Method and apparatus for implementing cloud password service resource pool

Abstract

The application relates to the field of resource pools, and discloses an implementation method and device of a cloud password service resource pool, which comprises the following steps: obtaining historical interaction data of each password in each server of the cloud password service resource pool, constructing a classification model to classify the historical interaction data, and calculating a time difference value between any two classification results; in a single server, obtaining a calling ratio of a single classification result, using the time difference value between any two classification results and the maximum value of the calling ratio to calculate a calling balance value between any two classification results, and then calculating the calling balance value of the single server; and using the calling balance value of each server and the load of each server to construct a target function, solving the target function, realizing password resource re-distribution, and realizing the cloud password resource pool. The application can improve the stability of the cloud password resource pool.

Description

Technical Field

[0001] This invention relates to the field of resource pool technology, and in particular to a method and apparatus for implementing a cloud cryptography service resource pool. Background Technology

[0002] With the rapid development of cloud computing technology, the cloud cryptography service resource pool, as a core infrastructure for ensuring data security in the cloud, has its stability and robustness directly related to the reliability of cloud services and the security of user data.

[0003] However, in actual operation, due to the dynamic nature of password service requests, the fluctuation of server load, and the static nature of password resource allocation strategies, cloud password resource pools often face the problem of uneven resource allocation: some servers are overloaded due to high-frequency password calls, while other servers are idle due to inefficient utilization.

[0004] This imbalance can lead to risks such as delayed response times, wasted resources, and even service interruptions in cryptographic services. Existing technologies mostly allocate resources through static thresholds or simple load balancing strategies, but these are difficult to adapt to the complex and ever-changing needs of cryptographic service scenarios. Summary of the Invention

[0005] To address the aforementioned technical problem of uneven resource allocation in cloud cryptography resource pools, this invention provides a method and apparatus for implementing cloud cryptography service resource pools.

[0006] In a first aspect, the present invention provides a method for implementing a cloud cryptography service resource pool, which adopts the following technical solution: The process involves: acquiring historical interaction data for each password from each server in the cloud cryptography service resource pool; normalizing the historical interaction data; constructing a classification model to classify the normalized historical interaction data; obtaining classification results; calculating the time difference between any two classification results; obtaining the call ratio of a single classification result among all classification results within a single server; calculating the call balance value between any two classification results using the maximum value of the time difference between any two classification results and the call ratio; obtaining the maximum value of the call balance value from any combination of any two classification results for a single server; acquiring the call balance value for each server in the cloud cryptography service resource pool; constructing an objective function using the call balance value and load of each server; minimizing the objective function by solving it; and realizing the redistribution of cryptography resources in the cloud cryptography service resource pool.

[0007] Preferably, the normalized historical interaction data includes: Obtain password interaction information from each server in the cloud password service resource pool, obtain historical interaction data for each password, normalize the time point sequence in the historical interaction data, and obtain normalized historical interaction data; wherein, a sample data in the historical interaction data is the time point sequence corresponding to the time point when a single password is called multiple times.

[0008] Preferably, the normalization includes: Get the minimum time interval between two password interaction calls, and use it as the minimum time scale value. Get the total number of minimum time scale values ​​in a day. Get the number of minimum time scale values ​​required from time 0:00 to the time point of interaction. Calculate the ratio of the number of minimum time scale values ​​to the total number. Use the number of minimum time scale values ​​as the numerator of the fraction and the total number as the denominator of the fraction. This is the normalized time point of interaction.

[0009] Preferably, calculating the time difference between any two classification results includes: Obtain the normalized time-point sequence data of a single password, perform peak point detection on the normalized time-point sequence data of a single password to obtain the representative time point of a single password, use an unsupervised classification model to classify the representative time points of all passwords in a single server, obtain the cluster center of any two classification results, calculate the Euclidean distance between the two cluster centers as the time difference value between the two classification results.

[0010] Preferably, the representative time points of the single password include: Histogram statistics are performed on the time-point sequence data of a single cryptography normalized. Peak point detection is performed on the histogram statistics results to obtain peak point detection results. The peak point detection results are sorted in descending order, and the peak points of the top 5 peaks in the descending sorted peak sequence are obtained. The time points corresponding to the peak points of the top 5 peaks are obtained as representative time points with interactive representativeness for a single cryptography.

[0011] Preferably, the call balancing value for a single server includes: Calculate the call balance value between the m-th classification result and the n-th classification result in a single server. .

[0012] ;in, It is an exponential function, and d is a hyperparameter. ; This represents the time difference between the m-th and n-th classification results; To find the maximum value of the ratio between the m-th classification result and the n-th classification result; This is the call balance value between the m-th classification result and the n-th classification result.

[0013] Preferably, the objective function construction includes: The objective function W for obtaining the cloud password resource pool is: I represents the total number of servers, i represents the traversal value of I, exp() is the exponential function, and s is a hyperparameter. ; R is the call balance value of the i-th server in the cloud password resource pool; R is the load variance value of all servers in the cloud password resource pool.

[0014] Preferably, the reallocation of cryptographic resources in the cloud cryptographic service resource pool includes: By solving the corresponding objective function, a new server number for each classification result can be obtained. Based on the new server number for each classification result, the password resources of the corresponding server in the cloud password service resource pool are exchanged and allocated, thus realizing the cloud password resource pool.

[0015] Secondly, the present invention provides an implementation device for a cloud cryptographic service resource pool, which adopts the following technical solution: A processor and a memory, the memory storing computer program instructions, which, when executed by the processor, implement the method for implementing a cloud cryptographic service resource pool according to any one of claims 1-8.

[0016] The above-described method for implementing the cloud cryptography service resource pool is used to generate a computer program, which is then stored in a memory for loading and execution by a processor. This allows for the creation of a system based on the memory and processor, making it convenient to use.

[0017] The present invention has the following technical effects: This invention categorizes similar cryptographic data for accessing cryptographic resources into one class and performs overall migration of this similar data, ensuring the regularity of resource allocation and reducing the problem of chaotic resource allocation.

[0018] This invention constructs a call balance value for a single server and an objective function for the cloud cryptographic service resource pool by leveraging the spatiotemporal characteristics of cryptographic resources. This ensures high call balance of cryptographic resources during allocation and improves the stability of the cloud cryptographic service resource pool. Attached Figure Description

[0019] Figure 1 This is a flowchart of steps S1-S3 in the implementation method of cloud cryptographic service resource pool according to an embodiment of the present invention. Detailed Implementation

[0020] This invention discloses a method for implementing a cloud cryptography service resource pool, referring to... Figure 1 ,include: S1: Obtain historical interaction data for each password from each server in the cloud password service resource pool, normalize the historical interaction data, construct a classification model to classify the normalized historical interaction data, obtain the classification results, and calculate the time difference value between any two classification results.

[0021] Password access management software is installed on each server in the cloud password service resource pool to collect password interaction information from each server, obtaining historical interaction data for ten consecutive days from the current time. A sample data point in the historical interaction data represents the time sequence corresponding to multiple accesses of a single password. The ten-day period used as the historical data collection range is an empirical value and can be adjusted by the implementer based on the specific implementation method.

[0022] Since each time point in the time series is represented as a time, which is not convenient for subsequent data analysis and processing, each time point in the time series is normalized.

[0023] The specific normalization process includes: obtaining the minimum time interval between two password interaction calls as the minimum time scale value; obtaining the total number of minimum time scale values ​​in a day; obtaining the number of minimum time scale values ​​required from 0:00 to the interaction time; calculating the ratio of the number of minimum time scale values ​​to the total number; using the number of minimum time scale values ​​as the numerator of the fraction and the total number as the denominator of the fraction; this is the normalized interaction time. The empirical value of using one day as the interaction cycle can be adjusted by the implementer according to the specific implementation method.

[0024] After obtaining the time-point sequence data of a single password, the time-point sequence lengths of different passwords are inconsistent due to the different number of interactions between them. Therefore, histogram statistics are performed on the time-point sequence data of the single password.

[0025] When performing histogram statistics, the normalized time points are used as the horizontal axis and the number of interactions corresponding to the normalized time points are used as the vertical axis to obtain the histogram statistics results. Peak point detection is then performed on the histogram statistics results to obtain the peak point detection results.

[0026] If the number of peaks in the peak detection results is greater than five, sort the peak detection results in descending order, obtain the peak points of the top 5 peaks in the descending sorted peak sequence, and obtain the time points corresponding to the peak points of the top 5 peaks as the representative time points with interactive representativeness for a single password.

[0027] If the number of peaks in the peak point detection results is less than or equal to five, it indicates that the amount of interactive data for a single password is too low, and its impact on the password call interaction resources of the server is relatively small. Therefore, the time-point sequence data of that single password should be discarded and not further analyzed. Here, 5 is an empirical value, which implementers can adjust according to the specific implementation method.

[0028] An unsupervised classification model is used to classify data at five representative time points for a single password. The single password is approximately classified into one class for all representative time points, resulting in multiple classification results. Each classification result includes at least one password. The unsupervised classification model can be selected from SOM (Self-Organizing Map) algorithm, hierarchical clustering algorithm, etc.

[0029] Obtain the cluster centers of any two classification results, calculate the Euclidean distance between the two cluster centers, and use it as the time difference value between the two classification results. Since the classification is performed on normalized data, the time difference value ranges from [0,1]. The larger the time difference value, the greater the difference in the time distribution of the representative time points in the two classification results, and the less likely it is to cause call blocking problems when passwords are called on various servers.

[0030] S2: In a single server, obtain the call ratio of a single classification result among all classification results. Calculate the call balance value between any two classification results using the time difference between any two classification results and the maximum value of the call ratio. Obtain the maximum value of the call balance value from any combination of two classification results in a single server, and use it as the call balance value of the single server.

[0031] Adjusting the time distribution differences can alleviate the congestion problem of password call interaction among servers in the cloud password service resource pool. However, if the time distribution of password call interaction among servers is large but the calls are frequent, it can still easily cause password call congestion.

[0032] To address the issue of single servers exhibiting significant time-distribution variations but high call frequency, the call concentration coefficient for all passwords within a single classification result on a single server is obtained. The process for obtaining the call concentration coefficient is as follows: First, the cumulative value of the peak value corresponding to the representative time point of each password in a single classification result is obtained as the call frequency of a single password. The call frequencies of all passwords are accumulated to obtain the total call frequency of a single classification result. The mean of the total call frequency among all classification results is calculated to obtain the mean of the total call frequency of all classification results.

[0033] Secondly, obtain the ratio of the total call frequency of a single category result to the average total call frequency of all category results. In the ratio formula, the total call frequency of a single category result is the numerator, and the average total call frequency of all category results is the denominator. The resulting ratio is used as the call ratio of a single category result. If the call ratio of any single category result is less than 1, it indicates a lower probability of risk. If the call ratio of a single category result is greater than 1, it indicates a higher probability of password blocking during the call.

[0034] Furthermore, the call balance value of a single server is calculated, the time difference between any two classification results in a single server and the maximum call ratio between these two classification results are calculated, the call balance value between any two classification results in a single server is obtained, all combinations of any two classification results in a single server are obtained, and the maximum call balance value among all combinations is obtained as the call balance value of a single server.

[0035] Obtain the m-th and n-th classification results from a single server, and calculate the time difference between the m-th and n-th classification results. .

[0036] Get the maximum value of the ratio between the m-th classification result and the n-th classification result. ,in, The ratio of calls to the m-th classification result. This represents the call ratio for the nth classification result.

[0037] Then, the call balance value between the m-th classification result and the n-th classification result is calculated.

[0038]

[0039] in, It is an exponential function, and d is a hyperparameter, which is taken as d=2 empirically.

[0040] This represents the time difference between the m-th and n-th classification results. The larger the value, the greater the difference in the time distribution of the representative time points in the two classification results, and the less likely it is to cause call blocking problems when passwords are called on various servers.

[0041] Call the maximum value of the ratio between the m-th classification result and the n-th classification result. The larger the value, the greater the probability that the password in the classification result will cause a blockage during the call, whereby... The value will be greater than 1, using the exponential function to... Perform mapping.

[0042] and then, The larger the value, the better the balance between the password call interaction between the m-th classification result and the n-th classification result, and the less likely the password call interaction will be blocked.

[0043] Then, obtain all possible pairwise combinations of any two classification results in all individual servers, calculate the call balance value of the corresponding two classification results in any two combinations, and obtain the largest call balance value from all the call balance values ​​of the combinations as the call balance value of a single server.

[0044] S3: Obtain the call balance value of each server in the cloud cryptography service resource pool, construct the objective function using the call balance value and load of each server, and realize the redistribution of cryptography resources in the cloud cryptography service resource pool by solving the objective function.

[0045] After obtaining the call balance value of a single server, the password call interaction resource balance of each server in the cloud password service resource pool can be achieved by adjusting the server in which the individual classification result of the single server is located in the cloud password service resource pool.

[0046] However, when using the call balance value of a single server to balance the password call interaction resources of each server in the cloud password service resource pool, the call ratio may result in similar call counts being assigned to the same server.

[0047] Although the number of password calls within each server in the cloud password service resource pool is similar, the overall amount of password data in a single server may be too high or too low, leading to an imbalance in password storage between different servers. For servers with high password storage, the risk resistance of a single server will decrease, and in case of emergencies, it is very easy to cause password call interaction blockage, which is not conducive to the stability of the cloud password service resource pool.

[0048] Obtain the target value function value W of the cloud password resource pool:

[0049] I represents the total number of servers, and i represents the traversal value of I. exp() is the exponential function, and s is a hyperparameter used for balancing. The weight allocation between R and S is determined by taking the empirical value s=1.5.

[0050] Let be the call balance value for the i-th server in the cloud password resource pool. The larger the value, the better the call balance of the password in the i-th server during password call interaction, and the less likely it is to cause password call interaction blocking problems. Therefore, the minimum call balance value among all servers is obtained as the lower limit of the call balance value of the cloud password resource pool. In addition, the higher the lower limit of the call balance value of the cloud password resource pool, the better the call balance of the password in the current cloud password resource pool during password call interaction. Therefore, the minimum value of the lower limit of the call balance value of the cloud password resource pool after mapping is obtained by using an exponential function.

[0051] R represents the load variance of all servers in the cloud password resource pool. The calculation process is as follows: obtain the upper limit of the storage capacity of a single server in the cloud password resource pool, obtain the current storage capacity of the current single server, use the current storage capacity as the numerator and the upper limit of the storage capacity as the denominator, calculate the ratio of the current storage capacity to the upper limit of the storage capacity, and obtain the variance of this ratio of all servers in the cloud password resource pool as the load variance of all servers.

[0052] The smaller the load variance of all servers in the cloud password resource pool, the more consistent the password storage volume of all servers in the cloud password resource pool is with their respective storage limits. This can reduce the impact of password call interaction blockage caused by excessive password storage volume of a single server in the event of an emergency, and improve the stability of the cloud password service resource pool.

[0053] Since the passwords in a single classification result have consistency at the interaction time point, the objective function of the cloud cryptography service resource pool is solved by taking the server number of all classification results in all servers in the cloud cryptography service resource pool as the variable. The objective function can be solved by methods such as particle swarm optimization and genetic algorithm.

[0054] By solving the corresponding objective function, a new server number for each classification result can be obtained. Based on the new server number for each classification result, the password resources of the corresponding server in the cloud password service resource pool are exchanged and allocated, thus realizing the cloud password resource pool.

[0055] To achieve dynamic allocation of the cloud cryptographic resource pool, the objective function value of the cloud cryptographic resource pool is obtained after a fixed interval. A threshold value for the objective function is set. When the objective function value is greater than or equal to the threshold value, the objective function is solved again. Based on the solution result, cryptographic resources in the cloud cryptographic service resource pool are reallocated, thus realizing the dynamic allocation of cryptographic resources in the cloud cryptographic service resource pool and completing the implementation of the cloud cryptographic resource pool. The fixed interval is taken as an empirical value of 30 days, and the objective function threshold is taken as an empirical value of 2. Both the fixed interval and the objective function threshold can be adjusted by the implementer according to the specific implementation scenario.

[0056] This invention also discloses an implementation apparatus for a cloud cryptographic service resource pool, including a processor and a memory. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, the implementation method of the cloud cryptographic service resource pool according to the present invention is implemented.

[0057] The system also includes other components well known to those skilled in the art, such as communication buses and communication interfaces, the settings and functions of which are known in the art and will not be described in detail here.

[0058] In this invention, the aforementioned memory can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, a computer-readable storage medium can be any suitable magnetic or magneto-optical storage medium, such as resistive random access memory (DRAM), dynamic random access memory (DRAM), static random access memory (SRAM), etc., or any other medium that can be used to store desired information and can be accessed by an application program, module, or both. Any such computer storage medium can be part of a device or accessible to or connected to a device.

[0059] The above are all preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, all equivalent changes made in accordance with the structure, shape and principle of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for implementing a cloud cryptography service resource pool, characterized in that, include: Obtain historical interaction data for each password from each server in the cloud password service resource pool, normalize the historical interaction data, construct a classification model to classify the normalized historical interaction data, obtain the classification results, and calculate the time difference value between any two classification results. The calculation of the time difference between any two classification results includes: Obtain the normalized time-point sequence data of a single password, perform peak point detection on the normalized time-point sequence data of a single password to obtain the representative time point of a single password, use an unsupervised classification model to classify the representative time points of all passwords in a single server, obtain the cluster center of any two classification results, calculate the Euclidean distance between the two cluster centers as the time difference value between the two classification results; In a single server, the call ratio of a single classification result among all classification results is obtained. Using the time difference between any two classification results and the maximum of the call ratios, the call balance value between any two classification results is calculated. The maximum of the call balance values ​​from any combination of two classification results in a single server is taken as the call balance value of the single server. The call balance value of the single server includes: Calculate the first in a single server The first classification result and the first Balance of calls among classification results : ； in, It is an exponential function. For hyperparameters, ; For the first The first classification result and the first The time difference value of each classification result; For the first The first classification result and the first The maximum value of the ratio of calls between the classification results; For the first The first classification result and the first The balance value of calls between classification results; Obtain the call balance value of each server in the cloud cryptography service resource pool, construct an objective function using the call balance value and load of each server, and minimize the objective function by solving it to achieve the redistribution of cryptographic resources in the cloud cryptography service resource pool, thus realizing the cloud cryptography resource pool; the objective function construction includes: Objective function for obtaining cloud password resource pool : ； The total number of all servers. Indicates to The traversal values, It is an exponential function. For hyperparameters, ; The first in the cloud password resource pool Call balance value for each server; This represents the load variance of all servers in the cloud password resource pool.

2. The method for implementing the cloud cryptography service resource pool according to claim 1, characterized in that, The normalized historical interaction data includes: Obtain password interaction information from each server in the cloud password service resource pool, obtain historical interaction data for each password, normalize the time point sequence in the historical interaction data, and obtain normalized historical interaction data. One sample of the historical interaction data is a time sequence corresponding to the time points when a single password is called multiple times.

3. The method for implementing the cloud cryptography service resource pool according to claim 2, characterized in that, The normalization includes: Get the minimum time interval between two password interaction calls, and use it as the minimum time scale value. Get the total number of minimum time scale values ​​in a day. Get the number of minimum time scale values ​​required from time 0:00 to the time point of interaction. Calculate the ratio of the number of minimum time scale values ​​to the total number. Use the number of minimum time scale values ​​as the numerator of the fraction and the total number as the denominator of the fraction. This is the normalized time point of interaction.

4. The method for implementing the cloud cryptography service resource pool according to claim 1, characterized in that, The representative time points of the individual password include: Histogram statistics are performed on the time-point sequence data of a single cryptography normalized. Peak point detection is performed on the histogram statistics results to obtain peak point detection results. The peak point detection results are sorted in descending order, and the peak points of the top 5 peaks in the descending sorted peak sequence are obtained. The time points corresponding to the peak points of the top 5 peaks are obtained as representative time points with interactive representativeness for a single cryptography.

5. The method for implementing a cloud cryptography service resource pool according to claim 1, characterized in that, The reallocation of cryptographic resources in the cloud cryptographic service resource pool includes: By solving the corresponding objective function, a new server number for each classification result can be obtained. Based on the new server number for each classification result, the password resources of the corresponding server in the cloud password service resource pool are exchanged and allocated, thus realizing the cloud password resource pool.

6. An apparatus for implementing a cloud cryptographic service resource pool, characterized in that, include: A processor and a memory, wherein the memory stores computer program instructions that, when executed by the processor, implement the method for implementing a cloud cryptographic service resource pool according to any one of claims 1-5.

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