Security protection method and apparatus for customer service management system

Abstract

The present invention relates to the technical field of network security protection. Disclosed are a security protection method and apparatus for a customer service management system. The method comprises: acquiring an employee data set, and performing permission assignment, so as to generate an employee operation permission set; performing identity verification on an access user, and determining a data management operation permission range of the access user; acquiring a sensitive data set for encryption processing, and storing same in a customer service management system; accessing data of the customer service management system, implementing an access control policy, and performing risk assessment, so as to generate a system risk level; extracting detected anomalous data, synchronizing same to a security protection network, and outputting a protection control policy; and executing the protection control policy for security assessment, regularly updating the protection control policy, and performing intelligent security protection on the customer service management system. The present invention solves the technical problem in the prior art that customer service management systems have low security protection capacity, which leads to difficulty in preventing network attacks, thus achieving the technical effect of improving the security protection capacity of customer service management systems.

Description

Security protection methods and devices for customer service management systems Technical Field

[0001] This invention relates to the field of network security protection technology, and specifically to a security protection method and device for a customer service management system. Background Technology

[0002] In the wave of the digital age, customer service management systems, as a crucial bridge between businesses and customers, bear multiple responsibilities, including handling customer inquiries, resolving issues, and improving customer satisfaction. However, with the rapid development of network technology and the increasing sophistication of hacker attack methods, customer service management systems face severe security challenges. Traditional network security defenses typically take action only after the system has been attacked, including but not limited to traditional antivirus software and signature-based intrusion detection. However, these methods cannot prevent attacks from occurring or effectively reduce losses to other terminals. Once a customer service management system is attacked, it can lead to serious consequences such as customer data breaches and system paralysis. Existing technologies suffer from low security protection capabilities in customer service management systems, making it difficult to prevent cyberattacks. Technical issues

[0003] This application provides a security protection method and apparatus for a customer service management system, which solves the technical problem that the low security protection capability of the existing customer service management system makes it difficult to prevent network attacks. Technical solutions

[0004] In view of the above problems, this application provides a security protection method and apparatus for a customer service management system.

[0005] A first aspect of this application provides a security protection method for a customer service management system, the method comprising:

[0006] Obtain an employee dataset, allocate permissions based on the employee dataset, and generate an employee operation permission set, wherein the employee operation permission set has a corresponding relationship with the employee dataset;

[0007] Based on the employee operation permission set, the access user is authenticated, and the data management operation permission range of the access user is determined according to the authentication result.

[0008] The sensitive dataset is obtained, encrypted, and then stored in the customer service management system.

[0009] Access the customer service management system according to the data management operation permission range, implement access control policies based on the encrypted sensitive dataset, monitor the customer service management system to conduct risk assessment, and generate a system risk level.

[0010] Construct a security protection network, perform anomaly detection and location based on the system risk level, extract anomaly detection data, synchronize the anomaly detection data to the security protection network, and output protection and control strategies.

[0011] The security assessment is performed by implementing the protection and control strategy, and the strategy is updated regularly based on the assessment results to provide intelligent security protection for the customer service management system.

[0012] A second aspect of this application provides a security protection device for a customer service management system, the device comprising:

[0013] The permission allocation module is used to obtain an employee dataset, allocate permissions based on the employee dataset, and generate an employee operation permission set, wherein the employee operation permission set has a corresponding relationship with the employee dataset.

[0014] The verification module is used to authenticate the accessing user based on the employee operation permission set, and determine the data management operation permission range of the accessing user based on the verification result;

[0015] An encryption processing module is used to acquire sensitive datasets, encrypt them, and store the encrypted sensitive datasets in the customer service management system.

[0016] The risk assessment module is used to access the customer service management system according to the data management operation permission range, implement access control policies based on the encrypted sensitive dataset, monitor the customer service management system to conduct risk assessment, and generate a system risk level.

[0017] The protection and control module is used to construct a security protection network, perform anomaly detection and location extraction based on the system risk level, synchronize the anomaly detection data to the security protection network, and output protection and control strategies.

[0018] A security protection module is used to perform security assessments by executing the protection control strategy, and to periodically update the protection control strategy based on the assessment results, thereby providing intelligent security protection for the customer service management system. Beneficial effects

[0019] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0020] First, an employee dataset is acquired, and permissions are assigned to it to generate employee operation permission sets, with a corresponding relationship between the employee operation permission sets and the employee datasets. Then, user authentication is performed based on these employee operation permission sets, and the data management operation permission range for each user is determined according to the authentication results. Next, a sensitive dataset is acquired, encrypted, and stored in the customer service management system. Data access to the customer service management system is granted according to the data management operation permission ranges, and access control policies are implemented based on the encrypted sensitive dataset. The customer service management system is monitored for risk assessment, generating a system risk level. Simultaneously, a security protection network is constructed, and anomaly detection and extraction are performed based on the system risk level. Anomaly detection data is synchronized to the security protection network, and protection control policies are output. Finally, the protection control policies are executed for security assessment, and the protection control policies are regularly updated based on the assessment results, providing intelligent security protection for the customer service management system. This addresses the technical problem of low security protection capabilities in existing customer service management systems, leading to difficulties in preventing network attacks, and achieves the technical effect of improving the security protection capabilities of customer service management systems. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 is a schematic diagram of a security protection method for a customer service management system provided in an embodiment of this application;

[0023] Figure 2 is a schematic diagram of the security protection device for the customer service management system provided in an embodiment of this application.

[0024] Explanation of reference numerals in the attached diagram: Permission allocation module 11, verification module 12, encryption processing module 13, risk assessment module 14, protection control module 15, security protection module 16. The best embodiment of the present invention

[0025] Example 1 Embodiments of the present invention

[0026] This application provides a security protection method and apparatus for a customer service management system, which solves the technical problem that the low security protection capability of the existing customer service management system makes it difficult to prevent network attacks.

[0027] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0028] It should be noted that the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to such processes, methods, products, or devices. Example

[0029] As shown in Figure 1, this application embodiment provides a security protection method for a customer service management system, wherein the method includes:

[0030] Obtain an employee dataset, allocate permissions based on the employee dataset, and generate an employee operation permission set, wherein the employee operation permission set has a corresponding relationship with the employee dataset;

[0031] The employee dataset is retrieved from the company database. This dataset includes employee names, positions, departments, job descriptions, start dates, and job levels. Permissions are assigned based on this dataset; that is, based on employee responsibilities and needs, employees are assigned corresponding operations they can perform in the system, thus generating an employee operation permission set. There is a correspondence between the employee operation permission set and the employee dataset; the employee operation permission set reflects the specific operations each employee can perform in the system, such as viewing, editing, and deleting.

[0032] Furthermore, the method for obtaining an employee dataset, allocating permissions based on the employee dataset, and generating an employee operation permission set includes:

[0033] Extract employee responsibility information and employee level information from the employee dataset;

[0034] Based on the employee responsibility information and the employee level information, a multi-level permission division is performed to generate a permission division result, which includes a first permission set, a second permission set, and a third permission set.

[0035] The employee dataset is evaluated periodically, and the first permission set, the second permission set, and the third permission set are adjusted according to the evaluation results to generate the employee operation permission set.

[0036] Employee responsibility information and employee level information are extracted from the employee dataset. Employee responsibility information includes job duties and job descriptions, while employee level information includes Level 1, Level 2, and Level 3. Based on the employee responsibility information, the responsibilities of each employee are analyzed to determine the scope of data and functions that each employee needs to access and operate. Simultaneously, based on the employee level information, the employee's operational permissions and position in the system's approval process are determined. Multi-level permission division is performed based on the combined employee responsibility information, resulting in three permission sets: a first permission set, a second permission set, and a third permission set. Each permission set represents the permission scope for employees at different levels and with different responsibilities. The first permission set is basic permissions, which are common to all employees, such as logging into the system and viewing public information. The second permission set is responsibility-related permissions, which refer to specific operational permissions assigned based on the employee's responsibilities, such as editing customer data and handling complaints. The third permission set is level-related permissions, which refer to higher-level permissions assigned based on the employee's level, such as data approval and system settings. The employee dataset may change over time (e.g., employee promotion, job transfer, resignation, etc.), so it is necessary to evaluate the employee dataset regularly. Based on the evaluation results, the first permission set, the second permission set, and the third permission set are adjusted to generate the employee operation permission set.

[0037] Based on the employee operation permission set, the access user is authenticated, and the data management operation permission range of the access user is determined according to the authentication result.

[0038] When a user accesses the customer service management system, the user's identity is verified. The purpose of the verification is to confirm the visitor's identity and ensure that only authorized employees or relevant personnel can enter the system. After the identity verification is successful, the user's data management operation permission range is determined according to the employee's operation permission set.

[0039] The sensitive dataset is obtained, encrypted, and then stored in the customer service management system.

[0040] Identify sensitive data from the customer service management system, such as customer personal information, transaction records, account information, and internal company documents, and extract the sensitive dataset. Encrypt the sensitive dataset to prevent unauthorized access and data leakage, and then store the encrypted sensitive dataset in the customer service management system.

[0041] Furthermore, the method of acquiring sensitive datasets, encrypting them, and storing the encrypted sensitive datasets in the customer service management system includes:

[0042] Determine data sensitivity based on the data business context and data usage.

[0043] Based on the aforementioned data sensitivity, a data traversal analysis is performed on the customer service management system to identify sensitive datasets;

[0044] The sensitive dataset is encrypted using a key with an asymmetric encryption algorithm to generate an encrypted sensitive dataset.

[0045] The key and the encrypted sensitive dataset are encrypted and stored in the customer service management system as data pairs.

[0046] Data sensitivity refers to the degree of potential loss or risk that a company or customer may suffer when data is leaked or misused. Data business context refers to the business scenarios, needs, characteristics, and sources of the data. Data purpose refers to the application scenarios of the data, such as customer service, data analysis, and decision support. Based on business context and data purpose, data is categorized into different sensitivity levels, such as high sensitivity, medium sensitivity, and low sensitivity. High-sensitivity data includes customer personal information and financial information, which could cause significant losses if leaked; medium-sensitivity data consists of internal business data; and low-sensitivity data is publicly available information or data with minimal impact on the company. A data traversal analysis is performed on the customer service management system based on data sensitivity to identify which datasets are sensitive. Asymmetric encryption algorithms use a pair of keys, including a public key and a private key, to encrypt and decrypt data. Asymmetric encryption algorithms are used to encrypt sensitive datasets using the public key, generating encrypted sensitive datasets. These encrypted sensitive datasets and their corresponding keys are stored as data pairs in the customer service management system, with each encrypted sensitive dataset having its own public and private key.

[0047] Access the customer service management system according to the data management operation permission range, implement access control policies based on the encrypted sensitive dataset, monitor the customer service management system to conduct risk assessment, and generate a system risk level.

[0048] For data access requests within the data management operation permission range, the system will implement access control policies for specific operations or sensitive data based on permission settings to prevent unauthorized access. These access control policies refer to operations such as adding, deleting, modifying, and querying data. The system monitors the operational status, data access activity, and system logs of the customer service management system in real time. Based on the monitoring data, a risk assessment is conducted to analyze potential risks to the system, such as data leakage, unauthorized access, and malicious attacks. The system's risk level is determined based on the risk assessment results.

[0049] Furthermore, the method of accessing the customer service management system according to the data management operation permission range and implementing access control policies based on the encrypted sensitive dataset includes:

[0050] Based on the data management operation permission range, extract the first permission set, the second permission set, and the third permission set of the accessing user;

[0051] Access the customer service management system according to the first permission set to generate the first access dataset;

[0052] Access the customer service management system according to the second permission set to generate a second access dataset;

[0053] Access the customer service management system according to the third permission set to generate a third access dataset;

[0054] Construct an access control list based on the first access dataset, the first access dataset, and the first access dataset;

[0055] The access control list is traversed and matched with the encrypted sensitive dataset, and the sensitive data protection information is determined based on the matching results.

[0056] The access control policy is implemented based on the sensitive data protection information.

[0057] Extract the first, second, and third permission sets of accessing users from the data management operation permission range. Use the first permission set to access the customer service management system, obtain data related to the first permission set, and generate the first access dataset. Use the second permission set to access the customer service management system, obtain data related to the second permission set, and generate the second access dataset. Use the third permission set to access the customer service management system, obtain data related to the third permission set, and generate the third access dataset. Based on the first, second, and third access datasets, construct an access control list (ACCL). The ACCL records the data access scope and permission level corresponding to each permission set. Traverse the ACCL and match it with the encrypted sensitive dataset to check which access permissions involve sensitive data. Based on the matching results, determine the protection level, access restrictions, encryption requirements, and other protection information for the sensitive data. Develop an access control policy based on the sensitive data protection information. When implementing the access control policy in the customer service management system, only users with the corresponding permissions can decrypt and access this data. Simultaneously, record access logs for the sensitive data.

[0058] Furthermore, monitoring the customer service management system to conduct risk assessments and generate system risk levels can be achieved through methods including:

[0059] The access control policy described above is implemented in the customer service management system and monitored in real time to obtain access control monitoring logs.

[0060] Risk identification is performed based on the access control monitoring logs, and multiple risk record information is obtained.

[0061] A risk assessment matrix is ​​constructed based on the multiple risk record information;

[0062] The risk level of the system is determined by classifying the risk levels according to the risk assessment matrix.

[0063] The customer service management system implements real-time monitoring of access control policies, recording all access control-related operations and behaviors, and generating detailed monitoring logs. These logs include information such as access time, accessing user, access object, and operation type. In-depth analysis of these logs identifies potential anomalies or violations. By analyzing time patterns, user behavior patterns, and access frequency, potential security risks are discovered, yielding multiple risk record information entries. These entries include risk descriptions, occurrence times, and involved users. Based on the characteristics and business needs of the customer service management system, key indicators for risk assessment are determined, such as the frequency of risk occurrence, scope of impact, and potential losses. Each risk record is quantitatively scored according to these indicators, reflecting its severity and urgency. The quantitative scores are then entered into the corresponding cells of a risk assessment matrix. The horizontal axis represents the probability of a risk occurring, and the vertical axis represents the potential impact. Each cell represents a combination of the probability and impact of a specific risk. Based on the scores and risk level classification criteria in the risk assessment matrix, the system risk level of the customer service management system is determined, for example, categorized as high, medium, or low.

[0064] Construct a security protection network, perform anomaly detection and location based on the system risk level, extract anomaly detection data, synchronize the anomaly detection data to the security protection network, and output protection and control strategies.

[0065] In the customer service management system, anomaly detection and localization are performed based on the system risk level. Anomaly data, specifically abnormal orders within the system, is extracted. This data is then input into a constructed security protection network. The network, based on the anomaly data and the system risk level, formulates and outputs corresponding protection and control strategies, including strengthening access control, restricting specific user permissions, and activating emergency response mechanisms.

[0066] Furthermore, methods for building a secure protection network include:

[0067] Determine the detection target information based on the abnormal operation records of the customer service management system;

[0068] The anomaly detection subnetwork is trained using unsupervised learning based on the detection target information, and the deviation of the anomaly detection subnetwork output is obtained.

[0069] Based on the deviation, anomaly detection is performed on the real-time data stream of the customer service management system, and feedback is given according to the detection results, outputting the anomaly detection sub-network;

[0070] Extract business requirement information from the customer service management system, and divide and obtain multiple security zones according to the business requirement information and security risk information;

[0071] Based on the multiple security zones, multiple protection levels are determined through security hardening, and a protection level sub-network is constructed.

[0072] The anomaly detection subnetwork is connected to the protection level subnetwork to obtain the security protection network.

[0073] Anomaly logs are retrieved from the customer service management system. These logs record anomaly information, including anomaly type, frequency, and involved modules. Based on these logs, detection target information is determined, which refers to historical anomaly information from the customer service management system. An anomaly detection algorithm, such as the Isolation Forest algorithm, is selected to construct an anomaly detection subnetwork. Historical data from the customer service management system is used as the training set, and the subnetwork is trained according to the determined detection target information. After training, the subnetwork performs anomaly detection on the input data and outputs a deviation score. This deviation score represents the degree of deviation of the input data from the normal data pattern and can be used to determine the degree of data anomaly. Anomaly detection is performed on the real-time data stream, and anomaly levels are assigned according to the magnitude of the deviation score. The detection results reflect the training effect of the anomaly detection subnetwork. Based on the detection results, the anomaly detection subnetwork is adjusted and adjusted, ultimately outputting the final anomaly detection subnetwork. Business requirement information from the customer service management system is extracted and divided into multiple security zones based on business requirement information and security risk information. These security zones include the DMZ zone (containing publicly accessible server facilities) and the internal network zone. For each security zone, corresponding security hardening strategies are developed, including access control, data encryption, and security auditing. Different protection levels are determined based on the importance and potential risk level of each security zone, with varying levels of security measures applied accordingly. Based on the determined protection levels and security hardening strategies, a protection level subnetwork is constructed, enabling dynamic security protection and adjustments to the customer service management system according to different protection levels. The anomaly detection subnetwork is connected to the protection level subnetwork via communication, integrating them into a complete security protection network. This security protection network can monitor abnormal behavior of the customer service management system in real time and take appropriate security measures based on different protection levels.

[0074] Furthermore, based on the system risk level, anomaly detection and location are performed to extract detected anomaly data, which is then synchronized to the security protection network to output protection control strategies. The method includes:

[0075] The anomaly detection subnetwork performs anomaly detection based on the system risk level to locate abnormal behavior in the customer service management system.

[0076] Data is extracted based on the abnormal behavior location to determine the detected abnormal data, which includes abnormal time, abnormal order, and abnormal user.

[0077] Based on the abnormal time and the abnormal user, the abnormal order is analyzed to generate an abnormal data source;

[0078] Based on the abnormal data source, the detected abnormal data is synchronized to the protection level sub-network within the security protection network for data collaborative processing, and the protection level is determined according to the collaborative data;

[0079] The protection level is added to the protection control strategy for output.

[0080] The anomaly detection subnetwork performs targeted anomaly detection based on the previously determined system risk level. Within the customer service management system, this subnetwork monitors various behaviors and events in real time. Once an anomaly is detected, it immediately locates it, determining the specific location and scope of the anomaly. Based on the location results, the system extracts relevant data, including system logs, user operation records, and order information at the time of the anomaly, to identify the detected anomaly data. This anomaly data includes the anomaly time, the anomaly order, and the anomaly user. Combining the anomaly time and user information, a detailed analysis of the anomaly order is performed, generating an anomaly data source containing all anomaly information. The detected anomaly data is synchronized to the protection level subnetwork within the security protection network for collaborative data processing, establishing corresponding protection levels. Protection levels can be anomaly identifiers, alarms, or higher-level protection measures (automatic anomaly isolation, access restriction, etc.). The newly established protection levels are added to the existing protection control strategy, making the strategy more comprehensive and targeted.

[0081] The security assessment is performed by implementing the protection and control strategy, and the strategy is updated regularly based on the assessment results to provide intelligent security protection for the customer service management system.

[0082] Deploy the established protection and control strategies into the customer service management system to ensure the system operates in accordance with the strategy requirements. Conduct a security assessment of the protection and control strategies, optionally evaluating their actual effectiveness based on log information, performance data, and user feedback. Based on the security assessment results, identify existing security issues or potential risks in the system and adjust and optimize the protection and control strategies accordingly. Redeploy the adjusted protection and control strategies into the system to ensure the new strategies are effective and continue to provide security protection.

[0083] In summary, the embodiments of this application have at least the following technical effects:

[0084] First, an employee dataset is acquired, and permissions are assigned to it to generate employee operation permission sets, with a correspondence between employee operation permissions and the employee dataset. Then, user authentication is performed based on the employee operation permission sets, and the data management operation permission range for each user is determined according to the authentication results. Next, a sensitive dataset is acquired, encrypted, and stored in the customer service management system. Data access to the customer service management system is granted according to the data management operation permission ranges, and access control policies are implemented based on the encrypted sensitive dataset. The customer service management system is monitored for risk assessment, generating a system risk level. Simultaneously, a security protection network is constructed, and anomaly detection and extraction are performed based on the system risk level. Anomaly detection data is synchronized to the security protection network, and protection control policies are output. Finally, the protection control policies are executed for security assessment, and the protection control policies are regularly updated based on the assessment results, providing intelligent security protection for the customer service management system. This solves the technical problem of low security protection capabilities in existing customer service management systems, making it difficult to prevent network attacks, and achieves the technical effect of improving the security protection capabilities of customer service management systems. Example

[0085] Based on the same inventive concept as the security protection method for the customer service management system in the foregoing embodiments, as shown in FIG2, this application provides a security protection device for a customer service management system. The device and method embodiments in this application are based on the same inventive concept. The device includes:

[0086] The permission allocation module 11 is used to obtain an employee dataset, allocate permissions based on the employee dataset, and generate an employee operation permission set, wherein the employee operation permission set has a corresponding relationship with the employee dataset.

[0087] Verification module 12 is used to authenticate the accessing user based on the employee operation permission set, and determine the data management operation permission range of the accessing user based on the verification result;

[0088] Encryption processing module 13 is used to acquire sensitive datasets, encrypt them, and store the encrypted sensitive datasets in the customer service management system.

[0089] Risk assessment module 14 is used to access the customer service management system according to the data management operation permission range, implement access control policies based on the encrypted sensitive dataset, monitor the customer service management system to conduct risk assessment, and generate system risk level.

[0090] Protection and control module 15 is used to construct a security protection network, perform anomaly detection and location extraction based on the system risk level, synchronize the anomaly detection data to the security protection network, and output protection and control strategies.

[0091] The security protection module 16 is used to perform security assessments by executing the protection control strategy, and to periodically update the protection control strategy based on the assessment results, thereby providing intelligent security protection for the customer service management system.

[0092] Furthermore, the permission allocation module 11 is used to perform the following method:

[0093] Extract employee responsibility information and employee level information from the employee dataset;

[0094] Based on the employee responsibility information and the employee level information, a multi-level permission division is performed to generate a permission division result, which includes a first permission set, a second permission set, and a third permission set.

[0095] The employee dataset is evaluated periodically, and the first permission set, the second permission set, and the third permission set are adjusted according to the evaluation results to generate the employee operation permission set.

[0096] Furthermore, the encryption processing module 13 is used to perform the following method:

[0097] Determine data sensitivity based on the data business context and data usage.

[0098] Based on the aforementioned data sensitivity, a data traversal analysis is performed on the customer service management system to identify sensitive datasets;

[0099] The sensitive dataset is encrypted using a key with an asymmetric encryption algorithm to generate an encrypted sensitive dataset.

[0100] The key and the encrypted sensitive dataset are encrypted and stored in the customer service management system as data pairs.

[0101] Furthermore, the risk assessment module 14 is used to perform the following methods:

[0102] Based on the data management operation permission range, extract the first permission set, the second permission set, and the third permission set of the accessing user;

[0103] Access the customer service management system according to the first permission set to generate the first access dataset;

[0104] Access the customer service management system according to the second permission set to generate a second access dataset;

[0105] Access the customer service management system according to the third permission set to generate a third access dataset;

[0106] Construct an access control list based on the first access dataset, the first access dataset, and the first access dataset;

[0107] The access control list is traversed and matched with the encrypted sensitive dataset, and the sensitive data protection information is determined based on the matching results.

[0108] The access control policy is implemented based on the sensitive data protection information.

[0109] Furthermore, the risk assessment module 14 is used to perform the following methods:

[0110] The access control policy described above is implemented in the customer service management system and monitored in real time to obtain access control monitoring logs.

[0111] Risk identification is performed based on the access control monitoring logs, and multiple risk record information is obtained.

[0112] A risk assessment matrix is ​​constructed based on the multiple risk record information;

[0113] The risk level of the system is determined by classifying the risk levels according to the risk assessment matrix.

[0114] Furthermore, the protection control module 15 is used to perform the following methods:

[0115] Determine the detection target information based on the abnormal operation records of the customer service management system;

[0116] The anomaly detection subnetwork is trained using unsupervised learning based on the detection target information, and the deviation of the anomaly detection subnetwork output is obtained.

[0117] Based on the deviation, anomaly detection is performed on the real-time data stream of the customer service management system, and feedback is given according to the detection results, outputting the anomaly detection sub-network;

[0118] Extract business requirement information from the customer service management system, and divide and obtain multiple security zones according to the business requirement information and security risk information;

[0119] Based on the multiple security zones, multiple protection levels are determined through security hardening, and a protection level sub-network is constructed.

[0120] The anomaly detection subnetwork is connected to the protection level subnetwork to obtain the security protection network.

[0121] Furthermore, the protection control module 15 is used to perform the following methods:

[0122] The anomaly detection subnetwork performs anomaly detection based on the system risk level to locate abnormal behavior in the customer service management system.

[0123] Data is extracted based on the abnormal behavior location to determine the detected abnormal data, which includes abnormal time, abnormal order, and abnormal user.

[0124] Based on the abnormal time and the abnormal user, the abnormal order is analyzed to generate an abnormal data source;

[0125] Based on the abnormal data source, the detected abnormal data is synchronized to the protection level sub-network within the security protection network for data collaborative processing, and the protection level is determined according to the collaborative data;

[0126] The protection level is added to the protection control strategy for output.

[0127] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in a different order than that shown in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0128] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0129] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A security protection method for a customer service management system, characterized in that, The method includes: Obtain an employee dataset, allocate permissions based on the employee dataset, and generate an employee operation permission set, wherein the employee operation permission set has a corresponding relationship with the employee dataset; Based on the employee operation permission set, the access user is authenticated, and the data management operation permission range of the access user is determined according to the authentication result. The sensitive dataset is obtained, encrypted, and then stored in the customer service management system. Access the customer service management system according to the data management operation permission range, implement access control policies based on the encrypted sensitive dataset, monitor the customer service management system to conduct risk assessment, and generate a system risk level. Construct a security protection network, perform anomaly detection and location based on the system risk level, extract anomaly detection data, synchronize the anomaly detection data to the security protection network, and output protection and control strategies. The security assessment is performed by implementing the protection and control strategy, and the strategy is updated regularly based on the assessment results to provide intelligent security protection for the customer service management system.

2. The method as described in claim 1, characterized in that, The method includes obtaining an employee dataset, allocating permissions based on the employee dataset, and generating an employee operation permission set. Extract employee responsibility information and employee level information from the employee dataset; Based on the employee responsibility information and the employee level information, a multi-level permission division is performed to generate a permission division result, which includes a first permission set, a second permission set, and a third permission set. The employee dataset is evaluated periodically, and the first permission set, the second permission set, and the third permission set are adjusted according to the evaluation results to generate the employee operation permission set.

3. The method as described in claim 1, characterized in that, The method involves acquiring sensitive datasets, encrypting them, and then storing the encrypted sensitive datasets in the customer service management system. Determine data sensitivity based on the data business context and data usage. Based on the aforementioned data sensitivity, a data traversal analysis is performed on the customer service management system to identify sensitive datasets; The sensitive dataset is encrypted using a key with an asymmetric encryption algorithm to generate an encrypted sensitive dataset. The key and the encrypted sensitive dataset are encrypted and stored in the customer service management system as data pairs.

4. The method as described in claim 2, characterized in that, Access to the customer service management system is granted according to the data management operation permission range, and access control policies are implemented based on the encrypted sensitive dataset. The method includes: Based on the data management operation permission range, extract the first permission set, the second permission set, and the third permission set of the accessing user; Access the customer service management system according to the first permission set to generate the first access dataset; Access the customer service management system according to the second permission set to generate a second access dataset; Access the customer service management system according to the third permission set to generate a third access dataset; Construct an access control list based on the first access dataset, the first access dataset, and the first access dataset; The access control list is traversed and matched with the encrypted sensitive dataset, and the sensitive data protection information is determined based on the matching results. The access control policy is implemented based on the sensitive data protection information.

5. The method as described in claim 1, characterized in that, The customer service management system is monitored to conduct risk assessments and generate system risk levels. Methods include: The access control policy described above is implemented in the customer service management system and monitored in real time to obtain access control monitoring logs. Risk identification is performed based on the access control monitoring logs, and multiple risk record information is obtained. A risk assessment matrix is ​​constructed based on the multiple risk record information; The risk level of the system is determined by classifying the risk levels according to the risk assessment matrix.

6. The method as described in claim 1, characterized in that, Methods for building a secure network include: Determine the detection target information based on the operational anomaly records of the customer service management system; The anomaly detection subnetwork is trained using unsupervised learning based on the detection target information, and the deviation of the anomaly detection subnetwork output is obtained. Based on the deviation, anomaly detection is performed on the real-time data stream of the customer service management system, and feedback is given according to the detection results, outputting the anomaly detection sub-network; Extract business requirement information from the customer service management system, and divide and obtain multiple security zones according to the business requirement information and security risk information; Based on the multiple security zones, multiple protection levels are determined through security hardening, and a protection level sub-network is constructed. The anomaly detection subnetwork is connected to the protection level subnetwork to obtain the security protection network.

7. The method as described in claim 6, characterized in that, Based on the system risk level, anomaly detection and location are performed, and anomaly data is extracted. This anomaly data is then synchronized to the security protection network, and a protection control strategy is output. The method includes: The anomaly detection subnetwork performs anomaly detection based on the system risk level to locate abnormal behavior in the customer service management system. Data is extracted based on the abnormal behavior location to determine the detected abnormal data, which includes abnormal time, abnormal order, and abnormal user. Based on the abnormal time and the abnormal user, the abnormal order is analyzed to generate an abnormal data source; Based on the abnormal data source, the detected abnormal data is synchronized to the protection level sub-network within the security protection network for data collaborative processing, and the protection level is determined according to the collaborative data; The protection level is added to the protection control strategy for output.

8. A security protection device for a customer service management system, characterized in that, For implementing the security protection method for a customer service management system according to any one of claims 1-7, the apparatus comprises: The permission allocation module is used to obtain an employee dataset, allocate permissions based on the employee dataset, and generate an employee operation permission set, wherein the employee operation permission set has a corresponding relationship with the employee dataset. The verification module is used to authenticate the accessing user based on the employee operation permission set, and determine the data management operation permission range of the accessing user based on the verification result; An encryption processing module is used to acquire sensitive datasets, encrypt them, and store the encrypted sensitive datasets in the customer service management system. The risk assessment module is used to access the customer service management system according to the data management operation permission range, implement access control policies based on the encrypted sensitive dataset, monitor the customer service management system to conduct risk assessment, and generate a system risk level. The protection and control module is used to construct a security protection network, perform anomaly detection and location extraction based on the system risk level, synchronize the anomaly detection data to the security protection network, and output protection and control strategies. A security protection module is used to perform security assessments by executing the protection control strategy, and to periodically update the protection control strategy based on the assessment results, thereby providing intelligent security protection for the customer service management system.

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