Computer network security transaction optimization system

Abstract

The invention discloses a computer network security transaction optimization system, and belongs to the technical field of network transaction security. The system comprises an identity verification authorization module, a transaction request processing module, a security monitoring protection module, a transaction intelligent optimization module, a transaction auditing management module and a transaction report analysis module, protection is enhanced by analyzing a user behavior mode, additional verification is triggered when abnormality is detected, the risks of identity false use and fraud are reduced, and the safety of the transaction is improved. Network traffic is monitored in real time, potential attack behaviors are identified and blocked, through transaction request checking and dynamic request scheduling strict auditing, node loads are monitored in real time, transaction requests are intelligently scheduled, system overload or bottleneck is avoided, standby nodes are automatically started, stable operation under the high concurrency condition is guaranteed, and the system reliability is improved. The method enhances the adaptation to the increase of the transaction flow and the change of the network environment, improves the security, efficiency and transparency of the transaction through the transaction audit management and report analysis, and guarantees the stability and compliance of the financial transaction environment.

Description

Technical Field

[0001] The present invention relates to the technical field of network transaction security, and in particular to a computer network security transaction optimization system. Background Art

[0002] Although existing network security technologies and transaction optimization systems can prevent some common attacks and violations to a certain extent, most of them focus on one aspect, such as identity authentication or transaction data encryption, and lack a comprehensive integrated solution.

[0003] Moreover, as network attack methods continue to escalate, traditional protection mechanisms often lag behind and are unable to detect and respond to complex attack patterns in real time.

[0004] In addition, existing transaction optimization solutions often ignore intelligent scheduling and traffic management during the transaction process, and cannot guarantee the system's efficient processing capabilities when the transaction volume surges, which can easily cause transaction delays or system crashes. Summary of the invention

[0005] The purpose of the present invention is to provide a computer network security transaction optimization system to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a computer network security transaction optimization system, comprising: Authentication and authorization modules for: Verify the identities of both parties to the transaction through multiple authentication methods, generate digital certificates for successfully verified users, and authorize and manage the scope of transaction operations based on the user's authority level; Transaction request processing module, used to: Receive and process transaction requests from the user, collaborate with the identity authentication and authorization module, determine whether the transaction request is compliant based on the content and identity authority of the user's request, encrypt sensitive information in the transaction, and check the rationality of the transaction instruction through amount verification and account status verification; Security monitoring and protection module, used for: Monitor network traffic in real time during the transaction process and identify attack behaviors, analyze transaction behavior patterns and identify abnormal transaction requests, encrypt data transmission during the transaction process, and combine with the transaction request processing module to block malicious requests in real time; Trading intelligent optimization module, used for: According to the distribution of transaction traffic, it cooperates with the transaction request processing module to dynamically adjust the processing nodes of transaction requests and the transaction data transmission path, and automatically executes transaction rules based on transaction logic; Transaction audit management module, used for: Audit all transaction processes and record transaction information, identify and mark suspicious transactions; Transaction report analysis module for: Transaction data is counted and displayed through charts, risk assessment is performed on transaction data, and transaction reports are generated in collaboration with the transaction audit management module. The transaction reports include all transaction records, risk assessments, and abnormal behavior analysis.

[0007] Furthermore, the identity authentication and authorization module includes: Multi-factor authentication unit for: When a user initiates a transaction, the user's identity is verified through multiple authentication methods, including password, dynamic token, and facial recognition. Analyze the user's historical behavior patterns during the multi-factor authentication process, including typing speed and transaction habits, and trigger additional authentication when abnormal behavior is detected, including requiring the input of additional security question answers; If both the multi-factor authentication and the additional authentication steps are passed, the identity verification is considered successful; After verification, a digital certificate is generated according to the user's authority level, and authority authorization management is performed; The permission authorization management unit is used to: Based on the user's identity authentication results and preset permission policies, the user's transaction permissions are dynamically allocated and a digital certificate is generated. When the user initiates a transaction request, the user's permissions are checked.

[0008] Furthermore, the transaction request processing module includes: The transaction request checking unit is used to: Receive a transaction request from a user, extract key information from the transaction request, including transaction amount, transaction type, transaction account, and payee information, and perform compliance checks on the request content; Check the status of the account initiating the transaction to ensure that the account is active and has no abnormal conditions such as freezing or restrictions; According to the preset transaction limit rules, the system verifies the transaction amount; Verify whether the transaction request meets compliance requirements based on preset transaction rules and laws and regulations; If the transaction request meets all the verification rule checks, the transaction request will be marked as a legal request and continue to be processed. Otherwise, the transaction will be rejected and an error message will be fed back; Information encryption protection unit, used for: Identify and mark all sensitive information in the transaction request as data to be encrypted, including account information, transaction amount, and user identity; Encrypt the data to be encrypted using a combination of symmetric encryption and asymmetric encryption; During the transaction process, the encrypted data is checked for integrity.

[0009] Furthermore, the security monitoring and protection module includes: Network monitoring and identification unit, used for: By monitoring network traffic in real time, capturing data packets in transaction requests, and analyzing the source, destination, size, frequency, and protocol characteristics of the data packets, the system can identify and detect potential attack behaviors by analyzing the source IP address, request frequency, and pattern of network traffic. When the system detects potential attack behaviors, it triggers the protection mechanism and temporarily restricts and intercepts requests from the attack source IP. Transaction Behavior Analysis Unit, used to: By analyzing the user's historical transaction data, a behavior model for each user is established, wherein the behavior model includes transaction amount, transaction frequency, transaction time, transaction type, and characteristics of the payee, and the user's normal transaction behavior pattern is extracted based on the behavior model; When a user initiates a transaction, the current transaction behavior characteristics are analyzed in real time and compared with the user's normal transaction behavior pattern; If the current transaction behavior characteristics are significantly different from the user's normal transaction behavior pattern, the current transaction will be marked as an abnormal transaction. The significant differences include abnormally large transactions, frequent small transactions, and transaction times that are inconsistent with the user's normal transaction behavior pattern.

[0010] Furthermore, the security monitoring and protection module further includes: Anomaly detection unit, used to: When the transaction behavior analysis unit detects abnormal transaction behavior, a protection mechanism is automatically triggered, which includes limiting the transaction amount, requiring users to perform additional identity verification, freezing accounts, and suspending transactions; At the same time, an alarm message is sent to the security administrator; Record abnormal transaction data marked as abnormal transactions and send them to the transaction audit management module.

[0011] Furthermore, the transaction intelligent optimization module includes: The transaction request scheduling unit is used to: Monitor the workload data and current transaction flow data of each processing node in real time, and collect the response time, processing capacity, and resource usage information of each node; When a new transaction request arrives, it distributes the transaction request among multiple available nodes based on the current transaction flow data. When it is detected that the load of the processing node exceeds the set threshold, the new transaction request is automatically allocated to the node with low load; When the volume of transaction requests increases and the network condition becomes unstable, backup processing nodes are automatically enabled and node configurations are dynamically adjusted.

[0012] Furthermore, the node resource abnormality monitoring module is used to: Real-time monitoring of node resource occupancy information corresponding to each unit time, wherein the node resource occupancy information includes CPU occupancy, memory occupancy and communication bandwidth occupancy; According to the CPU occupancy rate, memory occupancy rate and communication bandwidth occupancy rate corresponding to each unit time, the change degree coefficients corresponding to the CPU occupancy rate, the memory occupancy rate and the communication bandwidth occupancy rate are obtained; The coefficients of variation of the CPU occupancy, memory occupancy, and communication bandwidth occupancy are obtained by the following formula:

[0013] Where P represents the coefficient of variation of CPU occupancy, memory occupancy and communication bandwidth occupancy; n represents the number of unit time experienced by the processing node, and the unit time is 1s; X i represents the value of CPU occupancy, memory occupancy and communication bandwidth occupancy corresponding to the i-th unit time; X maxi represents the maximum value of CPU occupancy, memory occupancy and communication bandwidth occupancy at the i-th unit time; X bi represents the standard deviation of the CPU occupancy rate, memory occupancy rate, and communication bandwidth occupancy rate corresponding to the i-th unit time; X maxbi It represents the standard deviation of the maximum values ​​of CPU usage, memory usage and communication bandwidth usage that occur in the i-th unit time; Compare the change degree coefficients corresponding to the CPU occupancy rate, memory occupancy rate and communication bandwidth occupancy rate with their corresponding preset change degree coefficient thresholds respectively; When any one of the variation degree coefficients corresponding to the CPU occupancy rate, memory occupancy rate and communication bandwidth occupancy rate exceeds its corresponding preset variation degree coefficient threshold, the CPU occupancy rate, memory occupancy rate and communication bandwidth occupancy rate are used to determine whether there is resource utilization abnormality in the processing node.

[0014] Further, the use of CPU occupancy, memory occupancy, and communication bandwidth occupancy to determine whether there is resource utilization abnormality in the processing node includes: When any one of the variation coefficients corresponding to the CPU occupancy rate, the memory occupancy rate and the communication bandwidth occupancy rate exceeds the corresponding preset variation coefficient threshold, the CPU occupancy rate, the memory occupancy rate and the communication bandwidth occupancy rate corresponding to each unit time are retrieved; The resource anomaly determination coefficient is obtained by using the CPU occupancy rate, memory occupancy rate and communication bandwidth occupancy rate corresponding to each unit time; The resource anomaly determination coefficient is obtained by the following formula:

[0015] Where Z represents the resource anomaly determination coefficient; n represents the number of unit times experienced by the processing node, and the unit time is 1s; X ci Indicates the CPU occupancy rate corresponding to the i-th unit time; X ni represents the memory usage corresponding to the i-th unit time; X ti represents the communication bandwidth occupancy rate corresponding to the i-th unit time; X cfi Indicates the maximum change of CPU usage corresponding to the i-th unit time; X nfi Indicates the maximum change of memory usage rate corresponding to the i-th unit time; X tfi represents the maximum change amplitude of the communication bandwidth occupancy rate corresponding to the i-th unit time; T ci represents the time interval between the CPU usage rate corresponding to the i-th unit time and the maximum CPU usage rate; T ni represents the time interval between the memory usage rate corresponding to the i-th unit time and the maximum memory usage rate; T ti represents the time interval between the communication bandwidth occupancy rate corresponding to the i-th unit time and the maximum communication bandwidth occupancy rate; P ci , P ni and P ti Respectively represent the coefficient of change of CPU occupancy rate, memory occupancy rate and communication bandwidth occupancy rate of the i-th unit time Comparing the resource anomaly determination coefficient with a preset determination coefficient; When the resource anomaly determination coefficient exceeds a preset determination coefficient, it is determined that the node is in a resource utilization anomaly state, and a resource utilization anomaly alarm is issued.

[0016] Furthermore, the transaction intelligent optimization module includes: The transaction path adjustment unit is used to: When receiving a transaction request, the transmission requirements of the transaction data are evaluated based on the transaction type, amount, and location of the two parties. For sensitive transactions, a highly secure transmission path is selected. For normal transactions, the transmission path is optimized based on the latency requirements. For critical and high-risk transactions, data is transmitted simultaneously through multiple secure paths. Monitor the health status and transmission quality of network links in real time to determine whether the current network is congested, bandwidth limited, or subject to malicious attack risks. Automatically switch transmission paths when the quality of the transmission path degrades or is attacked.

[0017] Furthermore, the transaction audit management module includes: Data logging storage unit for: Record and store key transaction information during the transaction process, including transaction time, transaction amount, identities of both parties to the transaction, transaction status, transaction type, and transaction account; Transaction behavior audit unit, used to: Establish a transaction behavior audit rule base based on industry regulations, internal organizational policies, and historical transaction data. The transaction behavior audit rule base includes rules for abnormal transaction amounts, large transaction frequencies, transaction times that are inconsistent with habits, and transaction pattern mutations; Audit transactions based on the set rules in the transaction behavior audit rule base. If the transaction behavior violates the preset rules, the transaction will be marked as an abnormal transaction. When an abnormal transaction is identified, the current transaction is marked as a suspicious transaction, and the suspicious transaction information of the suspicious transaction is archived. The suspicious transaction information includes the transaction time, amount, accounts involved, and abnormal behavior characteristics.

[0018] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention establishes a multi-level security protection system through the close cooperation of the identity authentication authorization module and the security monitoring and protection module, which greatly improves the identity authentication and defense capabilities in the transaction process, ensures the authenticity and legitimacy of the identities of both parties to the transaction through a variety of identity authentication methods, and automatically triggers additional security verification by analyzing the user's historical behavior patterns when abnormal behavior is detected, reducing the risk of illegal intrusion, monitoring transaction network traffic in real time, identifying potential attack behaviors through in-depth analysis of data packets in transaction requests, and taking immediate response measures when abnormalities are found. Through a multi-dimensional security protection system, it effectively prevents security threats such as identity impersonation, fraud, and network attacks, and protects the asset security of both parties to the transaction.

[0019] 2. The present invention ensures that each transaction complies with compliance requirements by strictly checking the content, amount, account status, etc. of transaction requests, thereby minimizing the occurrence of erroneous transactions and illegal transactions. By encrypting and protecting sensitive information, the system ensures the security of transactions while protecting the privacy of users. Through the transaction request scheduling unit, the system monitors the load of each processing node in real time, and intelligently distributes transaction requests to idle nodes according to changes in transaction traffic, thereby avoiding the generation of system bottlenecks and improving the speed and stability of transaction processing. When the transaction request volume increases significantly or the network environment becomes unstable, the backup node is automatically enabled and the transaction path is dynamically adjusted to ensure efficient completion of transactions, effectively improving the flexibility and response capabilities of the system, and is particularly suitable for operations in environments with increased financial transaction volume or complex network environments.

[0020] 3. The present invention records all key transaction information and establishes a transaction behavior audit rule base based on industry regulations and corporate policies to monitor and review transaction behaviors in real time. Any transaction that violates the audit rules will be marked as a suspicious transaction, and the suspicious information will be automatically archived for further review and analysis. By summarizing and statistically analyzing all transaction data, a detailed risk assessment report is generated to help financial institutions, regulatory authorities or corporate managers gain an in-depth understanding of the risks and potential threats in the transaction process, enhance the monitoring of improper transaction behaviors, and provide strong support for compliance inspections, ensuring the legality and fairness of the transaction environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a module schematic diagram of the computer network security transaction optimization system of the present invention. DETAILED DESCRIPTION

[0022] 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.

[0023] See also Figure 1 , the present invention provides the following technical solutions: A computer network security transaction optimization system, comprising: Authentication and authorization modules for: Verify the identities of both parties to the transaction through multiple authentication methods, generate digital certificates for successfully verified users, and authorize and manage the scope of transaction operations based on the user's authority level; Transaction request processing module, used to: Receive and process transaction requests from the user, collaborate with the identity authentication and authorization module, determine whether the transaction request is compliant based on the content and identity authority of the user's request, encrypt sensitive information in the transaction, and check the rationality of the transaction instruction through amount verification and account status verification; Security monitoring and protection module, used for: Monitor network traffic in real time during the transaction process and identify attack behaviors, analyze transaction behavior patterns and identify abnormal transaction requests, encrypt data transmission during the transaction process, and combine with the transaction request processing module to block malicious requests in real time; Trading intelligent optimization module, used for: According to the distribution of transaction traffic, it cooperates with the transaction request processing module to dynamically adjust the processing nodes of transaction requests and the transaction data transmission path, and automatically executes transaction rules based on transaction logic; Transaction audit management module, used for: Audit all transaction processes and record transaction information, identify and mark suspicious transactions; Transaction report analysis module for: Transaction data is counted and displayed through charts, risk assessment is performed on transaction data, and transaction reports are generated in collaboration with the transaction audit management module. The transaction reports include all transaction records, risk assessments, and abnormal behavior analysis.

[0024] In the above embodiment, multi-level security verification of transactions is performed through the identity authentication authorization module and the security monitoring and protection module to avoid security risks such as identity impersonation, fraud, and malicious attacks. Sensitive data is encrypted during the transaction to ensure the confidentiality and integrity of the transaction data. The processing nodes and data transmission paths are dynamically adjusted to effectively allocate resources in a high-concurrency environment to ensure the efficiency and stability of transactions. Through intelligent scheduling and path adjustment, the transaction process and system response time are optimized, and the overall transaction performance is improved.

[0025] In the above embodiment, by real-time analysis of transaction behavior and network traffic, abnormal transactions can be discovered in a timely manner, protection mechanisms can be triggered, and potential risks can be reduced. By accurately identifying risky behaviors in transactions, it is ensured that the system can quickly respond to and prevent financial fraud, money laundering and other behaviors. Traceable records of all transaction processes are provided, and detailed transaction data reports are provided to facilitate auditors to conduct risk assessments and compliance inspections, and provide strong evidence for subsequent accountability.

[0026] Authentication and authorization modules, including: Multi-factor authentication unit for: When a user initiates a transaction, the user's identity is verified through multiple authentication methods, including password, dynamic token, and facial recognition. Analyze the user's historical behavior patterns during the multi-factor authentication process, including typing speed and transaction habits, and trigger additional authentication when abnormal behavior is detected, including requiring the input of additional security question answers; If both the multi-factor authentication and the additional authentication steps are passed, the identity verification is considered successful; After verification, a digital certificate is generated according to the user's authority level, and authority authorization management is performed; The permission authorization management unit is used to: Based on the user's identity authentication results and preset permission policies, the user's transaction permissions are dynamically allocated and a digital certificate is generated. When the user initiates a transaction request, the user's permissions are checked.

[0027] In the above embodiment, through the multiple authentication units, the system can increase the security of identity authentication and prevent identity fraud and theft through multiple authentication methods such as passwords, dynamic tokens and facial recognition. Behavioral pattern analysis further enhances the accuracy and intelligence of identity authentication, especially when identifying abnormal behavior, it can trigger additional verification measures in time, greatly improving the system's ability to prevent complex attacks and abnormal behaviors, dynamically adjust the scope of transaction operations according to the user's authority level, avoid unauthorized behavior and abuse of authority, and through real-time verification of the user's identity authentication results and authority settings, the system ensures that only authorized users can perform specific transaction operations, effectively preventing internal personnel or external attackers from abusing authority to conduct illegal transactions.

[0028] Transaction request processing module, including: The transaction request checking unit is used to: Receive a transaction request from a user, extract key information from the transaction request, including transaction amount, transaction type, transaction account, and payee information, and perform compliance checks on the request content; Check the status of the account initiating the transaction to ensure that the account is active and has no abnormal conditions such as freezing or restrictions; According to the preset transaction limit rules, the system verifies the transaction amount; Verify whether the transaction request meets compliance requirements based on preset transaction rules and laws and regulations; If the transaction request meets all the verification rule checks, the transaction request will be marked as a legal request and continue to be processed. Otherwise, the transaction will be rejected and an error message will be fed back; Information encryption protection unit, used for: Identify and mark all sensitive information in the transaction request as data to be encrypted, including account information, transaction amount, and user identity; Encrypt the data to be encrypted using a combination of symmetric encryption and asymmetric encryption; During the transaction process, the encrypted data is checked for integrity.

[0029] In the above embodiment, the transaction request checking unit is used to check the legality and compliance of key information of the transaction to ensure that each transaction complies with regulatory requirements and preset transaction rules, automatically verify whether the transaction amount complies with the user's transaction limit rules, prevent the occurrence of abnormally large transactions, and effectively prevent illegal transactions of frozen or restricted accounts. The sensitive data in the transaction request is strictly encrypted, and a combination of symmetric encryption and asymmetric encryption is used to ensure that the transaction data is not intercepted, tampered with or leaked during transmission. At the same time, the integrity of the data is checked during the transaction process to further ensure the reliability of the transaction, effectively reduce the transaction risks caused by human errors or malicious attacks, ensure the security of transaction data and the compliance of the transaction process, and improve the user's trust in the system.

[0030] Security monitoring and protection module, including: Network monitoring and identification unit, used for: By monitoring network traffic in real time, capturing data packets in transaction requests, and analyzing the source, destination, size, frequency, and protocol characteristics of the data packets, the system can identify and detect potential attack behaviors by analyzing the source IP address, request frequency, and pattern of network traffic. When the system detects potential attack behaviors, it triggers the protection mechanism and temporarily restricts and intercepts requests from the attack source IP. Transaction Behavior Analysis Unit, used to: By analyzing the user's historical transaction data, a behavior model for each user is established, wherein the behavior model includes transaction amount, transaction frequency, transaction time, transaction type, and characteristics of the payee, and the user's normal transaction behavior pattern is extracted based on the behavior model; When a user initiates a transaction, the current transaction behavior characteristics are analyzed in real time and compared with the user's normal transaction behavior pattern; If the current transaction behavior characteristics are significantly different from the user's normal transaction behavior pattern, the current transaction will be marked as an abnormal transaction. The significant differences include abnormally large transactions, frequent small transactions, and transaction times that are inconsistent with the user's normal transaction behavior pattern; Anomaly detection unit, used to: When the transaction behavior analysis unit detects abnormal transaction behavior, a protection mechanism is automatically triggered, which includes limiting the transaction amount, requiring users to perform additional identity verification, freezing accounts, and suspending transactions; At the same time, an alarm message is sent to the security administrator; Record abnormal transaction data marked as abnormal transactions and send them to the transaction audit management module.

[0031] In the above embodiment, through the network security monitoring and real-time protection functions, various attack behaviors can be identified and responded to. By analyzing the network traffic, the source and target of the data packet, the frequency and other characteristics, potential attack behaviors can be detected in real time, and by analyzing the traffic pattern, the possible attack source can be identified, and unsafe requests can be intercepted and restricted in time, effectively preventing the impact of network attacks such as DoS attacks and DDoS attacks. By analyzing the user's historical transaction data and establishing a behavior model, the user's normal transaction pattern can be accurately identified, and abnormal transactions can be discovered in time. When the user's transaction behavior is abnormal, the system automatically marks the transaction as an abnormal transaction, triggering a protection mechanism, reducing the risk of fraud, money laundering and other illegal transactions. When the system detects abnormal behavior, it can trigger restrictive measures in real time, such as freezing accounts, suspending transactions, etc., and report abnormal transaction information to the security administrator in time. Through multi-level security protection measures, the transaction system's anti-attack capability is effectively improved and the risk of financial fraud is reduced.

[0032] Transaction intelligent optimization module, including: The transaction request scheduling unit is used to: Monitor the workload data and current transaction flow data of each processing node in real time, and collect the response time, processing capacity, and resource usage information of each node; When a new transaction request arrives, it distributes the transaction request among multiple available nodes based on the current transaction flow data. When it is detected that the load of the processing node exceeds the set threshold, the new transaction request is automatically allocated to the node with low load; When the transaction request volume increases and the network condition is unstable, the backup processing nodes are automatically enabled and the node configuration is dynamically adjusted; The transaction path adjustment unit is used to: When receiving a transaction request, the transmission requirements of the transaction data are evaluated based on the transaction type, amount, and location of the two parties. For sensitive transactions, a highly secure transmission path is selected. For normal transactions, the transmission path is optimized based on the latency requirements. For critical and high-risk transactions, data is transmitted simultaneously through multiple secure paths. Monitor the health status and transmission quality of network links in real time to determine whether the current network is congested, bandwidth limited, or subject to malicious attack risks. Automatically switch transmission paths when the quality of the transmission path degrades or is attacked.

[0033] In the above embodiments, the transaction processing efficiency and system resource allocation are optimized by dynamically adjusting the transaction flow, processing node load and transmission path. By real-time monitoring the workload of each processing node, transaction requests can be intelligently allocated to nodes with lower loads, avoiding transaction delays and system crashes due to node overload. When the transaction request volume surges, the system can automatically enable backup nodes to ensure that transaction requests are efficiently processed. According to the type, amount and risk level of the transaction, the appropriate transmission path is dynamically selected. For sensitive transactions, high-security transmission channels are given priority to ensure data security. For normal transactions, path optimization is performed according to delay requirements to ensure transaction efficiency. If the transmission path is attacked or the quality is degraded, the system can quickly switch the path to ensure reliable data transmission. By intelligently optimizing transaction flow and resources, the transaction processing efficiency and the security of transaction data transmission are improved.

[0034] Specifically, the node resource abnormality monitoring module is used to: Real-time monitoring of node resource occupancy information corresponding to each unit time, wherein the node resource occupancy information includes CPU occupancy, memory occupancy and communication bandwidth occupancy; According to the CPU occupancy rate, memory occupancy rate and communication bandwidth occupancy rate corresponding to each unit time, the change degree coefficients corresponding to the CPU occupancy rate, the memory occupancy rate and the communication bandwidth occupancy rate are obtained; The coefficients of variation of the CPU occupancy, memory occupancy, and communication bandwidth occupancy are obtained by the following formula:

[0035] Where P represents the coefficient of variation of CPU occupancy, memory occupancy and communication bandwidth occupancy; n represents the number of unit time experienced by the processing node, and the unit time is 1s; X i represents the value of CPU occupancy, memory occupancy and communication bandwidth occupancy corresponding to the i-th unit time; X maxi represents the maximum value of CPU occupancy, memory occupancy and communication bandwidth occupancy at the i-th unit time; X bi represents the standard deviation of the CPU occupancy rate, memory occupancy rate, and communication bandwidth occupancy rate corresponding to the i-th unit time; X maxbi It represents the standard deviation of the maximum values ​​of CPU usage, memory usage and communication bandwidth usage that occur in the i-th unit time; Compare the change degree coefficients corresponding to the CPU occupancy rate, memory occupancy rate and communication bandwidth occupancy rate with their corresponding preset change degree coefficient thresholds respectively; When any one of the variation degree coefficients corresponding to the CPU occupancy rate, memory occupancy rate and communication bandwidth occupancy rate exceeds its corresponding preset variation degree coefficient threshold, the CPU occupancy rate, memory occupancy rate and communication bandwidth occupancy rate are used to determine whether there is resource utilization abnormality in the processing node.

[0036] The technical effect of the above technical solution is: by real-time monitoring of node resource occupancy information (CPU occupancy, memory occupancy, communication bandwidth occupancy) per unit time (such as per second), the system can quickly capture the dynamic changes in resource usage. This real-time monitoring mechanism helps to timely discover and deal with potential resource utilization problems and ensure the stable operation of the system or application. By introducing the degree of change coefficient P, the solution can quantify the changes in CPU occupancy, memory occupancy and communication bandwidth occupancy in different unit times. This coefficient not only takes into account the absolute value of resource occupancy (such as Xi and Xmaxi), but also incorporates the volatility of the value (such as Xbi and Xmaxbi), thereby providing a more comprehensive and accurate assessment of the trend of resource utilization changes. By comparing the calculated degree of change coefficient with the preset threshold, the solution can intelligently determine whether there is a resource utilization anomaly in the processing node. When the degree of change coefficient of any resource exceeds its corresponding threshold, the system can trigger an alarm or take other countermeasures, thereby effectively avoiding problems such as resource overload and performance degradation. By real-time monitoring of resource occupancy and intelligent detection of anomalies, the solution helps to timely discover and deal with potential system bottlenecks or failure points. This not only improves the stability and reliability of the system, but also reduces the risk of system crashes or data loss due to improper resource utilization. In the long run, this solution also helps optimize resource allocation and scheduling. By analyzing historical resource usage data, the system can more accurately predict future resource needs, thereby reasonably allocating resources, improving resource utilization, and reducing operating costs.

[0037] In summary, this technical solution effectively improves the stability, reliability and resource utilization efficiency of the system through real-time monitoring, precise evaluation, intelligent anomaly detection and other means, providing strong support for building high-performance and high-availability information systems.

[0038] Specifically, the use of CPU occupancy, memory occupancy, and communication bandwidth occupancy to determine whether a processing node has resource utilization abnormality includes: When any one of the variation coefficients corresponding to the CPU occupancy rate, the memory occupancy rate and the communication bandwidth occupancy rate exceeds the corresponding preset variation coefficient threshold, the CPU occupancy rate, the memory occupancy rate and the communication bandwidth occupancy rate corresponding to each unit time are retrieved; The resource anomaly determination coefficient is obtained by using the CPU occupancy rate, memory occupancy rate and communication bandwidth occupancy rate corresponding to each unit time; The resource anomaly determination coefficient is obtained by the following formula:

[0039] Where Z represents the resource anomaly determination coefficient; n represents the number of unit times experienced by the processing node, and the unit time is 1s; X ci Indicates the CPU occupancy rate corresponding to the i-th unit time; X ni represents the memory usage corresponding to the i-th unit time; X ti represents the communication bandwidth occupancy rate corresponding to the i-th unit time; X cfi Indicates the maximum change of CPU usage corresponding to the i-th unit time; X nfi Indicates the maximum change of memory usage rate corresponding to the i-th unit time; X tfi represents the maximum change amplitude of the communication bandwidth occupancy rate corresponding to the i-th unit time; T ci represents the time interval between the CPU usage rate corresponding to the i-th unit time and the maximum CPU usage rate; T ni represents the time interval between the memory usage rate corresponding to the i-th unit time and the maximum memory usage rate; T ti represents the time interval between the communication bandwidth occupancy rate corresponding to the i-th unit time and the maximum communication bandwidth occupancy rate; P ci , P ni and P ti Respectively represent the coefficient of change of CPU occupancy rate, memory occupancy rate and communication bandwidth occupancy rate of the i-th unit time Comparing the resource anomaly determination coefficient with a preset determination coefficient; When the resource anomaly determination coefficient exceeds a preset determination coefficient, it is determined that the node is in a resource utilization anomaly state, and a resource utilization anomaly alarm is issued.

[0040] The technical effect of the above technical solution is: the solution comprehensively evaluates the resource utilization status of the processing node by introducing the resource anomaly determination coefficient Z by comprehensively considering the degree of change of CPU occupancy, memory occupancy and communication bandwidth occupancy, as well as the time interval between them and their respective maximum values. This comprehensive determination method can more accurately reflect the overall resource utilization of the node than a single indicator, and helps to timely discover potential resource utilization anomalies. By calculating the maximum value of the resource occupancy and its change amplitude in each unit time, and combining the time interval between the maximum value, the solution can more accurately capture the abnormal fluctuation of resource utilization. This meticulous analysis method reduces the possibility of false alarms and missed alarms, and improves the accuracy of anomaly detection. Once the resource anomaly determination coefficient Z exceeds the preset determination coefficient, the system can immediately trigger the alarm mechanism and notify relevant personnel to handle it. This real-time response capability helps to quickly resolve resource utilization anomalies, prevent the problem from further deteriorating, and ensure the stability and reliability of the system. Through real-time monitoring and anomaly detection, the solution provides strong data support for resource management and scheduling. The system can dynamically adjust resource configuration according to resource utilization, optimize resource utilization, reduce operating costs, and improve system performance. The solution reduces the workload of operation and maintenance personnel and improves system maintainability by automatically detecting resource utilization anomalies. Operation and maintenance personnel can focus more on handling alarm events without having to frequently manually check the system status.

[0041] In summary, this technical solution provides a comprehensive and effective solution for resource utilization management of processing nodes by comprehensively determining resource utilization status, improving the accuracy of anomaly detection, realizing real-time response and alarm mechanism, optimizing resource management and scheduling, and enhancing system maintainability. This not only helps to improve the stability and reliability of the system, but also optimizes resource utilization, reduces operating costs, and improves overall system performance.

[0042] Transaction audit management module, including: Data logging storage unit for: Record and store key transaction information during the transaction, including transaction time, transaction amount, identities of both parties to the transaction, transaction status, transaction type, and transaction account; Transaction behavior audit unit, used to: Establish a transaction behavior audit rule base based on industry regulations, internal organizational policies, and historical transaction data. The transaction behavior audit rule base includes rules for abnormal transaction amounts, large transaction frequencies, transaction times that are inconsistent with habits, and transaction pattern mutations; Audit transactions based on the set rules in the transaction behavior audit rule base. If the transaction behavior violates the preset rules, the transaction will be marked as an abnormal transaction. When an abnormal transaction is identified, the current transaction is marked as a suspicious transaction, and the suspicious transaction information of the suspicious transaction is archived. The suspicious transaction information includes the transaction time, amount, accounts involved, and abnormal behavior characteristics.

[0043] In the above embodiment, traceable transaction audits are performed through the transaction audit management module to ensure the legality and compliance of each transaction. All transaction data are recorded in detail and stored in a secure database to ensure the integrity, non-tamperability and long-term preservation of transaction records, which is convenient for future audits and investigations. By establishing a transaction behavior rule library, transaction behaviors are reviewed in real time, and abnormal transactions can be identified and marked in a timely manner. Transactions that violate regulations are automatically marked as suspicious transactions and archived for subsequent tracking and investigations. Through flexible audit rules, the supervision and monitoring capabilities of transaction behaviors are effectively improved, providing a strong compliance guarantee for the system, and providing accurate data support for financial supervision and risk assessment.

[0044] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A computer network security transaction optimization system, characterized in that: include: Authentication and authorization modules for: Verify the identities of both parties to the transaction through multiple authentication methods, generate digital certificates for successfully verified users, and authorize and manage the scope of transaction operations based on the user's authority level; Transaction request processing module, used to: Receive and process transaction requests from the user, collaborate with the identity authentication and authorization module, determine whether the transaction request is compliant based on the content and identity authority of the user's request, encrypt sensitive information in the transaction, and check the rationality of the transaction instruction through amount verification and account status verification; Security monitoring and protection module, used for: Monitor network traffic in real time during the transaction process and identify attack behaviors, analyze transaction behavior patterns and identify abnormal transaction requests, encrypt data transmission during the transaction process, and combine with the transaction request processing module to block malicious requests in real time; Transaction intelligent optimization module, used for: According to the distribution of transaction traffic, it cooperates with the transaction request processing module to dynamically adjust the processing nodes of transaction requests and the transaction data transmission path, and automatically executes transaction rules based on transaction logic; Transaction audit management module, used for: Audit all transaction processes and record transaction information, identify and mark suspicious transactions; Transaction report analysis module for: Transaction data is counted and displayed through charts, risk assessment is performed on transaction data, and transaction reports are generated in collaboration with the transaction audit management module. The transaction reports include all transaction records, risk assessments, and abnormal behavior analysis.

2. A computer network security transaction optimization system as claimed in claim 1, characterized in that: The identity authentication and authorization module comprises: Multi-factor authentication unit for: When a user initiates a transaction, the user's identity is verified through multiple authentication methods, including password, dynamic token, and facial recognition. Analyze the user's historical behavior patterns during the multi-factor authentication process, including typing speed and transaction habits, and trigger additional authentication when abnormal behavior is detected, including requiring the input of additional security question answers; If both the multi-factor authentication and the additional authentication steps are passed, the identity verification is considered successful; After verification, a digital certificate is generated according to the user's authority level, and authority authorization management is performed; The permission authorization management unit is used to: Based on the user's identity authentication results and preset permission policies, the user's transaction permissions are dynamically allocated and a digital certificate is generated. When the user initiates a transaction request, the user's permissions are checked.

3. A computer network security transaction optimization system as claimed in claim 1, characterized in that: The transaction request processing module includes: The transaction request checking unit is used to: Receive a transaction request from a user, extract key information from the transaction request, including transaction amount, transaction type, transaction account, and payee information, and perform compliance checks on the request content; Check the status of the account initiating the transaction to ensure that the account is active and has no abnormal freezing or restrictions; Verify the transaction amount according to the preset transaction limit rules; Verify whether the transaction request meets compliance requirements based on preset transaction rules and laws and regulations; If the transaction request meets all the verification rule checks, the transaction request will be marked as a legal request and continue to be processed. Otherwise, the transaction will be rejected and an error message will be fed back; Information encryption protection unit, used for: Identify and mark all sensitive information in the transaction request as data to be encrypted, including account information, transaction amount, and user identity; Encrypt the data to be encrypted using a combination of symmetric encryption and asymmetric encryption; During the transaction process, the encrypted data is checked for integrity.

4. A computer network security transaction optimization system as claimed in claim 1, characterized in that: The security monitoring and protection module includes: Network monitoring and identification unit, used for: By monitoring network traffic in real time, capturing data packets in transaction requests, and analyzing the source, destination, size, frequency, and protocol characteristics of the data packets, the system can identify and detect potential attack behaviors by analyzing the source IP address, request frequency, and pattern of network traffic. When the system detects potential attack behaviors, it triggers the protection mechanism and temporarily restricts and intercepts requests from the attack source IP. Transaction Behavior Analysis Unit, used to: By analyzing the user's historical transaction data, a behavior model for each user is established, wherein the behavior model includes transaction amount, transaction frequency, transaction time, transaction type, and characteristics of the payee, and the user's normal transaction behavior pattern is extracted based on the behavior model; When a user initiates a transaction, the current transaction behavior characteristics are analyzed in real time and compared with the user's normal transaction behavior pattern; If the current transaction behavior characteristics are significantly different from the user's normal transaction behavior pattern, the current transaction will be marked as an abnormal transaction. The significant differences include abnormally large transactions, frequent small transactions, and transaction times that are inconsistent with the user's normal transaction behavior pattern.

5. A computer network security transaction optimization system as claimed in claim 4, characterized in that: The security monitoring and protection module further includes: Anomaly detection unit, used to: When the transaction behavior analysis unit detects abnormal transaction behavior, a protection mechanism is automatically triggered, which includes limiting the transaction amount, requiring users to perform additional identity verification, freezing accounts, and suspending transactions; At the same time, an alarm message is sent to the security administrator; Record abnormal transaction data marked as abnormal transactions and send them to the transaction audit management module.

6. A computer network security transaction optimization system as claimed in claim 1, characterized in that: The transaction intelligent optimization module includes: The transaction request scheduling unit is used to: Monitor the workload data and current transaction flow data of each processing node in real time, and collect the response time, processing capacity, and resource usage information of each node; When a new transaction request arrives, it distributes the transaction request among multiple available nodes based on the current transaction flow data. When it is detected that the load of the processing node exceeds the set threshold, the new transaction request is automatically allocated to the node with low load; When the volume of transaction requests increases and the network condition becomes unstable, backup processing nodes are automatically enabled and node configurations are dynamically adjusted.

7. A computer network security transaction optimization system as claimed in claim 6, characterized in that: The transaction intelligent optimization module further includes: Node resource anomaly monitoring module, used for: Real-time monitoring of node resource occupancy information corresponding to each unit time, wherein the node resource occupancy information includes CPU occupancy, memory occupancy and communication bandwidth occupancy; According to the CPU occupancy rate, memory occupancy rate and communication bandwidth occupancy rate corresponding to each unit time, the change degree coefficients corresponding to the CPU occupancy rate, the memory occupancy rate and the communication bandwidth occupancy rate are obtained; The coefficients of variation of the CPU occupancy, memory occupancy, and communication bandwidth occupancy are obtained by the following formula: Where P represents the coefficient of variation of CPU occupancy, memory occupancy and communication bandwidth occupancy; n represents the number of unit time experienced by the processing node, and the unit time is 1s; X i represents the value of CPU occupancy, memory occupancy and communication bandwidth occupancy corresponding to the i-th unit time; X maxi represents the maximum value of CPU occupancy, memory occupancy and communication bandwidth occupancy at the i-th unit time; X bi represents the standard deviation of the CPU occupancy rate, memory occupancy rate, and communication bandwidth occupancy rate corresponding to the i-th unit time; X maxbi It represents the standard deviation of the maximum values ​​of CPU usage, memory usage and communication bandwidth usage that occur in the i-th unit time; Compare the change degree coefficients corresponding to the CPU occupancy rate, memory occupancy rate and communication bandwidth occupancy rate with their corresponding preset change degree coefficient thresholds respectively; When any one of the variation degree coefficients corresponding to the CPU occupancy rate, memory occupancy rate and communication bandwidth occupancy rate exceeds its corresponding preset variation degree coefficient threshold, the CPU occupancy rate, memory occupancy rate and communication bandwidth occupancy rate are used to determine whether there is resource utilization abnormality in the processing node.

8. A computer network security transaction optimization system as claimed in claim 7, characterized in that: The determining whether there is resource utilization abnormality in the processing node by using the CPU occupancy rate, the memory occupancy rate and the communication bandwidth occupancy rate includes: When any one of the variation coefficients corresponding to the CPU occupancy rate, the memory occupancy rate and the communication bandwidth occupancy rate exceeds the corresponding preset variation coefficient threshold, the CPU occupancy rate, the memory occupancy rate and the communication bandwidth occupancy rate corresponding to each unit time are retrieved; The resource anomaly determination coefficient is obtained by using the CPU occupancy rate, memory occupancy rate and communication bandwidth occupancy rate corresponding to each unit time; The resource anomaly determination coefficient is obtained by the following formula: Where Z represents the resource anomaly determination coefficient; n represents the number of unit times experienced by the processing node, and the unit time is 1s; X ci Indicates the CPU occupancy rate corresponding to the i-th unit time; X ni represents the memory usage corresponding to the i-th unit time; X ti represents the communication bandwidth occupancy rate corresponding to the i-th unit time; X cfi Indicates the maximum change of CPU usage corresponding to the i-th unit time; X nfi Indicates the maximum change of memory usage rate corresponding to the i-th unit time; X tfi represents the maximum change amplitude of the communication bandwidth occupancy rate corresponding to the i-th unit time; T ci represents the time interval between the CPU usage rate corresponding to the i-th unit time and the maximum CPU usage rate; T ni represents the time interval between the memory usage rate corresponding to the i-th unit time and the maximum memory usage rate; T ti represents the time interval between the communication bandwidth occupancy rate corresponding to the i-th unit time and the maximum communication bandwidth occupancy rate; P ci , P ni and P ti Respectively represent the change degree coefficient of the CPU occupancy rate, the change degree coefficient of the memory occupancy rate and the change degree coefficient of the communication bandwidth occupancy rate of the i-th unit time; compare the resource abnormality determination coefficient with the preset determination coefficient; When the resource anomaly determination coefficient exceeds a preset determination coefficient, it is determined that the node is in a resource utilization anomaly state, and a resource utilization anomaly alarm is issued.

9. A computer network security transaction optimization system as claimed in claim 6, characterized in that: The transaction intelligent optimization module includes: The transaction path adjustment unit is used to: When receiving a transaction request, the transmission requirements of the transaction data are evaluated based on the transaction type, amount, and location of the two parties. For sensitive transactions, a highly secure transmission path is selected. For normal transactions, the transmission path is optimized based on the latency requirements. For critical and high-risk transactions, data is transmitted simultaneously through multiple secure paths. Monitor the health status and transmission quality of network links in real time to determine whether the current network is congested, bandwidth limited, or subject to malicious attack risks. Automatically switch transmission paths when the quality of the transmission path degrades or is attacked.

10. A computer network security transaction optimization system as claimed in claim 1, characterized in that: The transaction audit management module includes: Data logging storage unit for: Record and store key transaction information during the transaction process, including transaction time, transaction amount, identities of both parties to the transaction, transaction status, transaction type, and transaction account; Transaction behavior audit unit, used to: Establish a transaction behavior audit rule base based on industry regulations, internal organizational policies, and historical transaction data. The transaction behavior audit rule base includes rules for abnormal transaction amounts, large transaction frequencies, transaction times that are inconsistent with habits, and transaction pattern mutations; Audit transactions based on the set rules in the transaction behavior audit rule base. If the transaction behavior violates the preset rules, the transaction will be marked as an abnormal transaction. When an abnormal transaction is identified, the current transaction is marked as a suspicious transaction, and the suspicious transaction information of the suspicious transaction is archived. The suspicious transaction information includes the transaction time, amount, accounts involved, and abnormal behavior characteristics.

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