High-safety terminal equipment for e-commerce operation and maintenance management and working method thereof
By introducing technologies such as multi-factor authentication, dynamic permission tokens, and real-time policy matching into the operation and maintenance terminal equipment, the problem of permission abuse in existing operation and maintenance terminals has been solved. Dynamic permission control based on session context and real-time anomaly detection have been realized to ensure the security and integrity of operation and maintenance operations.
Patent Information
- Application Number
- CN202511665405.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-13
- Publication Date
- 2025-12-12
AI Technical Summary
Existing high-security operation and maintenance terminals use static and coarse-grained permission allocation, which cannot achieve dynamic least privilege control based on session context, thus posing a risk of permission abuse.
It employs an authentication module, an authorization module, a channel establishment module, a data encryption module, an operation capture module, a session reconstruction module, a behavior analysis module, and a policy decision module. Combined with multi-factor authentication, dynamic permission tokens, national cryptographic algorithms, machine learning, and real-time policy matching, it forms a complete protection closed loop to prevent the abuse of permissions.
It implements dynamic access control based on session context, ensuring the security and integrity of operation and maintenance, preventing access abuse, and providing real-time anomaly detection and response mechanisms, forming a comprehensive protection from identity authentication to operation response.
Smart Images
Figure CN121125362A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the fields of e-commerce and information security technology, and in particular to a high-security terminal device for e-commerce operation and maintenance management and its working method. Background Technology
[0002] The stable and efficient operation of e-commerce platforms heavily relies on continuous system maintenance and management. Maintenance and management terminal devices are crucial tools for maintenance engineers to configure, monitor, debug, and troubleshoot the servers, databases, network devices, and applications of e-commerce platforms. Traditionally, these terminals are typically general-purpose computers or workstations equipped with remote connection tools such as SSH, RDP, and Telnet. Maintenance personnel directly access the production environment through these terminals to execute various maintenance commands; their operations directly impact the core data security and service continuity of the e-commerce business.
[0003] To enhance security, several high-security operation and maintenance (O&M) endpoint solutions have emerged in the current technology landscape. These solutions typically employ basic username / password authentication, potentially combined with hardware keys. Their basic architecture involves deploying a jump server or bastion host between the O&M endpoint and the business server. All O&M connections must first pass through this intermediate node, where authentication and logging are performed. The security principle lies in centralized access control, transforming direct server access into indirect access via a controlled gateway, thereby isolating O&M personnel from production servers at the network layer.
[0004] However, in actual use, although the authentication mechanism of existing high-security operation and maintenance terminals has been strengthened, the permission allocation is often static and coarse-grained, which cannot achieve dynamic least privilege control based on session context, and there is a risk of permission abuse. Summary of the Invention
[0005] The purpose of this invention is to provide a high-security e-commerce operation and maintenance management terminal device and its working method, which solves the problem that in the actual use of existing high-security operation and maintenance terminals, although the authentication mechanism has been strengthened, the permission allocation is often static and coarse-grained, which cannot achieve dynamic least privilege control based on session context, and there is a risk of permission abuse.
[0006] To achieve the above objectives, the present invention provides a high-security e-commerce operation and maintenance management terminal device, which includes an authentication module, an authorization module, a channel establishment module, a data encryption module, an operation capture module, a session reconstruction module, a behavior analysis module, a policy decision module, and a response execution module. The authentication module is used to perform multi-factor authentication on the operator and trigger the authorization module after successful authentication. The authorization module is used to receive the authentication pass signal and dynamically generate a temporary permission token for this session based on the attribute-based access control model. The token is then sent to the channel establishment module. The channel establishment module is used to receive a temporary permission token from the authorization module and establish a communication connection with the target e-commerce business server according to the authorization scope of the token. The data encryption module is used to encrypt and protect the integrity of all data transmitted through the channel establishment module. The operation capture module is used to capture all operation and maintenance operation instructions, input parameters and server response data flowing through the data encryption module in real time, and send the captured raw data to the session reconstruction module. The session reconstruction module is used to receive raw data from the operation capture module, reconstruct it into a complete operation and maintenance session flow with temporal relationship based on the session identifier, and then send the reconstructed session flow to the behavior analysis module. The behavior analysis module is used to receive the session stream from the session reconstruction module, perform risk analysis on it based on rules and machine learning models to identify abnormal operation patterns, and output the analysis results to the policy decision module. The policy decision module is used to receive the analysis results from the behavior analysis module, match them with the internally preset security policy rule set in real time, and send the matching results to the response execution module. The response execution module is used to receive the matching result from the policy judgment module and to perform response actions such as real-time blocking, alarm, or requiring secondary confirmation for operations that are judged to be in violation.
[0007] The identity verification module includes a static credential verification unit, a dynamic credential verification unit, and an anti-brute-force control unit. The static credential verification unit is used to verify the username and password submitted by the user. The dynamic credential verification unit is used to verify at least one of time-based one-time password, hardware digital certificate or biometric information after the static credential verification is passed. The explosion-proof control unit is used to lock the current account and send a security alarm to the backend security management system when the number of consecutive authentication failures exceeds a preset threshold.
[0008] The authorization module includes a context acquisition unit, a policy calculation unit, and a token generation unit. The context acquisition unit is used to obtain the context information of the current session in real time. The context information includes the terminal device network address, access network type, current timestamp, and target server resource tag. The policy calculation unit is used to load access control policies based on roles, resources, operations, and environment, and combine them with the information obtained by the context acquisition unit to perform calculations through the policy decision engine, and output permission authorization determination. The token generation unit is used to generate a temporary permission token that specifies the scope of server access, operations that can be performed, and data access based on the output of the policy calculation unit. The validity period of the token is strictly limited to the current session.
[0009] The data encryption module, after establishing communication, uses a national cryptographic algorithm or an internationally recognized encryption algorithm to negotiate a key, generates a unique session key, and uses the session key to encrypt and decrypt communication data in real time. At the same time, it uses a message authentication code mechanism to verify the integrity of the data.
[0010] The operation capture module is deployed on the data flow path in a non-intrusive manner. The captured data includes operation instruction text, structured query language statements, graphical interface operation events, high-precision timestamps of operation occurrence, source and target network addresses, and session unique identifiers.
[0011] The behavior analysis module includes a rule matching unit and a machine learning unit. The rule matching unit predefines a list of high-risk operation sequences, a list of sensitive data access patterns, and a list of operations that violate the principle of least privilege, which are used to directly match the operation and maintenance session flow. The machine learning unit continuously learns from historical normal operation and maintenance behavior data to build a baseline of user and role behavior, and calculates in real time the abnormal deviation of the current operation sequence from the behavior baseline in order to detect potential threats.
[0012] The security policy rule set preset in the policy decision module is dynamically updatable.
[0013] The response actions executed by the response execution module have configurable priorities and execution order. High-level alarms can trigger the forced termination of the session and automatically generate a security event report.
[0014] This invention also provides a method for operating a high-security e-commerce operation and maintenance management terminal device, applied to the high-security e-commerce operation and maintenance management terminal device as described above, comprising the following steps: Authentication steps: The authentication module performs multi-factor authentication on the operation and maintenance personnel; Authorization steps: After successful verification, a temporary permission token for this session is dynamically generated through the authorization module; Secure channel establishment steps: A connection is established through the channel establishment module based on the authorization token, and encrypted communication is enabled through the data encryption module; Operation monitoring steps: During the operation and maintenance session, all operation data is captured in real time by the operation capture module, the session stream is reconstructed by the session reconstruction module, and real-time risk analysis is performed by the behavior analysis module. Strategy execution steps: The strategy judgment module performs real-time matching of behavior analysis results, and the response execution module implements preset response actions for violations. Audit report generation steps: After the session ends, a complete audit report containing all operation records, risk analysis results, and security response events is generated.
[0015] This invention discloses a high-security e-commerce operation and maintenance management terminal device and its working method, comprising an identity verification module, an authorization module, a channel establishment module, a data encryption module, an operation capture module, a session reconstruction module, a behavior analysis module, a policy decision module, and a response execution module. The identity verification module employs multi-factor authentication to ensure the operator's identity is trustworthy; the authorization module generates a dynamic permission token based on the real-time session context to achieve least privilege control; the channel establishment module establishes a directed connection based on the permission token; the data encryption module ensures transmission security; the operation capture module comprehensively records operation behaviors; the session reconstruction module reconstructs the complete operation scenario; the behavior analysis module identifies abnormal patterns through rules and machine learning; the policy decision module performs real-time policy matching; and the response execution module immediately handles unauthorized operations. These modules work collaboratively to form a complete protection loop from identity authentication to operation response, eliminating the risk of permission abuse. Attached Figure Description
[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the 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.
[0017] Figure 1 This is a schematic diagram of the high-security e-commerce operation and maintenance management terminal device provided by the present invention.
[0018] Figure 2 This is a flowchart illustrating the steps of the working method of the high-security e-commerce operation and maintenance management terminal device provided by the present invention.
[0019] 101-Authentication Module, 102-Authorization Module, 103-Channel Establishment Module, 104-Data Encryption Module, 105-Operation Capture Module, 106-Session Reconstruction Module, 107-Behavior Analysis Module, 108-Policy Decision Module, 109-Response Execution Module, 110-Static Credential Verification Unit, 111-Dynamic Credential Verification Unit, 112-Anti-Explosive Control Unit, 113-Context Acquisition Unit, 114-Policy Calculation Unit, 115-Token Generation Unit, 116-Rule Matching Unit, 117-Machine Learning Unit. Detailed Implementation
[0020] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.
[0021] Please see Figure 1 The present invention provides a high-security e-commerce operation and maintenance management terminal device, which includes an authentication module 101, an authorization module 102, a channel establishment module 103, a data encryption module 104, an operation capture module 105, a session reconstruction module 106, a behavior analysis module 107, a policy decision module 108, and a response execution module 109. The authentication module 101 is used to perform multi-factor authentication on the operator and trigger the authorization module 102 after successful authentication. The authorization module 102 is used to receive the authentication pass signal and dynamically generate a temporary permission token for this session based on the attribute-based access control model. The token is sent to the channel establishment module 103. The channel establishment module 103 is used to receive a temporary permission token from the authorization module 102 and establish a communication connection with the target e-commerce business server according to the authorization scope of the token. The data encryption module 104 is used to encrypt and protect the integrity of all data transmitted through the channel establishment module 103. The operation capture module 105 is used to capture all operation and maintenance operation instructions, input parameters and server response data flowing through the data encryption module 104 in real time, and send the captured raw data to the session reconstruction module 106. The session reconstruction module 106 is used to receive raw data from the operation capture module 105, reconstruct it into a complete operation and maintenance session flow with temporal relationship based on the session identifier, and then send the reconstructed session flow to the behavior analysis module 107. The behavior analysis module 107 is used to receive the session stream from the session reconstruction module 106, perform risk analysis on it based on rules and machine learning models to identify abnormal operation patterns, and output the analysis results to the policy decision module 108. The policy decision module 108 is used to receive the analysis results from the behavior analysis module 107, match them with the internally preset security policy rule set in real time, and send the matching results to the response execution module 109. The response execution module 109 is used to receive the matching result from the policy judgment module 108, and to perform response actions such as real-time blocking, alarm, or requiring secondary confirmation for operations that are judged to be in violation.
[0022] In this embodiment, the identity verification module 101 employs multi-factor authentication to ensure the operator's identity is trustworthy; the authorization module 102 generates a dynamic permission token based on the real-time session context to achieve least privilege control; the channel establishment module 103 establishes a directed connection based on the permission token; the data encryption module 104 ensures transmission security; the operation capture module 105 comprehensively records operation behavior; the session reconstruction module 106 reconstructs the complete operation scenario; the behavior analysis module 107 identifies abnormal patterns through rules and machine learning; the policy judgment module 108 performs real-time policy matching; and the response execution module 109 immediately handles unauthorized operations. These modules work collaboratively to form a complete protection loop from identity authentication to operation response, eliminating the risk of permission abuse.
[0023] Furthermore, the identity verification module 101 includes a static credential verification unit 110, a dynamic credential verification unit 111, and an anti-explosive control unit 112. The static credential verification unit 110 is used to verify the username and password submitted by the user. The dynamic credential verification unit 111 is used to verify at least one of time-based one-time password, hardware digital certificate or biometric information after the static credential verification is passed. The explosion-proof control unit 112 is used to lock the current account and send a security alarm message to the backend security management system when the number of consecutive authentication failures exceeds a preset threshold.
[0024] In this embodiment, the static credential verification unit 110 first verifies the traditional username and password to ensure the authenticity of the basic identity; the dynamic credential verification unit 111 adds a second layer of verification, such as a one-time password or biometric feature, to effectively prevent the risk of credential leakage; the anti-brute-force control unit 112 monitors the authentication attempt frequency in real time and automatically locks the account and issues an alarm when it detects brute-force attack behavior (multiple identity verification attempts in a short period of time).
[0025] Furthermore, the authorization module 102 includes a context acquisition unit 113, a policy calculation unit 114, and a token generation unit 115. The context acquisition unit 113 is used to acquire the context information of the current session in real time. The context information includes the terminal device network address, access network type, current timestamp, and target server resource tag. The policy calculation unit 114 is used to load access control policies based on roles, resources, operations and environment, and combine them with the information obtained by the context acquisition unit 113 to perform calculations through the policy decision engine and output permission authorization judgments. The token generation unit 115 is used to generate a temporary permission token that specifies the scope of server access, operations that can be performed, and data access based on the output of the policy calculation unit 114. The validity period of the token is strictly limited to the current session.
[0026] In this implementation, this real-time context-based authorization method transforms traditional static permissions into a minimum set of permissions that dynamically adjusts with the scenario, fundamentally eliminating the risk of excessive permission allocation and abuse, and achieving refined and intelligent permission management.
[0027] Furthermore, after establishing communication, the data encryption module 104 uses a national cryptographic algorithm or an internationally recognized encryption algorithm to negotiate a key, generates a unique session key, and uses the session key to encrypt and decrypt the communication data in real time. At the same time, it uses a message authentication code mechanism to verify the integrity of the data.
[0028] Furthermore, the operation capture module 105 is deployed on the data flow path in a non-intrusive manner, and the captured data includes operation instruction text, structured query language statements, graphical interface operation events, high-precision timestamps of operation occurrence, source and target network addresses, and session unique identifiers.
[0029] In this embodiment, the data encryption module 104 employs a high-strength encryption algorithm and integrity verification to ensure that all operation and maintenance data cannot be stolen or tampered with during transmission; the operation capture module 105 comprehensively records various operation instructions and their detailed context information in a non-intrusive manner, forming a complete chain of operation evidence.
[0030] Furthermore, the behavior analysis module 107 includes a rule matching unit 116 and a machine learning unit 117. The rule matching unit 116 predefines a list of high-risk operation sequences, a list of sensitive data access patterns, and a list of operations that violate the principle of least privilege, which are used to directly match the operation and maintenance session flow. The machine learning unit 117 constructs a baseline of user and role behavior by continuously learning historical normal operation and maintenance behavior data, and calculates the abnormal deviation of the current operation sequence from the behavior baseline in real time to detect potential threats.
[0031] In this embodiment, the rule matching unit 116 directly intercepts known high-risk operations and unauthorized behaviors based on a preset security policy list; the machine learning unit 117 intelligently detects abnormal operation sequences that deviate from the normal pattern by establishing a user behavior baseline.
[0032] Furthermore, the set of security policy rules preset in the policy decision module 108 is dynamically updatable.
[0033] Furthermore, the identity verification module 101 includes a static credential verification unit 110, a dynamic credential verification unit 111, and an anti-explosive control unit 112. The static credential verification unit 110 is used to verify the username and password submitted by the user. The dynamic credential verification unit 111 is used to verify at least one of time-based one-time password, hardware digital certificate or biometric information after the static credential verification is passed. The explosion-proof control unit 112 is used to lock the current account and send a security alarm message to the backend security management system when the number of consecutive authentication failures exceeds a preset threshold.
[0034] In this embodiment, the static credential verification unit 110 first verifies the traditional username and password to ensure the authenticity of the basic identity; the dynamic credential verification unit 111 adds a second layer of verification, such as a one-time password or biometric feature, to effectively prevent the risk of credential leakage; the anti-brute-force control unit 112 monitors the authentication attempt frequency in real time and automatically locks the account and issues an alarm when it detects brute-force attack behavior (multiple identity verification attempts in a short period of time).
[0035] Furthermore, the authorization module 102 includes a context acquisition unit 113, a policy calculation unit 114, and a token generation unit 115. The context acquisition unit 113 is used to acquire the context information of the current session in real time. The context information includes the terminal device network address, access network type, current timestamp, and target server resource tag. The policy calculation unit 114 is used to load access control policies based on roles, resources, operations and environment, and combine them with the information obtained by the context acquisition unit 113 to perform calculations through the policy decision engine and output permission authorization judgments. The token generation unit 115 is used to generate a temporary permission token that specifies the scope of server access, operations that can be performed, and data access based on the output of the policy calculation unit 114. The validity period of the token is strictly limited to the current session.
[0036] In this implementation, this real-time context-based authorization method transforms traditional static permissions into a minimum set of permissions that dynamically adjusts with the scenario, fundamentally eliminating the risk of excessive permission allocation and abuse, and achieving refined and intelligent permission management.
[0037] Furthermore, after establishing communication, the data encryption module 104 uses a national cryptographic algorithm or an internationally recognized encryption algorithm to negotiate a key, generates a unique session key, and uses the session key to encrypt and decrypt the communication data in real time. At the same time, it uses a message authentication code mechanism to verify the integrity of the data.
[0038] Furthermore, the operation capture module 105 is deployed on the data flow path in a non-intrusive manner, and the captured data includes operation instruction text, structured query language statements, graphical interface operation events, high-precision timestamps of operation occurrence, source and target network addresses, and session unique identifiers.
[0039] In this embodiment, the data encryption module 104 employs a high-strength encryption algorithm and integrity verification to ensure that all operation and maintenance data cannot be stolen or tampered with during transmission; the operation capture module 105 comprehensively records various operation instructions and their detailed context information in a non-intrusive manner, forming a complete chain of operation evidence.
[0040] Furthermore, the behavior analysis module 107 includes a rule matching unit 116 and a machine learning unit 117. The rule matching unit 116 predefines a list of high-risk operation sequences, a list of sensitive data access patterns, and a list of operations that violate the principle of least privilege, which are used to directly match the operation and maintenance session flow. The machine learning unit 117 constructs a baseline of user and role behavior by continuously learning historical normal operation and maintenance behavior data, and calculates the abnormal deviation of the current operation sequence from the behavior baseline in real time to detect potential threats.
[0041] In this embodiment, the rule matching unit 116 directly intercepts known high-risk operations and unauthorized behaviors based on a preset security policy list; the machine learning unit 117 intelligently detects abnormal operation sequences that deviate from the normal pattern by establishing a user behavior baseline.
[0042] Furthermore, the set of security policy rules preset in the policy decision module 108 is dynamically updatable.
Claims
1. A high-security e-commerce operation and maintenance management terminal device, characterized in that, comprising an identity verification module, an authorization module, a channel establishment module, a data encryption module, an operation capture module, a session reconstruction module, a behavior analysis module, a policy decision module and a response execution module, the identity verification module is used for multi-factor identity verification of operators, and triggers the authorization module after verification; The authorization module is used for receiving identity verification pass signal, and dynamically generating temporary permission token of this session based on attribute-based access control model, and the token is sent to the channel establishment module; The channel establishment module is used for receiving temporary permission token from the authorization module, and establishing communication connection with the target e-commerce business server according to the authorization range of the token; The data encryption module is used for encrypting and integrity protecting all data transmitted through the channel establishment module; The operation capture module is used for capturing all operation instructions, input parameters and server response data flowing through the data encryption module in real time, and sending the captured original data to the session reconstruction module; The session reconstruction module is used for receiving original data from the operation capture module, and recombining it into a complete operation session stream with time sequence relationship based on session identifier, and then sending the reconstructed session stream to the behavior analysis module; The behavior analysis module is used for receiving the session stream from the session reconstruction module, performing risk analysis based on rules and machine learning model to identify abnormal operation mode, and outputting the analysis result to the policy decision module; The policy decision module is used for receiving the analysis result from the behavior analysis module, and matching it with the internal preset security policy rule set in real time, and sending the matching result to the response execution module; The response execution module is used for receiving the matching result from the policy decision module, and executing real-time blocking, alarming or requiring secondary confirmation response action for the operation judged as violating the rules.
2. The high-security e-commerce operation and maintenance management terminal device of claim 1, characterized in that, The identity verification module comprises a static credential verification unit, a dynamic credential verification unit and a blast control unit, the static credential verification unit is used for verifying the username and password submitted by the user; The dynamic credential verification unit is used for verifying at least one of the time-based one-time password, hardware digital certificate or biometric information after the static credential verification passes; The blast control unit is used for locking the current account and sending security alarm information to the backend security management system when the number of consecutive authentication failures exceeds the preset threshold.
3. The high-security e-commerce operation and maintenance management terminal device of claim 2, characterized in that, The authorization module comprises a context collection unit, a policy calculation unit and a token generation unit, the context collection unit is used for acquiring context information of the current session in real time, and the context information comprises terminal device network address, access network type, current timestamp and target server resource label; The policy computing unit is configured to load an access control policy based on roles, resources, operations and environments, and to combine information obtained by the context collection unit to perform calculation through a policy decision engine, and output a permission authorization decision. The token generation unit is configured to generate a temporary permission token that specifies accessible servers, executable operations and data access ranges according to an output result of the policy computing unit, and the validity period of the token is strictly limited to the current session.
4. The terminal device for high-security e-commerce operation and maintenance management according to claim 3, characterized in that: The data encryption module uses a national encryption algorithm or an internationally common encryption algorithm to perform key negotiation after establishing communication, generates a unique session key, and uses the session key to perform real-time encryption and decryption of communication data, while using a message authentication code mechanism to verify the integrity of the data.
5. The terminal device for high-security e-commerce operation and maintenance management according to claim 4, characterized in that: The operation capture module is deployed in a non-intrusive manner on a data flow path, and the captured data includes operation instruction text, structured query language statements, graphical interface operation events, high-precision timestamps of operation occurrence, source and target network addresses, and session unique identifiers.
6. The terminal device for high-security e-commerce operation and maintenance management according to claim 5, characterized in that: The behavior analysis module includes a rule matching unit and a machine learning unit, the rule matching unit is pre-defined with a list of high-risk operation sequences, a list of sensitive data access patterns, and a list of operations that violate the principle of least privilege, and is used to directly match the operation and maintenance session flow; The machine learning unit constructs a user and role behavior baseline by continuously learning historical normal operation and maintenance behavior data, and calculates the abnormal deviation degree of the current operation sequence relative to the behavior baseline in real time to detect potential threats.
7. The terminal device for high-security e-commerce operation and maintenance management according to claim 6, characterized in that: The set of security policy rules pre-installed in the policy decision module is dynamically updateable.
8. The terminal device for high-security e-commerce operation and maintenance management according to claim 7, characterized in that: The response actions performed by the response execution module have configurable priority and execution order, and high-level alarms can trigger forced termination of the session and automatically generate a security event report. 9.A working method of a terminal device for high-security e-commerce operation and maintenance management, applied to the terminal device for high-security e-commerce operation and maintenance management according to claim 1, characterized in that, The steps include: An identity verification step: performing multi-factor identity verification of the operation and maintenance operator through the identity verification module; An authorization step: after verification, generating a temporary permission token for the current session through the authorization module; A secure channel establishment step: establishing a connection according to the permission token through the channel establishment module, and enabling encrypted communication through the data encryption module; An operation monitoring step: during the operation and maintenance session, capturing all operation data in real time through the operation capture module, reorganizing the session flow through the session reconstruction module, and performing real-time risk analysis through the behavior analysis module; A policy execution step: performing real-time matching of the behavior analysis result through the policy decision module, and implementing pre-set response actions on the rule-violating operation through the response execution module; Audit report generation step: After the session ends, a complete audit report containing all operation records, risk analysis results, and security response events is generated.