Cloud computing-based password service unified management system and method, and storage medium

Abstract

The invention discloses a password service unified management system and method based on cloud computing and a storage medium, and relates to the technical field of password management, if the preset information sensitivity level of an application system currently logged in by a user on a government affair platform is not the highest level, a first login state coefficient of the user in the application system currently logged in is acquired; when the user is switched to the application system with the preset information sensitivity level higher than that of the currently logged-in application system, latest login verification password information is determined, and the latest login verification password information is sent to the user for login verification; and obtaining a second login state coefficient in the login verification process of the user according to the latest login verification password information, and judging whether the user needs to input a password again for login or not when the user logs in next time, so that the risks that the government affair platform is attacked and data is leaked can be reduced, the user operation is convenient, and the user experience is improved. And the influence of user working efficiency is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of password management, and in particular to a unified management system, method and storage medium for password services based on cloud computing. Background Art

[0002] Cloud computing is a technology that provides computing resources and services through the Internet. Users can obtain remote computing power, storage, network, and application resources on demand without having to own local hardware and infrastructure.

[0003] The unified password service management system based on cloud computing is a technology that combines the management of login passwords for service platforms with cloud computing. Especially in the field of government affairs, there are a large number of users. Relying on the powerful cloud computing capabilities, the passwords of each user logging into the government affairs platform are managed to achieve efficient management.

[0004] In order to facilitate user login, when a general user logs into an application system in the government affairs platform, the current login information will be automatically saved, and the user will be granted access to all authorized application systems on the platform. That is, after a user logs into an application system, he does not need to log in again when switching to other application systems. The realization of "one-stop login, full domain access" simplifies user operations and ensures the consistency of the identity of the same user in different application systems.

[0005] However, in the actual login process, the application system that the user logs in first may not correspond to the highest information sensitivity level. If it is blindly assumed that users can access all application systems on the government platform, it may increase the risk of attacks and data leakage on the government platform. Moreover, if a password is required every time the user logs in to the government platform, it may cause inconvenience to the user and affect the user's work efficiency. Summary of the invention

[0006] The purpose of the present invention is to solve the above-mentioned problems and provide a unified management system, method and storage medium for cryptographic services based on cloud computing.

[0007] In a first aspect of the present invention, a unified management method for cryptographic services based on cloud computing is first proposed, the method comprising:

[0008] Obtain the preset information sensitivity level of the application system currently logged in by the user on the government affairs platform, and determine whether the preset information sensitivity level of the application system currently logged in is the highest level;

[0009] If the preset information sensitivity level of the currently logged-in application system is not the highest level, the user's login status data in the currently logged-in application system is obtained, and a first login status coefficient is obtained according to the login status data; the login status data includes a login time deviation coefficient, a login behavior abnormality coefficient, a login network instability coefficient, and a current application system access coefficient;

[0010] When the user switches to an application system with a higher information sensitivity level than the currently logged-in application system, the latest login verification password information is obtained according to the first login state coefficient and the preset login verification password information, and the latest login verification password information is sent to the user for verification login;

[0011] The login status data of the user during the login verification process according to the latest login verification password information is obtained to obtain a second login status coefficient, and combined with a preset login status coefficient threshold, it is determined whether the user needs to enter the password again to log in the next time.

[0012] Optionally, the login behavior abnormality coefficient includes:

[0013] The total number of times the user incorrectly enters the password and the duration of each incorrect password entry are obtained during the process of the user logging into the current application system on the government affairs platform, and the sequence is performed based on time to obtain the sequence of duration of incorrect password entry; and the mean of the sequence of duration of incorrect password entry is calculated as the input time error coefficient;

[0014] Obtain the total number of times the user enters the password, and calculate the time interval between two adjacent password inputs to obtain a password input time interval sequence, calculate the mean of the password input time interval sequence, and divide the mean by the preset input interval to obtain an input frequency coefficient;

[0015] The input time error coefficient and the input frequency coefficient are normalized, and the login behavior abnormality coefficient is obtained according to the normalized input time error coefficient and the input frequency coefficient.

[0016] Optionally, the login time deviation coefficient and the current application system access coefficient include:

[0017] Obtain the total duration of the user's login in the current application system on the government affairs platform, calculate the absolute difference between the total duration of the login and the preset duration of the login, and divide the absolute difference by the preset duration of the login to obtain the login time deviation coefficient;

[0018] Obtain the time interval of each click in the current application system when the user logs in to the government affairs platform, calculate the difference between the preset fastest click time interval and the click time interval, and calculate the sum of all differences to obtain the click speed abnormality coefficient;

[0019] The total number of function modules clicked in the current application system is obtained, and the total number of function modules clicked is multiplied by the click speed abnormality coefficient to obtain the current application system access coefficient.

[0020] Optionally, the login network instability coefficient includes:

[0021] Obtain the network signal values ​​at different times when the user logs into the current application system on the government affairs platform, and perform sequence analysis based on time to obtain the network signal sequence, calculate the standard deviation of the network signal sequence, and use the standard deviation as the signal fluctuation value;

[0022] Compare each signal value in the network signal sequence with a preset minimum signal value, and mark the signal value less than the preset minimum signal value as 0; divide the total number of 0s in the network signal sequence by the total number of signal values ​​to obtain the signal disconnection value;

[0023] The signal fluctuation value and the signal disconnection value are normalized, and the login network instability coefficient is obtained according to the normalized signal fluctuation value and signal disconnection value.

[0024] Optionally, obtaining the first login status coefficient according to the login status data includes:

[0025] The login time deviation coefficient, login behavior abnormality coefficient, login network instability coefficient and current application system access coefficient are used as input items of fuzzy rules, and the first login state coefficient is used as output item;

[0026] Fuzzify the input items and convert the exact input values ​​into fuzzy sets;

[0027] Define fuzzy rules based on the fuzzy sets of input items to map input items to output items;

[0028] According to the fuzzy rules, the input items are inferred to determine the fuzzy value of the output items;

[0029] For each rule, calculate the membership of its predecessor and take the minimum value as the activation of the rule;

[0030] Synthesize the results of all rules and calculate the fuzzy set of output items;

[0031] The fuzzy value of the output item is converted into an exact value, and the first login state coefficient is output according to the defuzzification result.

[0032] Optionally, obtaining the latest login verification password information according to the first login state coefficient and the preset login verification password information includes:

[0033] Split the password verification action of the preset login verification password information according to the preset password verification action library, assign a different preset importance value to each of the split actions, and add the preset importance values ​​of all actions to obtain a preliminary password importance value;

[0034] Calculate the sum of the first login state coefficient and the value 1, and multiply the calculated sum by the preliminary password importance value to obtain the final password importance value, and select from the preset verification password action library according to the final password importance value to obtain the latest login verification password information.

[0035] Optionally, judging whether the user needs to enter the password again to log in next time in combination with a preset login status coefficient threshold includes:

[0036] Obtain the login time deviation coefficient, login behavior abnormality coefficient, login network instability coefficient and current application system access coefficient of the user in the process of verifying the login according to the latest login verification password information, obtain the second login state coefficient, and compare the second login state coefficient with the preset login state coefficient threshold;

[0037] If the second login status coefficient is less than the preset login status coefficient threshold, the government affairs platform automatically saves the user's login information, and the default user can log in directly the next time without having to enter the password to log in to the platform again;

[0038] If the second login status coefficient is not less than the preset login status coefficient threshold, the government platform will automatically not save the user's login information, and the user may still need to enter the password again to log in to the platform the next time.

[0039] In a second aspect of the present invention, a unified management system for cryptographic services based on cloud computing is proposed, the system comprising:

[0040] Judgment module: obtain the preset information sensitivity level of the application system currently logged in by the user on the government affairs platform, and judge whether the preset information sensitivity level of the application system currently logged in is the highest level;

[0041] Login status coefficient module: if the preset information sensitivity level of the currently logged-in application system is not the highest level, the user's login status data in the currently logged-in application system is obtained, and the first login status coefficient is obtained according to the login status data; the login status data includes the login time deviation coefficient, the login behavior abnormality coefficient, the login network instability coefficient and the current application system access coefficient;

[0042] Latest verification module: when the user switches to an application system with a higher information sensitivity level than the currently logged-in application system, the latest login verification password information is obtained according to the first login state coefficient and the preset login verification password information, and the latest login verification password information is sent to the user for verification login;

[0043] Judgment management module: obtain the login status data of the user during the verification login process according to the latest login verification password information, obtain the second login status coefficient, and combine the preset login status coefficient threshold to determine whether the user needs to enter the password again to log in next time.

[0044] In a third aspect of the implementation of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, any of the above-mentioned methods is implemented.

[0045] Beneficial effects of the present invention:

[0046] The present invention proposes a unified management system, method and storage medium for password services based on cloud computing, which can adjust the login passwords of other application systems according to the actual login status of the current application system on the government affairs platform, reduce the risk of the government affairs platform being attacked and data leakage, and can determine whether a user needs to log in with a password every time he logs in to the government affairs platform according to the actual situation, thereby facilitating user operation and reducing the impact on user efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0048] Figure 1 A flowchart of a unified management approach for cloud-based cryptographic services;

[0049] Figure 2 Framework diagram for a unified management system for cloud-based cryptographic services. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0051] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making any creative work shall fall within the scope of protection of the present invention.

[0052] The embodiment of the present invention provides a unified management method for cryptographic services based on cloud computing. Figure 1 , Figure 1 A flowchart of a unified management method for cryptographic services based on cloud computing provided by an embodiment of the present invention. The method comprises the following steps:

[0053] Obtain the preset information sensitivity level of the application system currently logged in by the user on the government affairs platform, and determine whether the preset information sensitivity level of the application system currently logged in is the highest level;

[0054] If the preset information sensitivity level of the currently logged-in application system is not the highest level, the user's login status data in the currently logged-in application system is obtained, and a first login status coefficient is obtained according to the login status data; the login status data includes a login time deviation coefficient, a login behavior abnormality coefficient, a login network instability coefficient, and a current application system access coefficient;

[0055] When the user switches to an application system with a higher information sensitivity level than the currently logged-in application system, the latest login verification password information is obtained according to the first login state coefficient and the preset login verification password information, and the latest login verification password information is sent to the user for verification login;

[0056] The login status data of the user during the login verification process according to the latest login verification password information is obtained to obtain a second login status coefficient, and combined with a preset login status coefficient threshold, it is determined whether the user needs to enter the password again to log in the next time.

[0057] Based on the unified management method of password services based on cloud computing provided by the embodiment of the present invention, through the above method, the login passwords of other application systems can be adjusted according to the actual login status of the current application system on the government platform, thereby reducing the risk of the government platform being attacked and data leaks, and can determine whether the user needs to log in with a password every time he logs in to the government platform according to the actual situation, thereby facilitating user operation and reducing the impact on user efficiency.

[0058] In one embodiment, determining whether the preset information sensitivity level of the currently logged-in application system is the highest level includes:

[0059] If the preset information sensitivity level of the currently logged-in application system is the highest level, the user will be granted access to all other application systems directly without sending an additional login password for login verification;

[0060] If the preset information sensitivity level of the currently logged-in application system is not the highest level, the login status data of the user in the currently logged-in application system is obtained, and the first login status coefficient is obtained based on the login status data. When the user switches to an application system with a higher information sensitivity level than the currently logged-in application system, the password is resent for login verification.

[0061] It should be noted that the preset information sensitivity level is set by professionals based on the actual situation. It can comprehensively consider factors such as the nature of the data, legal and regulatory requirements, business needs, and potential risks, and reasonably evaluate and classify the data sensitivity of different application systems on the government platform, and determine different sensitivity levels. The specific preset information sensitivity level is determined according to the actual situation and is not limited or elaborated.

[0062] In one implementation, precise permission control and security verification are achieved by dynamically evaluating the user login status and the sensitivity level of the application system. This method effectively reduces the risk of disorderly access of low-sensitivity information systems to highly sensitive information, preventing users from unknowingly accessing sensitive data, thereby reducing the possibility of data leakage. At the same time, it simplifies the login process of highly sensitive systems and improves the user experience, allowing users to maintain security and effectively improve work efficiency when handling high-risk information. This flexible permission management method not only enhances the security of the government platform, but also provides convenience for users, helping to establish a more trusted digital government environment.

[0063] In one embodiment, the login behavior abnormality coefficient includes:

[0064] The total number of times the user incorrectly enters the password and the duration of each incorrect password entry are obtained during the process of the user logging into the current application system on the government affairs platform, and the sequence is performed based on time to obtain the sequence of duration of incorrect password entry; and the mean of the sequence of duration of incorrect password entry is calculated as the input time error coefficient;

[0065] Obtain the total number of times the user enters the password, and calculate the time interval between two adjacent password inputs to obtain a password input time interval sequence, calculate the mean of the password input time interval sequence, and divide the mean by the preset input interval to obtain an input frequency coefficient;

[0066] The input time error coefficient and the input frequency coefficient are normalized, and the login behavior abnormality coefficient is obtained according to the normalized input time error coefficient and the input frequency coefficient.

[0067] It should be noted that the login behavior abnormality coefficient obtained according to the normalized input time error coefficient and input frequency coefficient can be, for example, Wherein, Dax is the coefficient of abnormal login behavior, Wv and Pn are respectively the normalized input time error coefficient and input frequency coefficient, a1 and a2 are respectively the preset proportional coefficients of Wv and Pn, and f1 and f2 are both greater than 0; in addition, a1 and a2 are set by professionals according to the actual situation. Generally, the sum of a1 and a2 is 1. For example, a1 and a2 can be 0.5 and 0.5 respectively, or can be other numbers without specific limitation.

[0068] It should be noted that, through the user's login log records on the government platform, the timestamps and durations of the user's password input are automatically collected to construct a sequence of incorrect input durations; by monitoring the time difference between each password input, a sequence of password input time intervals is formed. Other acquisition methods can also be used, which are not specifically limited or elaborated on; in addition, the preset input interval is set by professionals based on actual circumstances, which are not specifically elaborated or limited on.

[0069] It should be noted that the login behavior abnormality coefficient refers to the average duration of the user's incorrect password input and the interval time of the user's password input during the process of the user logging into the current application system on the government platform; if the average duration of the user's incorrect password input and the interval time of the user's password input are larger, it means that the login status during the process of logging into the current application system on the government platform is worse. When the user switches to an application system with a higher preset information sensitivity level than the current logged-in application system, it is necessary to resend the login verification password information for login verification, and resending the login verification password information is more complicated. The reason is that when the user logs into the current application system on the government platform, the longer the average duration of the incorrect password input and the interval time of the password input are, it usually means that the user has encountered more difficulties during the login process, which may indicate that the user is less familiar with the system or there are potential security risks, such as the possibility of password forgetting or account theft. Such a poor login status directly affects the security of the system. Therefore, when the user switches to an application system with a higher preset information sensitivity level, it is necessary to resend the login verification password information and perform complex verification. This is because highly sensitive application systems usually handle more confidential and important information. If the user's login status is not good, the added verification steps can effectively reduce the risk of unauthorized access to sensitive information and ensure that only users with strict identity authentication can access these systems, thereby protecting the security and integrity of the data.

[0070] In one implementation, the above calculation method can directly and comprehensively calculate the login behavior abnormality coefficient, and the judgment of the subsequent login status coefficient is more accurate.

[0071] In one embodiment, the login time deviation coefficient and the current application system access coefficient include:

[0072] Obtain the total duration of the user's login in the current application system on the government affairs platform, calculate the absolute difference between the total duration of the login and the preset duration of the login, and divide the absolute difference by the preset duration of the login to obtain the login time deviation coefficient;

[0073] Obtain the time interval of each click in the current application system when the user logs in to the government affairs platform, calculate the difference between the preset fastest click time interval and the click time interval, and calculate the sum of all differences to obtain the click speed abnormality coefficient;

[0074] The total number of function modules clicked in the current application system is obtained, and the total number of function modules clicked is multiplied by the click speed abnormality coefficient to obtain the current application system access coefficient.

[0075] It should be noted that the preset login duration and the preset fastest click time interval are set by professionals according to actual conditions, and are not specifically described or limited; in addition, when a user logs in to the current application system on the government affairs platform, the total login duration can be obtained through the login log record on the government affairs platform, or other acquisition methods, which are not specifically limited or detailed;

[0076] It should be noted that the time interval between each click and the total number of function modules clicked in the current application system can be obtained through the login log records on the government affairs platform, or other acquisition methods, which are not limited or elaborated in detail;

[0077] It should be noted that the login time deviation coefficient refers to the degree to which the actual login time of the user deviates from the preset login duration during the process of logging into the current application system on the government platform. The greater the degree to which the actual login time deviates from the preset login duration, the worse the login status during the process of logging into the current application system on the government platform. When the user switches to an application system with a higher information sensitivity level than the preset information sensitivity level of the currently logged-in application system, it is necessary to resend the login verification password information for login verification, and resending the login verification password information is more complicated. The reason is that the login time deviation coefficient indicates the duration of the user's actual login process on the government platform and the preset normal Differences between login times; if the actual login time deviates significantly from the preset time (for example, too long), this usually indicates that the user encountered problems during the login process, such as entering the wrong password multiple times and needing to re-enter the verification code; this situation may reflect the abnormality of the user's operation or the existence of potential security risks, such as an account being attempted to be logged in by an unfamiliar person; therefore, when the user switches to a system with a higher information sensitivity level than the current application system, in order to ensure security, the system will resend more complex login verification password information; this is because sensitive information systems require higher access security to prevent unauthorized access and data leakage, ensure that visitors are truly authorized users, and reduce security risks.

[0078] It should be noted that the current application system access coefficient refers to the degree to which the time interval between each click in the current application system is faster than the preset fastest click time interval and the total number of function modules clicked when the user logs in on the government affairs platform; the greater the degree to which the time interval between clicks is faster than the preset fastest click time interval and the greater the total number of function modules clicked, the worse the login status during the process of logging in to the current application system on the government affairs platform. When the user switches to an application system with a higher information sensitivity level than the preset information sensitivity level of the currently logged in application system, it is necessary to resend the login verification password information to verify the login, and resending the login verification password information is more complicated because this may indicate that the user's operation speed is abnormal and exceeds the normal user's usage behavior. This situation may mean that the user is operating through an automated script, or trying to quickly browse and operate a large number of function modules to detect system vulnerabilities, or may even be performing malicious behavior. Therefore, this login status is considered abnormal and there is a potential security risk.

[0079] In one embodiment, the login network instability coefficient includes:

[0080] Obtain the network signal values ​​at different times when the user logs into the current application system on the government affairs platform, and perform sequence analysis based on time to obtain the network signal sequence, calculate the standard deviation of the network signal sequence, and use the standard deviation as the signal fluctuation value;

[0081] Compare each signal value in the network signal sequence with a preset minimum signal value, and mark the signal value less than the preset minimum signal value as 0; divide the total number of 0s in the network signal sequence by the total number of signal values ​​to obtain the signal disconnection value;

[0082] The signal fluctuation value and the signal disconnection value are normalized, and the login network instability coefficient is obtained according to the normalized signal fluctuation value and signal disconnection value.

[0083] It should be noted that the present invention can use the following formula to calculate the login network instability coefficient, and the calculation expression is: QW=b1×ED+b2×RF; wherein, QW is the login network instability coefficient, ED and RF are the signal fluctuation value and signal disconnection value after normalization, respectively, b1 and b2 are the preset proportional coefficients of ED and RF, respectively, and b1 and b2 are both greater than 0.

[0084] It should be noted that b1 and b2 are also set by professionals according to actual conditions. Generally, the sum of b1 and b2 is 1. For example, b1 and b2 can be 0.5 and 0.5 respectively, or other numbers, which are not specifically limited.

[0085] It should be noted that the preset minimum signal value is set by professionals based on actual conditions, and is not limited or elaborated on in detail; the network signal value is the signal strength, which indicates the network signal strength of the device for logging into the government affairs platform in the current application system, such as the WI FI signal strength value, or it can be other values, depending on the actual situation; in addition, during the process of the user logging into the current application system on the government affairs platform, the network signal values ​​at different times can be obtained through the login log records on the government affairs platform, or can be obtained by other means, and are not limited or elaborated on in detail.

[0086] It should be noted that the login network instability coefficient refers to the degree of network fluctuation and network disconnection during the user's login to the current application system on the government platform. The greater the degree of network fluctuation and the greater the degree of network disconnection, the worse the login status during the login to the current application system on the government platform. When the user switches to an application system with a higher information sensitivity level than the preset information sensitivity level of the currently logged-in application system, it is necessary to resend the login verification password information to verify the login, and resending the login verification password information is more complicated. The reason is that the login network instability coefficient reflects the network stability of the user during the login process of the government platform. If the network fluctuation is greater or the number of network disconnections increases, it means that the user may encounter frequent interruptions or delays when logging in, which will not only increase the time for the user to enter the password, but may also cause multiple login failures, thereby reducing the reliability of successful login; when the user switches to an application system with a higher information sensitivity level, the system will require the login verification password information to be resent to ensure the security of identity authentication. This process requires more complex operations because highly sensitive systems usually carry more important data and functions, and therefore have higher security requirements. The system must verify the identity of the user in an unstable network environment to prevent potential unauthorized access and data leakage risks. Such additional verification steps help protect the security of sensitive information and ensure that only authenticated users can access higher-level application systems, thereby improving the security of the entire government platform.

[0087] In one embodiment, obtaining the first login status coefficient according to the login status data includes:

[0088] The login time deviation coefficient, login behavior abnormality coefficient, login network instability coefficient and current application system access coefficient are used as input items of fuzzy rules, and the first login state coefficient is used as output item;

[0089] Fuzzify the input items and convert the exact input values ​​into fuzzy sets;

[0090] Define fuzzy rules based on the fuzzy sets of input items to map input items to output items;

[0091] According to the fuzzy rules, the input items are inferred to determine the fuzzy value of the output items;

[0092] For each rule, calculate the membership of its predecessor and take the minimum value as the activation of the rule;

[0093] Synthesize the results of all rules and calculate the fuzzy set of output items;

[0094] The fuzzy value of the output item is converted into an exact value, and the first login state coefficient is output according to the defuzzification result.

[0095] It should be noted that the above steps are explained:

[0096] First, the login time deviation coefficient, login behavior abnormality coefficient, login network instability coefficient and current application system access coefficient are determined as the input items of the fuzzy rule; in this way, the influence of multiple factors on the login status can be comprehensively considered;

[0097] Fuzzification: In this stage, the exact value of each input item is converted into a fuzzy set. For example, the login time deviation coefficient can be divided into fuzzy levels such as "low", "medium" and "high" to better reflect the actual user behavior status;

[0098] Define fuzzy rules: Based on the fuzzy set of input items, define fuzzy rules. For example, if the "login behavior abnormality coefficient" is high and the "current application system access coefficient" is high, the output "first login state coefficient" should also be high. These rules will help understand the impact of different input combinations on the output.

[0099] Reasoning process: In this step, the input items are mapped to the output items through fuzzy reasoning. Fuzzy rules are used to calculate the fuzzy values ​​of the output items in different situations and evaluate the overall login status of the user.

[0100] Calculate the activation degree of rules: For each rule, calculate the membership degree of its premise part and take the minimum value as the activation degree of the rule. In this way, you can determine which rules have the greatest impact on the output items.

[0101] Result synthesis: The activations of all rules are synthesized to calculate the fuzzy set of output items. This step ensures that the comprehensive impact of all input items is fully considered.

[0102] Defuzzification: Finally, the fuzzy value of the output item is converted to an exact value to obtain the first login state coefficient. Defuzzification is usually performed using techniques such as the centroid method or the maximum membership method.

[0103] In one implementation, the above approach can handle uncertainty and ambiguity, especially when faced with complex user behavior. By integrating multiple factors and using fuzzy logic, the system can more accurately assess the user's login status and identify potential abnormal behavior in a timely manner.

[0104] In one embodiment, obtaining the latest login verification password information according to the first login state coefficient and the preset login verification password information includes:

[0105] Split the password verification action of the preset login verification password information according to the preset password verification action library, assign a different preset importance value to each of the split actions, and add the preset importance values ​​of all actions to obtain a preliminary password importance value;

[0106] Calculate the sum of the first login state coefficient and the value 1, and multiply the calculated sum by the preliminary password importance value to obtain the final password importance value, and select from the preset verification password action library according to the final password importance value to obtain the latest login verification password information.

[0107] It should be noted that the preset login verification password information, the preset verification password action library and the preset importance value of each action are all set by professionals according to actual situations. For example, the preset importance value of an ordinary numeric login password is 0.5, the preset importance value of a face verification password is 0.7, etc. The specific numbers are determined according to actual situations and are not limited or elaborated. In addition, in addition to face actions, the preset verification password action library also includes fingerprint password verification, voice verification, etc., which are determined according to actual situations and are not limited or elaborated.

[0108] In one implementation, through the above method, the password verification information can be obtained according to the actual situation when the user switches to an application system with a higher information sensitivity level than the currently logged-in application system, which is more in line with the actual situation and reduces the risk of data leakage.

[0109] In one embodiment, judging whether the user needs to enter the password again to log in next time in combination with the preset login status coefficient threshold includes:

[0110] Obtain the login time deviation coefficient, login behavior abnormality coefficient, login network instability coefficient and current application system access coefficient of the user in the process of verifying the login according to the latest login verification password information, obtain the second login state coefficient, and compare the second login state coefficient with the preset login state coefficient threshold;

[0111] If the second login status coefficient is less than the preset login status coefficient threshold, the government affairs platform automatically saves the user's login information, and the default user can log in directly the next time without having to enter the password to log in to the platform again;

[0112] If the second login status coefficient is not less than the preset login status coefficient threshold, the government platform will automatically not save the user's login information, and the user may still need to enter the password again to log in to the platform the next time.

[0113] It should be noted that the preset login status coefficient threshold is set by professionals based on actual circumstances, and is determined based on actual circumstances without limitation or elaboration; and the password that the user needs to enter the next time he logs in is generally the default initial password of the government platform, such as ID card information, verification code, etc., which is determined based on actual circumstances without limitation or elaboration.

[0114] In one implementation method, it is possible to balance user experience and system security; by flexibly determining whether the password needs to be re-entered based on the user's login status coefficient, the system can simplify the login process and improve user convenience without sacrificing security; when the user's login status is good, the next time the user logs in, the system can be quickly entered, reducing unnecessary verification steps, making user operation convenient and reducing the impact on user efficiency; and when an abnormality or potential risk is detected, re-verification is mandatory to enhance account protection measures; this intelligent management method effectively improves the level of security protection and ensures the overall security and availability of the government affairs platform.

[0115] Based on the same inventive concept, the embodiment of the present invention also provides a unified management system for cryptographic services based on cloud computing. Figure 2 , Figure 2 A framework diagram of a unified management system for cryptographic services based on cloud computing provided by an embodiment of the present invention, the system comprising:

[0116] Judgment module: obtain the preset information sensitivity level of the application system currently logged in by the user on the government affairs platform, and judge whether the preset information sensitivity level of the application system currently logged in is the highest level;

[0117] Login status coefficient module: if the preset information sensitivity level of the currently logged-in application system is not the highest level, the user's login status data in the currently logged-in application system is obtained, and the first login status coefficient is obtained according to the login status data; the login status data includes the login time deviation coefficient, the login behavior abnormality coefficient, the login network instability coefficient and the current application system access coefficient;

[0118] Latest verification module: when the user switches to an application system with a higher information sensitivity level than the currently logged-in application system, the latest login verification password information is obtained according to the first login state coefficient and the preset login verification password information, and the latest login verification password information is sent to the user for verification login;

[0119] Judgment management module: obtain the login status data of the user during the verification login process according to the latest login verification password information, obtain the second login status coefficient, and combine the preset login status coefficient threshold to determine whether the user needs to enter the password again to log in next time.

[0120] Based on the cloud computing-based unified management system for password services provided by the embodiment of the present invention, through the above method, it is possible to adjust the login passwords of other application systems according to the actual login status of the current application system on the government affairs platform, thereby reducing the risk of the government affairs platform being attacked and data leaks, and can determine whether a user needs to log in with a password every time he logs in to the government affairs platform according to the actual situation, thereby making it convenient for users to operate and reducing the impact on user efficiency.

[0121] In another embodiment provided by the present invention, a computer-readable storage medium is also provided, in which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned cloud computing-based unified management methods for cryptographic services are implemented.

[0122] In another embodiment provided by the present invention, a computer program product including instructions is also provided, which, when executed on a computer, enables the computer to execute any unified management of cryptographic services based on cloud computing in the above-mentioned embodiments.

[0123] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A unified management method for cryptographic services based on cloud computing, characterized in that: The following steps are involved: Obtain the preset information sensitivity level of the application system currently logged in by the user on the government affairs platform, and determine whether the preset information sensitivity level of the application system currently logged in is the highest level; If the preset information sensitivity level of the currently logged-in application system is not the highest level, the user's login status data in the currently logged-in application system is obtained, and a first login status coefficient is obtained according to the login status data; the login status data includes a login time deviation coefficient, a login behavior abnormality coefficient, a login network instability coefficient, and a current application system access coefficient; When the user switches to an application system with a higher information sensitivity level than the currently logged-in application system, the latest login verification password information is obtained according to the first login state coefficient and the preset login verification password information, and the latest login verification password information is sent to the user for verification login; The login status data of the user during the login verification process according to the latest login verification password information is obtained to obtain a second login status coefficient, and combined with a preset login status coefficient threshold, it is determined whether the user needs to enter the password again to log in the next time.

2. The unified management method of cryptographic services based on cloud computing according to claim 1, characterized in that: The login behavior abnormality coefficient includes: The total number of times the user incorrectly enters the password and the duration of each incorrect password entry are obtained during the process of the user logging into the current application system on the government affairs platform, and the sequence is performed based on time to obtain the sequence of duration of incorrect password entry; and the mean of the sequence of duration of incorrect password entry is calculated as the input time error coefficient; Obtain the total number of times the user enters the password, and calculate the time interval between two adjacent password inputs to obtain a password input time interval sequence, calculate the mean of the password input time interval sequence, and divide the mean by the preset input interval to obtain an input frequency coefficient; The input time error coefficient and the input frequency coefficient are normalized, and the login behavior abnormality coefficient is obtained according to the normalized input time error coefficient and the input frequency coefficient.

3. The unified management method of cryptographic services based on cloud computing according to claim 1, characterized in that: The login time deviation coefficient includes: The total duration of the user's login in the current application system on the government platform is obtained, and the absolute difference between the total login duration and the preset login duration is calculated, and the absolute difference is divided by the preset login duration to obtain the login time deviation coefficient.

4. The unified management method of cryptographic services based on cloud computing according to claim 1, characterized in that: The current application system access coefficient includes: Obtain the time interval of each click in the current application system when the user logs in to the government affairs platform, calculate the difference between the preset fastest click time interval and the click time interval, and calculate the sum of all differences to obtain the click speed abnormality coefficient; The total number of function modules clicked in the current application system is obtained, and the total number of function modules clicked is multiplied by the click speed abnormality coefficient to obtain the current application system access coefficient.

5. The unified management method of cryptographic services based on cloud computing according to claim 1, characterized in that: The login network instability coefficient includes: Obtain the network signal values ​​at different times when the user logs into the current application system on the government affairs platform, and perform sequence analysis based on time to obtain the network signal sequence, calculate the standard deviation of the network signal sequence, and use the standard deviation as the signal fluctuation value; Compare each signal value in the network signal sequence with a preset minimum signal value, and mark the signal value less than the preset minimum signal value as 0; divide the total number of 0s in the network signal sequence by the total number of signal values ​​to obtain the signal disconnection value; The signal fluctuation value and the signal disconnection value are normalized, and the login network instability coefficient is obtained according to the normalized signal fluctuation value and signal disconnection value.

6. The unified management method of cryptographic services based on cloud computing according to claim 1, characterized in that: Obtaining the first login status coefficient according to the login status data includes: The login time deviation coefficient, login behavior abnormality coefficient, login network instability coefficient and current application system access coefficient are used as input items of fuzzy rules, and the first login state coefficient is used as output item; Fuzzify the input items and convert the exact input values ​​into fuzzy sets; Define fuzzy rules based on the fuzzy sets of input items to map input items to output items; According to the fuzzy rules, the input items are inferred to determine the fuzzy value of the output items; For each rule, calculate the membership of its predecessor and take the minimum value as the activation of the rule; Synthesize the results of all rules and calculate the fuzzy set of output items; The fuzzy value of the output item is converted into an exact value, and the first login state coefficient is output according to the defuzzification result.

7. The unified management method of cryptographic services based on cloud computing according to claim 1, characterized in that: The latest login verification password information is obtained according to the first login state coefficient and the preset login verification password information, including: Split the password verification action of the preset login verification password information according to the preset password verification action library, assign a different preset importance value to each of the split actions, and add the preset importance values ​​of all actions to obtain a preliminary password importance value; Calculate the sum of the first login state coefficient and the value 1, and multiply the calculated sum by the preliminary password importance value to obtain the final password importance value, and select from the preset verification password action library according to the final password importance value to obtain the latest login verification password information.

8. The unified management method of cryptographic services based on cloud computing according to claim 1, characterized in that: Combining the preset login status coefficient threshold to determine whether the user needs to enter the password again to log in next time includes: Obtain the login time deviation coefficient, login behavior abnormality coefficient, login network instability coefficient and current application system access coefficient of the user in the process of verifying the login according to the latest login verification password information, obtain the second login state coefficient, and compare the second login state coefficient with the preset login state coefficient threshold; If the second login status coefficient is less than the preset login status coefficient threshold, the government affairs platform automatically saves the user's login information, and the default user can log in directly the next time without having to enter the password to log in to the platform again; If the second login status coefficient is not less than the preset login status coefficient threshold, the government platform will automatically not save the user's login information, and the user may still need to enter the password again to log in to the platform the next time.

9. A unified management system for cryptographic services based on cloud computing, used to implement the unified management method for cryptographic services based on cloud computing as described in any one of claims 1 to 8, characterized in that: The system comprises: Judgment module: obtain the preset information sensitivity level of the application system currently logged in by the user on the government affairs platform, and judge whether the preset information sensitivity level of the application system currently logged in is the highest level; Login status coefficient module: if the preset information sensitivity level of the currently logged-in application system is not the highest level, the user's login status data in the currently logged-in application system is obtained, and the first login status coefficient is obtained according to the login status data; the login status data includes the login time deviation coefficient, the login behavior abnormality coefficient, the login network instability coefficient and the current application system access coefficient; Latest verification module: when the user switches to an application system with a higher information sensitivity level than the currently logged-in application system, the latest login verification password information is obtained according to the first login state coefficient and the preset login verification password information, and the latest login verification password information is sent to the user for verification login; Judgment management module: obtain the login status data of the user during the verification login process according to the latest login verification password information, obtain the second login status coefficient, and combine the preset login status coefficient threshold to determine whether the user needs to enter the password again to log in next time.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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