the software development cycle are obtained and marked on the X-axis. The time point of the most recent single point failure of the centralized identity authentication system before the start time point of the software development cycle is obtained and marked on the X-axis as a reference point.

[0086] It should be noted that the software development cycle represents the length of time from the start to the end of software development, which is obtained from the software development contract signed between software development users;

[0087] The interval times in all interval reference time groups are summed and averaged to obtain the interval reference time reference value. The reference point is used as the starting point, and the interval reference time reference value is used as the interval distance. The intervals are marked on the X-axis, and the marked points are marked as the starting points of the single point failure.

[0088] After each single point failure start point, mark the interval on the X-axis with the single point failure reference duration as the interval distance, and mark the marked point as the single point failure end point;

[0089] Mark the period between the start point of a single point failure and the end point of the single point failure adjacent to it as the single point failure period, mark the period between the start time point and the end time point of the software development cycle as the software development period, and mark the overlapping period between the single point failure period and the software development period as the single point failure period within the software development cycle;

[0090] When a software development user needs to authenticate his identity, the current time point of his authentication is obtained, and the current time point of the authentication is compared with the single point failure period in the software development cycle. If the current time point of the authentication is within the single point failure period in the software development cycle, a control stop signal is generated; if the current time point of the authentication is not within the single point failure period in the software development cycle, a signal to be analyzed is generated;

[0091] Based on the signal to be analyzed, the current time point of verification is marked on the X-axis, and based on the X-axis, the single point fault starting point that is behind the current time point of verification and closest to the current time point of verification is obtained, and the corresponding interval time between the single point fault starting points closest to the current time point of verification is obtained, and it is marked as the verification limit time, and the verification limit time is compared with the verification reference time;

[0092] If the verification limit time is greater than or equal to the verification reference time, a verification continuation signal is generated;

[0093] If the verification limit time is less than the verification reference time, a control stop signal is generated;

[0094] It should be noted that the verification reference time refers to the time it takes for the centralized identity authentication system to verify the software development and integration user information. The method for obtaining the verification reference time is as follows: obtain the time it takes for the centralized identity authentication system to verify the software development and integration user information in multiple historical cycles, and select the longest time it takes to verify the software development and integration user information as the verification reference time.

[0095] It should be noted that the verification continuation signal indicates that the centralized identity authentication system is used to verify the software development integration user information until the verification is completed, and the control stop signal indicates that the centralized identity authentication system is stopped to verify the software development integration user information;

[0096] The technical solution of the embodiment of the present invention is: obtaining single-point failure data of a centralized identity authentication system in which software development integrated user information is stored in multiple historical operation cycles, obtaining a failure risk performance value based on processing and analyzing the single-point failure data, judging the operation risk of the centralized identity authentication system, obtaining time data of single-point failures of the centralized identity authentication system in multiple historical operation cycles based on high-risk signals, obtaining a single-point failure regularity performance value based on a combined analysis of the time data and the single-point failure data, judging whether there is a regular change in the single-point failure of the centralized identity authentication system, and if so, generating a regularity signal, obtaining the software The single-point failure period in the software development cycle is compared with the current time point of verification, and the verification process of user information in the software development integration is controlled according to the comparison result, and a control signal is generated, wherein the control signal includes a control stop signal and a verification continuation signal. The present invention analyzes the operation risk of the centralized identity authentication system. When the operation risk is high, it analyzes whether there is regularity in the single-point failure of the centralized identity authentication system. If so, when verifying the information of the software development user, an advance verification evaluation comparison is performed, and effective control is performed according to the evaluation comparison results, which is beneficial to improving the security of software development user information verification and ensuring the efficiency of software development.

[0097] Example 2

[0098] like Figure 2 As shown, based on Example 1, a blockchain-based software development integrated control system described in an embodiment of the present invention further includes:

[0099] Sending module: based on the high risk signal, sends a conversion instruction to the conversion transmission module;

[0100] Conversion and transmission module: receives conversion instructions and transmits the software development integration user information stored in the centralized identity authentication system to the blockchain for backup storage;

[0101] Verification switching module: receives the control stop signal, stops the centralized identity verification system from verifying the software development integrated user information, and sends a verification signal to the blockchain;

[0102] Blockchain: Receive verification signals and verify the user information integrated into software development.

[0103] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A blockchain-based software development integrated control system, characterized by: include: Risk assessment module: obtains single point failure data of the centralized identity authentication system where the software development integrated user information is stored in multiple historical operation cycles, obtains the failure risk performance value based on the processing and analysis of the single point failure data, judges the operation risk of the centralized identity authentication system based on the failure risk performance value, and generates risk signals, wherein the signals include high risk signals and low risk signals; Single point failure data includes the number of single point failures and the duration of single point failures Based on the analysis of the number of single-point failures and the duration of single-point failures, the single-point failure frequency performance value and the single-point failure time performance value are obtained respectively; The single point failure frequency performance value and the single point failure time performance value are summed to obtain the failure risk performance value; comparing the failure risk representation value to a failure risk representation threshold; If the fault risk manifestation value is greater than the fault risk manifestation threshold, a high risk signal is generated; If the fault risk performance value is less than or equal to the fault risk performance threshold, a low risk signal is generated; Fault pattern analysis module: Based on high-risk signals, the time data of single-point failures of the centralized identity authentication system in multiple historical operation cycles is obtained, and the single-point failure regularity performance value is obtained based on the combined analysis of the time data and the single-point failure data. Based on the single-point failure regularity performance value, it is determined whether there is a regular change in the single-point failure of the centralized identity authentication system. If so, a regularity signal is generated; The time data of the single point failure includes the time point of the single point failure; The single point failure regularity performance value is obtained as follows: The first law performance value is marked as DY; The second rule performance value is marked as DR; By formula: The single-point fault law performance value DGZ is obtained, where s1 and s2 are both preset proportional coefficients; Verification and evaluation module: Based on regular signals, obtain the single-point failure period in the software development cycle and compare it with the current time point of verification. According to the comparison results, control the verification process of user information in the software development integration and generate control signals, where the control signals include control stop signals and verification continuation signals.

2. A blockchain-based software development integrated control system according to claim 1, characterized in that: The number of single-point failures of the centralized identity authentication system in all historical operation cycles is summed up and averaged to obtain the mean number of single-point failures. The mean number of single-point failures is ratioed with the length of the historical operation cycle to obtain the single-point failure frequency. The single-point failure frequency is ratioed with the single-point failure frequency threshold to obtain the single-point failure frequency performance value.

3. According to a blockchain-based software development integrated control system according to claim 1, it is characterized by: The single point failure duration of the centralized identity authentication system in all historical operation cycles is summed up to obtain the total single point failure duration. The total single point failure duration is ratioed with the number of historical operation cycles to obtain the average single point failure duration in the historical operation cycle. The average single point failure duration in the historical operation cycle is ratioed with the duration of the historical operation cycle to obtain the single point failure time performance value.

4. According to a blockchain-based software development integrated control system according to claim 1, it is characterized by: The first rule performance value and the second rule performance value are obtained as follows: Obtain the number of normal historical operation cycles and the duration of normal historical operation cycles, mark the historical operation cycles that are both the number of normal historical operation cycles and the duration of normal historical operation cycles as overlapping normal historical operation cycles, and number and mark the single point failure time points in each overlapping normal historical operation cycle in chronological order; Based on the processing and analysis of the single point failure time points marked with numbers, the time deviation is obtained; The obtained time deviation is compared with the time deviation threshold respectively. If the time deviation is less than or equal to the time deviation threshold, the time deviation is marked as a normal time deviation; The number of normal time deviations is obtained, and the number of normal time deviations is processed by ratio processing to the number of time deviations to obtain a normal time deviation number ratio, and the normal time deviation number ratio is compared with a normal time deviation number ratio threshold. If the normal time deviation number ratio is greater than the normal time deviation number ratio threshold, the coincident normal historical operation cycle is marked as a comprehensive normal historical operation cycle; The number of comprehensive normal historical operation cycles is obtained, and the ratio is processed with the number of historical operation cycles to obtain the first regularity performance value; Obtain all interval reference times within the comprehensive normal historical operation cycle and integrate them into interval reference time groups, obtain the variance values ​​of all interval reference time groups and sum and average them to obtain the variance mean, and mark the variance mean as the second rule performance value.

5. According to a blockchain-based software development integrated control system according to claim 1, it is characterized by: The method for obtaining the historical operation cycle of the number of abnormalities is as follows: The single point failure times of the centralized identity authentication system in all historical operation cycles are integrated into a single point failure times data group, the mode of the single point failure times data group is obtained, and it is marked as the single point failure reference times, and the single point failure times in the single point failure times data group are compared with the single point failure reference times. If the single point failure times are equal to the single point failure reference times, the historical operation cycle corresponding to the single point failure times is marked as the normal historical operation cycle times; if the single point failure times are not equal to the single point failure reference times, the historical operation cycle corresponding to the single point failure times is marked as the abnormal historical operation cycle times; The method for obtaining the historical operation cycle of duration anomalies is the same as the method for obtaining the historical operation cycle of number anomalies.

6. A blockchain-based software development integrated control system according to claim 1, characterized in that: Compare the single point fault regularity performance value DGZ with the single point fault regularity performance threshold; If the single-point fault regularity performance value DGZ is greater than the single-point fault regularity performance threshold, a regularity signal is generated; If the single point failure regularity performance value DGZ is less than or equal to the single point failure regularity performance threshold, no operation is performed.

7. A blockchain-based software development integrated control system according to claim 1, characterized in that: The method for obtaining the single point failure period in the software development cycle is as follows: Get the start and end time points of the software development cycle and mark them on the X-axis. Get the time point of the most recent single point failure of the centralized identity authentication system before the start time point of the software development cycle and mark it on the X-axis as a reference point. The interval times in all interval reference time groups are summed and averaged to obtain the interval reference time reference value. The reference point is used as the starting point, and the interval reference time reference value is used as the interval distance. The intervals are marked on the X-axis, and the marked points are marked as the starting points of the single point failure. After each single point failure start point, mark the interval on the X-axis with the single point failure reference duration as the interval distance, and mark the marked point as the single point failure end point; The period corresponding to the starting point of a single point failure and the end point of the adjacent single point failure is marked as the single point failure period, the period corresponding to the starting time point and the end time point of the software development cycle is marked as the software development period, and the overlapping period between the single point failure period and the software development period is marked as the single point failure period within the software development cycle.

8. A blockchain-based software development integrated control system according to claim 7, characterized in that: When a software development user needs to authenticate his identity, the current time point of his authentication is obtained, and the current time point of the authentication is compared with the single point failure period in the software development cycle. If the current time point of the authentication is within the single point failure period in the software development cycle, a control stop signal is generated; if the current time point of the authentication is not within the single point failure period in the software development cycle, a signal to be analyzed is generated; Based on the signal to be analyzed, the current time point of verification is marked on the X-axis, and based on the X-axis, the single point fault starting point that is behind the current time point of verification and closest to the current time point of verification is obtained, and the corresponding interval time between the single point fault starting points closest to the current time point of verification is obtained, and it is marked as the verification limit time, and the verification limit time is compared with the verification reference time; If the verification limit time is greater than or equal to the verification reference time, a verification continuation signal is generated; If the verification limit time is less than the verification reference time, a control stop signal is generated.

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