Network information consultation platform based on zero-trust architecture and communication method

Abstract

The invention discloses a network information consultation platform and communication method based on a zero-trust architecture, and relates to the technical field of digital platform communication, and the method comprises the following steps: carrying out the identity authentication of a user; when the identity authentication is passed, obtaining user data; inputting the user data into a trust evaluation model, and outputting a comprehensive trust degree; obtaining an access permission according to the comprehensive credibility; monitoring the consultation behavior of the user in real time, and calculating the real-time credibility; and managing the access authority according to the real-time credibility. According to the invention, the user data of the user whose identity authentication is successful is acquired, the comprehensive credibility of the user is calculated according to the user data to quantify the credit rating of the user, the user is monitored in the whole course in the user consultation process, and the user access authority is managed in combination with the user credit rating and real-time monitoring, so that the security of the platform is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of digital platform communication, in particular to a network information consulting platform based on a zero-trust architecture and a communication method. BACKGROUND

[0002] A network information consulting platform is an Internet-based service platform that provides efficient and convenient information consulting and resource access. It contains resources in multiple fields and helps users quickly obtain the information they need by integrating data resources and professional knowledge. However, with the complexity of the network environment, traditional network information consulting platforms have certain security defects.

[0003] The existing network information consulting platform adopts a static permission management mechanism. When a user is authenticated, the user obtains fixed access permissions. When facing multiple resource accesses, there may be problems of excessive or insufficient permission allocation, affecting the user's consulting experience and the security of the platform. Therefore, there is an urgent need for a network information consulting platform communication method that implements fine-grained permission management. SUMMARY

[0004] The purpose of the present application is to provide a network information consulting platform based on a zero-trust architecture and a communication method. The present application obtains user data of a user who has successfully passed identity authentication, calculates the comprehensive trust degree of the user according to the user data to quantify the credit level of the user, monitors the user throughout the consultation process, manages the user's access permissions in combination with the user's credit level and real-time monitoring, and improves the security of the platform.

[0005] The purpose of the present application is achieved by the following technical means:

[0006] In a first aspect, the present application provides a communication method for a network information consulting platform based on a zero-trust architecture, comprising the following steps:

[0007] Authenticating the user;

[0008] When the identity authentication is passed, obtaining user data;

[0009] Inputting the user data into a trust evaluation model and outputting a comprehensive trust degree;

[0010] According to the comprehensive trust degree, obtaining access permissions;

[0011] Real-time monitoring of the user's consulting behavior and calculating a real-time trust degree;

[0012] According to the real-time trust degree, managing the access permissions.

[0013] Preferably, the step of inputting the user data into a trust evaluation model and outputting a comprehensive trust degree comprises the following steps:

[0014] normalizing the user data and calculating a weight coefficient of each user data;

[0015] calculating a first trust degree according to the normalized user data and the weight coefficient;

[0016] obtaining historical access data;

[0017] obtaining a consultation score of each historical access data and calculating a time difference of the data;

[0018] calculating a second trust degree according to the consultation score and the time difference;

[0019] weighting and summing the first trust degree and the second trust degree to obtain the comprehensive trust degree.

[0020] Preferably, the calculation formula of the first trust degree is as follows:

[0021] ,

[0022] wherein, is the first trust degree, is the number of user data, is the weight coefficient of the i-th user data, is the normalized value of the i-th user data; The calculation formula of the second trust degree is as follows:

[0023]

[0024] ,

[0025] wherein, is the second trust degree, is the number of historical access data, is a time decay rate, is the time difference between the i-th historical access data and the current access, is the consultation score of the i-th historical access data; The calculation formula of the comprehensive trust degree is as follows:

[0026]

[0027] , ,

[0028] wherein, is the comprehensive trust degree, ​​​​and These are the weighting coefficients. As the highest level of trust, This is the second level of trust.

[0029] Preferably, obtaining access rights based on the comprehensive trust level includes the following steps:

[0030] Analyze the consultation content to identify the consultation topics;

[0031] Select a decision tree based on the consultation topic;

[0032] The overall trust level is compared with the trust threshold, and the initial permissions are obtained from the decision tree based on the comparison result;

[0033] Calculate the relevance between the consultation topic and the initial permissions;

[0034] The initial permissions are removed based on the correlation to obtain the access permissions.

[0035] Preferably, the real-time monitoring of users' consultation behavior and the calculation of real-time trust levels include the following steps:

[0036] Monitor users' inquiry behavior in real time and record the number of times it is completed;

[0037] When abnormal behavior is detected, the number of abnormalities is recorded and an abnormality score is obtained.

[0038] The real-time trust level is calculated based on the number of completions, the number of anomalies, and the anomaly score.

[0039] Preferably, the formula for calculating the real-time trust level is as follows:

[0040] ,

[0041] in, For real-time trust levels, To assess overall trust levels, The number of types of abnormal behavior. For the first Abnormal scores for various abnormal behaviors For the first The number of abnormal behaviors. For normal score, This represents the number of consultations completed.

[0042] Preferably, managing the access permissions based on the real-time trust level includes the following steps:

[0043] Compare the real-time trust level with the trust threshold;

[0044] When the real-time trust level is less than the trust threshold, the user's consultation session is terminated;

[0045] When the real-time trust level is greater than or equal to the trust threshold, the real-time difference is calculated;

[0046] When the real-time difference is greater than or equal to zero, the access permission is expanded;

[0047] When the real-time difference is less than zero, the access permission is reduced;

[0048] When a consultation session ends, the consultation score is recorded and added to the historical access data.

[0049] Secondly, the present invention provides a network information consultation platform based on a zero-trust architecture, and the communication method of the network information consultation platform based on a zero-trust architecture described above includes: an identity management module, a data acquisition module, a trust assessment module, an access management module, a real-time monitoring module, and an access management module.

[0050] The identity management module is used to authenticate the user's identity;

[0051] The data acquisition module is used to acquire user data when identity authentication is successful;

[0052] The trust assessment module is used to input the user data into the trust assessment model and output a comprehensive trust level.

[0053] The access management module is used to obtain access permissions based on the comprehensive trust level;

[0054] The real-time monitoring module is used to monitor users' consultation behavior in real time and calculate the real-time trust level.

[0055] The access management module is used to manage the access permissions based on the real-time trust level.

[0056] Thirdly, the present invention provides an electronic device including a processor and a memory, the memory being used to store computer program code, the computer program code including computer instructions, and when the processor executes the computer instructions, the electronic device executes the above-described communication method for a network information consultation platform based on a zero-trust architecture.

[0057] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor of an electronic device, cause the processor to execute the aforementioned communication method of a network information consultation platform based on a zero-trust architecture.

[0058] Compared with the prior art, the present application has the beneficial effects that:

[0059] The present application quantifies the credit level of the user by obtaining the user data of the user whose identity authentication is successful, calculating the comprehensive trust degree of the user according to the user data, monitoring the user throughout the consultation process, and managing the access authority of the user in combination with the credit level of the user and real-time monitoring, thereby improving the security of the platform.

[0060] The present application improves the security of the platform by obtaining the static data of the user, performing normalization processing on the static data, and evaluating and calculating the first trust degree from three aspects of payment degree, authentication security and address security, obtaining the consultation score and time difference of each access from the historical access data, evaluating and calculating the second trust degree from the historical behavior, and calculating the comprehensive trust degree of the user according to the first trust degree and the second trust degree to measure the trust level of the user, thereby providing a data basis for subsequent initial allocation of authority.

[0061] The present application improves the efficiency of resource query by analyzing the consultation topic of the user through NLP technology, selecting a suitable decision tree from the pre-constructed multiple resource decision trees and obtaining the initial authority, and at the same time, calculating the relevance of the consultation topic and the initial authority through NLP technology, eliminating redundant authority, which is beneficial to the accurate allocation of authority and improves the security of the platform.

[0062] The present application improves the security of the platform by obtaining the normal behavior and abnormal behavior of the user, dynamically responding to the behavior change of the user, terminating the session in time when the real-time trust degree of the user is low, and dynamically adjusting the access authority of the user according to the real-time trust degree, storing the consultation score of the user to the historical access data, thereby providing a data basis for trust evaluation of future access of the user. BRIEF DESCRIPTION OF DRAWINGS

[0063] The accompanying drawings, which are incorporated into and form part of the specification, illustrate embodiments consistent with the present application and, together with the specification, serve to explain the principles of the present application.

[0064] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows, and obviously, other drawings can also be obtained by those skilled in the art without creative labor.

[0065] Figure 1 A flowchart of a communication method of a network information consultation platform based on a zero-trust architecture provided by the present embodiment;

[0066] Figure 2The step S3 provided for the embodiment is inputting the user data into the trust evaluation model, and outputting the comprehensive trust degree.

[0067] Figure 3 The step S4 provided for the embodiment is a flowchart of acquiring the access right according to the comprehensive trust degree.

[0068] Figure 4 The step S5 provided for the embodiment is a flowchart of monitoring the consulting behavior of the user in real time and calculating the real-time trust degree.

[0069] Figure 5 The step S6 provided for the embodiment is a flowchart of managing the access right according to the real-time trust degree.

[0070] Figure 6 The structural schematic diagram of the network information consulting platform based on the zero trust architecture provided for the embodiment;

[0071] Figure 7 The structural schematic diagram of the electronic device provided for the embodiment. DETAILED DESCRIPTION

[0072] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0073] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present application are only used to explain the relative positional relationship, movement condition, etc. between components in a certain posture, and if the certain posture changes, the directional indications will also change accordingly.

[0074] In addition, the description of "first", "second", etc. in the present application is only for the purpose of description, and cannot be understood as indicating or implying the relative importance of the indicated technical features or implicitly indicating the number of the indicated technical features. Therefore, the features limited by "first", "second" can explicitly or implicitly include at least one of the features. In addition, the technical solutions of each embodiment can be combined with each other, but it must be based on the realization of those of ordinary skill in the art, and when the combination of technical solutions appears contradictory or unachievable, it should be considered that the combination of technical solutions does not exist, and is not within the scope of protection required by the present application.

[0075] Embodiment one

[0076] The embodiment provides a communication method of a network information consultation platform based on a zero-trust architecture, as shown in the accompanying drawings, comprising the following steps: Figure 1

[0077] S1, identity authentication is performed on the user;

[0078] S2, when the identity authentication is passed, user data is acquired;

[0079] S3, the user data is input into a trust evaluation model, and a comprehensive trust degree is output;

[0080] S4, according to the comprehensive trust degree, access permission is acquired;

[0081] S5, the consultation behavior of the user is monitored in real time, and a real-time trust degree is calculated;

[0082] S6, according to the real-time trust degree, the access permission is managed.

[0083] It should be noted that identity authentication is performed on the user, which is the basis of the zero-trust architecture, and its essence lies in ensuring that only the verified user can access the resources of the platform through the preset security policy. The security policy adopted in the identity authentication is prior art, and will not be described here. The user data includes: user account type, identity authentication level and device security state. Specifically, the user account type includes free users, paid users and subscription users, the identity authentication level is rated according to the identity authentication method adopted by the user, and the device security state is evaluated according to the IP of the user device. The comprehensive trust degree of the user is calculated through the above-mentioned user data. The trust evaluation model is a mathematical calculation model designed according to platform data, which is used to calculate the comprehensive trust degree according to the user data. The comprehensive trust degree is used to measure the trust level of the user, and the access permission of the user is determined according to the trust level. In the process of consultation of the user, the consultation behavior of the user is monitored in real time, the trust degree of the user is updated, and the access permission of the user is adjusted in real time.

[0084] In the embodiment, the user data of the user whose identity authentication is successful is acquired, the comprehensive trust degree of the user is calculated according to the user data to quantify the credit level of the user, the user is monitored throughout the consultation process, the access permission of the user is managed in combination with the credit level of the user and the real-time monitoring, and the safety of the platform is improved.

[0085] In some embodiments, step S3, the user data is input into a trust evaluation model, and a comprehensive trust degree is output, as shown in the accompanying drawings, comprising the following steps: Figure 2

[0086] S31, the user data is normalized, and the weight coefficient of each user data is calculated;

[0087] ​​S32, calculate a first trust degree according to the normalized user data and the weight coefficient;

[0088] S33, obtain historical access data;

[0089] S34, obtain a consultation score of each historical access data and calculate a time difference of the data;

[0090] S35, calculate a second trust degree according to the consultation score and the time difference;

[0091] S36, perform weighted summation on the first trust degree and the second trust degree to obtain a comprehensive trust degree.

[0092] It should be noted that the comprehensive trust degree of the user is measured from two aspects, including user static data and user dynamic behavior. For the user static data part, it is calculated through user data. Since the value ranges of the user data are different, the user data with a larger value range will have a greater impact on the calculation result, therefore, the obtained user data is linearly normalized, the user data is normalized through the parameters obtained by statistically processing other user data stored by the platform, and the weight coefficients of each index in the user data are obtained by processing the stored other user data through the entropy weight method. Specifically, the historical user data stored by the platform is obtained as a sample, each user data includes three indexes of user account type, identity authentication level and device security state, a mapping table is established for each index, such as user account type including free user, paid user and subscription user, scoring according to payment level is 30, 50 and 90 respectively; the identity authentication level and the device state are scored according to a pre-set score table according to the type of user data that meets the type, specifically, the identity authentication level includes common authentication methods such as password, SMS verification code, fingerprint, face and two or more combinations, etc., the sum of the authentication security strength score and the authentication method is calculated, and the device security state is scored by evaluating the device IP location and the device signature, that is, the trust degree of the user is measured from three aspects of payment level, authentication security and address security. The weight coefficients of each index are calculated by the entropy weight method, and the specific calculation process of the entropy weight method for calculating the weight coefficients of each index is prior art, which is not described here. The first trust degree is obtained by performing weighted summation on the normalized user data and the weight coefficient and mapping to [0, 1], and the first trust degree is the score of the user static data part.

[0093] For the user dynamic behavior part, the first trust degree is calculated by historical access data. Since the historical access data has different access times, the earlier historical access data has less influence on the calculation result. Therefore, the time difference between each historical access and the current access is calculated, and the consultation score of each historical access is combined to obtain a second trust degree, which is the score of the user dynamic behavior part. The consultation score is a score based on the user's behavior during access. When the user completes a consultation, he will get a certain score, and conversely, when the user has abnormal behavior, he will get a certain deduction. After the user completes the consultation in a time period, the scores are summed to obtain the consultation score. After obtaining the first trust degree and the second trust degree, the first trust degree and the second trust degree are weighted and summed to obtain the comprehensive trust degree score.

[0094] Specifically, the calculation formula of the first trust degree is as follows:

[0095] ,

[0096] Among them, is the first trust degree, is the number of user data, is the weight coefficient of the first user data, is the normalized value of the first user data; The calculation formula of the second trust degree is as follows:

[0097]

[0098] ,

[0099] Among them, is the second trust degree, is the number of historical access data, is the time decay rate, is the time difference between the first historical access data and the current access, is the consultation score of the first historical access data; the time decay rate is used to control the influence weight of the historical access data with different access times on the current trust evaluation. According to actual needs, it is set to be 0.5, for example, when it is hoped that the influence of the historical access data will be halved after one week, the time decay rate is set to be 0.5. The value of the time decay rate is not limited here.

[0100] The calculation formula of the comprehensive trust degree is as follows:

[0101] , ,

[0102] Among them, ​​​​is a comprehensive trust degree, and is a weight coefficient, is a first trust degree, is a second trust degree. and According to actual needs, in some embodiments, the zero trust architecture consulting platform pays more attention to static data of initial identity authentication, and in order to improve the interception rate of abnormal access and reduce the false interception rate of normal access, the value of the weight coefficient is set to , .

[0103] In this embodiment, by combining the static data and dynamic behavior of the user, the static data is normalized and the first trust degree is evaluated and calculated from three aspects of payment degree, authentication security and address security, the consulting score and time difference of each access are obtained from the historical access data, the second trust degree is evaluated and calculated from the historical behavior, and the comprehensive trust degree of the user is calculated according to the first trust degree and the second trust degree to measure the trust level of the user, which provides a data basis for subsequent initial permission allocation and improves the security of the platform.

[0104] In some embodiments, step S4, according to the comprehensive trust degree, obtaining the access permission, as shown in Figure 3 , includes the following steps:

[0105] S41, analyzing the consulting content to obtain a consulting topic;

[0106] S42, selecting a decision tree according to the consulting topic;

[0107] S43, comparing the comprehensive trust degree with a trust threshold, and obtaining an initial permission from the decision tree according to the comparison result;

[0108] S44, calculating the relevance of the consulting topic and the initial permission;

[0109] S45, eliminating the initial permission according to the relevance to obtain the access permission.

[0110] It should be noted that the network information consulting platform stores information related to multiple aspects and fields, and needs to quickly locate the corresponding information according to the user's consulting content and determine the user's access permission. The platform classifies all internal resources into multiple decision trees, each decision tree corresponds to a topic, and uses NLP technology to extract the consulting topic of the user's consulting content, such as preprocessing the user's consulting text, including eliminating stop words and word segmentation, identifying entities in the consulting text and generating topic vectors, and calculating the relevance of the topic vector and the corresponding topic of the decision tree to quickly select the decision tree. For example, when the user asks about medical insurance, the platform analyzes the user's consulting topic and classifies it into the legal and medical categories, so the legal decision tree and the medical decision tree can be quickly selected for subsequent processing. Multiple decision trees in different fields form a decision forest, and each decision tree contains multiple nodes, each node representing the permission of a class of resources. The network information consulting platform supports consulting in the fields of law, medicine, and education. For example, the intermediate nodes of the legal decision tree include different legal resources such as criminal law, civil code, and labor law, and the leaf nodes under each node are the user's operation permissions such as viewing, downloading, or editing, as well as the trust level of opening the permission; the intermediate nodes of the medical decision tree include medical equipment, medical drugs, and case resources, and the leaf nodes under each node are also the user's operation permissions such as viewing, downloading, editing, or analysis, as well as the trust level of opening the permission. The division depth and conditions of the decision tree nodes are prior art and can be manually adjusted according to actual needs, and will not be described here.

[0111] After that, the platform compares the user's comprehensive trust level with the trust threshold interval in the corresponding decision tree to obtain the initial access permission. For example, the trust threshold for opening permission in the legal decision tree is 0.2, when the user's comprehensive trust level is less than 0.2, the user will not be able to access, and the initial permission is empty, when the user's comprehensive trust level is greater than or equal to 0.2, the user's viewing permission will be opened, and according to the size of the user's comprehensive trust level, more access permissions of functions and data are obtained to form the initial permission.

[0112] The initial permission includes the user's required permission and excess permission, and the initial permission needs to be further screened to eliminate the excess permission to achieve fine-grained resource isolation and avoid user over-reach access. When obtaining the consulting topic, NLP technology is used to analyze the consulting content, and the text features of the consulting content are converted into vector features. When calculating the relevance, NLP technology is used to analyze the node description of the initial permission to obtain the vector features of each node description, and the similarity between the consulting topic and the initial permission vector is calculated to obtain the relevance. When the relevance is greater than the matching threshold, the permission is retained, otherwise the permission is eliminated, thereby obtaining the user's access permission for this consultation.

[0113] In this embodiment, NLP technology is used to analyze the user's consultation topic, select the appropriate decision tree from multiple pre-built resource decision trees and obtain initial permissions, which improves the efficiency of resource query. At the same time, NLP technology is used to calculate the correlation between consultation topic and initial permissions, eliminate redundant permissions, which is conducive to the accurate allocation of permissions and improves the security of the platform.

[0114] In some embodiments, step S5 involves monitoring the user's consultation behavior in real time and calculating the real-time trust level, such as... Figure 4 As shown, it includes the following steps:

[0115] S51 monitors users' inquiry behavior in real time and records the number of times it is completed;

[0116] S52, when abnormal behavior is detected, record the number of abnormalities and obtain an abnormality score;

[0117] S53 calculates real-time trust level based on the number of completions, the number of anomalies, and the anomaly score.

[0118] It's important to note that a continuous monitoring system covering the entire consultation process is necessary. This system dynamically adjusts user access permissions based on real-time monitoring of user consultation behavior to ensure platform security. Consultation behavior includes normal and abnormal behavior. Each time a user completes a consultation, the number of completions is counted, representing normal behavior. Abnormal behavior is categorized into several types, such as multiple URL redirects, batch repetitive operations, access to sensitive data, and abnormal exits. Each abnormal behavior has a corresponding score. These scores are set according to actual needs; for example, 0.1 points are awarded for each URL redirect, 0.1 points for each repetitive operation, 0.15 points for each access to sensitive data, and 0.05 points for each abnormal exit. When abnormal behavior is detected, it is counted to obtain the number of times each type of abnormal behavior occurs. Normal behavior is added to the score, while abnormal behavior is subtracted from the score, calculating the real-time trust level. Therefore, whenever a user exhibits abnormal behavior, the real-time trust level is updated based on the normal and abnormal behaviors prior to the occurrence of the abnormal behavior.

[0119] Specifically, the formula for calculating real-time trust level is as follows:

[0120] ,

[0121] in, For real-time trust levels, To assess overall trust levels, The number of types of abnormal behavior. For the first Abnormal scores for various abnormal behaviors the number of abnormal behaviors, a normal score, the number of completed consultations. In some embodiments, the normal score is 0.05 points.

[0122] In some embodiments, step S6, according to the real-time trustworthiness, the access permission is managed, as shown in the following steps: Figure 5

[0123] S61, comparing the real-time trustworthiness with a trust threshold;

[0124] S62, when the real-time trustworthiness is less than the trust threshold, terminating the consultation session of the user;

[0125] S63, when the real-time trustworthiness is greater than or equal to the trust threshold, calculating a real-time difference value;

[0126] S64, when the real-time difference value is greater than or equal to zero, expanding the access permission;

[0127] S65, when the real-time difference value is less than zero, reducing the access permission;

[0128] S66, when the consultation session ends, recording a consultation score, and adding the consultation score to the historical access data.

[0129] It should be noted that during the consultation of the user, a continuous monitoring system for the whole consultation cycle needs to be established, the real-time trustworthiness of the user is calculated, and the access permission of the user is dynamically adjusted to ensure the security of the platform. The real-time trustworthiness is calculated by the comprehensive trustworthiness of the user and the consultation behavior score of the user. The higher the comprehensive trustworthiness of the user is, the higher the tolerance of the platform to the abnormal behavior of the user is. However, when the real-time trustworthiness decreases to the trust threshold, the platform will automatically terminate the consultation session of the user, and add the consultation score to the historical access data of the user for obtaining the access permission in the next consultation. In this case, the user with high comprehensive trustworthiness will record a lower consultation score, thereby seriously affecting the access permission in the next consultation. The real-time difference value is the difference between the real-time trustworthiness and the real-time trustworthiness at the last update time, and the access permission is controlled and managed in real time according to the real-time difference value. The dynamic adjustment of the access permission can obtain the initial permission in the decision tree according to the real-time trustworthiness, and the actual access permission is obtained by secondary screening of the initial permission. The consultation score is the difference between the real-time trustworthiness and the comprehensive trustworthiness when the consultation session ends, and the access permission in the next consultation is controlled and managed according to the consultation score.

[0130] ​​In the embodiment, by acquiring normal behavior and abnormal behavior of the user, dynamic response to the behavior change of the user, when the real-time trust degree of the user is low, the session is terminated in time, and the access permission of the user is dynamically adjusted according to the real-time trust degree, the consultation score of the user is stored to the historical access data, which provides a data basis for trust evaluation of future access of the user, and improves the security of the platform.

[0131] Embodiment two

[0132] The embodiment provides a network information consultation platform based on a zero trust architecture, and the network information consultation platform based on the zero trust architecture is applied to a communication method, as shown in the method, comprising an identity management module, a data acquisition module, a trust evaluation module, an access management module, a real-time monitoring module and an access management module. Figure 6

[0133] The identity management module is used for identity authentication of the user.

[0134] The data acquisition module is used for acquiring user data when the identity authentication is passed.

[0135] The trust evaluation module is used for inputting the user data into a trust evaluation model and outputting a comprehensive trust degree.

[0136] The access management module is used for acquiring access permission according to the comprehensive trust degree.

[0137] The real-time monitoring module is used for real-time monitoring of consultation behavior of the user and calculation of a real-time trust degree.

[0138] The access management module is used for management of the access permission according to the real-time trust degree.

[0139] In the embodiment, by acquiring user data of the user whose identity authentication is successful, the comprehensive trust degree of the user is calculated according to the user data to quantify the credit level of the user, the user is monitored throughout the consultation process, the access permission of the user is managed in combination with the credit level of the user and the real-time monitoring, and the security of the platform is improved.

[0140] It should be understood that the disclosed system can be implemented in other ways. For example, the system embodiments described above are only illustrative, for example, the division of the above modules is only a logical function division, and actual implementation can have another division mode, for example, a plurality of modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, each functional module can be integrated in one processing module, or each module can be physically independent, or two or more modules can be integrated in one module. The integrated module can be realized in the form of hardware or software function module. ​

[0141] Embodiment three

[0142] This embodiment provides an electronic device 2, such as Figure 7 As shown, the processor 21 and the memory 22, the memory 22 is used to store computer program code, the computer program code includes computer instructions, when the processor 21 executes the computer instructions, the electronic device executes the communication method of the network information consulting platform based on the zero trust architecture described above.

[0143] The electronic device 2 includes a processor 21, a memory 22, an output device 23, and an input device 24. The processor 21, the memory 22, the output device 23, and the input device 24 are coupled by a connector, which includes various interfaces, transmission lines, or buses, etc. The present embodiment is not limited in this regard. It should be understood that in various embodiments of the present application, coupling means mutual connection in a specific manner, including direct connection or indirect connection through other devices, for example, various interfaces, transmission lines, buses, etc.

[0144] The processor 21 can be one or more graphics processing units (GPU). In the case of the processor 21 being a GPU, the GPU can be a single-core GPU or a multi-core GPU. Alternatively, the processor 21 can be a processor group composed of multiple GPUs, and the multiple processors are coupled to each other through one or more buses. Alternatively, the processor 21 can be other types of processors, etc. The present embodiment is not limited in this regard.

[0145] The memory 22 can be used to store computer program instructions, as well as various types of computer program codes for executing the present application. Alternatively, the memory 22 includes but is not limited to random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), or compact disc read-only memory (CD-ROM), which is used for related instructions and data.

[0146] The input device 24 is used to input data and / or signals, and the output device 23 is used to output data and / or signals. The output device 23 and the input device 24 can be independent devices, or they can be a whole device.

[0147] The embodiment provides a computer readable storage medium, and the computer readable storage medium stores a computer program. The computer program comprises program instructions. When the program instructions are executed by a processor of an electronic device, the processor executes the communication method of the network information consultation platform based on the zero trust architecture.

[0148] The above merely describes the specific embodiments of the present application, so that those skilled in the art can understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A communication method of a network information consulting platform based on a zero-trust architecture, characterized in that, The method comprises the following steps: identity authentication is performed on a user; user data is obtained when the identity authentication is passed; the user data is input into a trust evaluation model to output a comprehensive trust degree; access permission is obtained according to the comprehensive trust degree; consultation behavior of the user is monitored in real time, and a real-time trust degree is calculated; the access permission is managed according to the real-time trust degree.

2. The communication method of the network information consulting platform based on the zero trust architecture according to claim 1, characterized in that, The user data is input into the trust evaluation model to output the comprehensive trust degree, which comprises the following steps: the user data is normalized to calculate a weight coefficient of each user data; a first trust degree is calculated according to the normalized user data and the weight coefficient; historical access data is obtained; a consultation score of each historical access data is obtained, and a time difference of the data is calculated; a second trust degree is calculated according to the consultation score and the time difference; the first trust degree and the second trust degree are weighted and summed to obtain the comprehensive trust degree.

3. The communication method of claim 2, wherein, The calculation formula of the first trust degree is as follows: ， wherein, is the first trust level, is the number of user data, is the weight coefficient of the user data, is the normalization value of the user data; The calculation formula of the second trust degree is as follows: ， in, As the second level of trust, The number of historical access data. The decay rate over time. For the first The time difference between the historical access data and the current access. For the first Consultation score of each historical access data; The calculation formula of the comprehensive trust degree is as follows: ， ， wherein, is a comprehensive trust degree, and is a weight coefficient, is a first trust degree, is a second trust degree.

4. The communication method of claim 2, wherein, The access permission is obtained according to the comprehensive trust degree, which comprises the following steps: consultation content is analyzed to obtain a consultation topic; a decision tree is selected according to the consultation topic; the comprehensive trust degree is compared with a trust threshold value, and initial permission is obtained from the decision tree according to a comparison result; the consultation topic is correlated with the initial permission; the initial permission is eliminated according to the correlation to obtain the access permission.

5. The communication method of claim 1, wherein, The consultation behavior of the user is monitored in real time to calculate the real-time trust degree, which comprises the following steps: the consultation behavior of the user is monitored in real time, and a completion frequency is recorded; when an abnormal behavior is monitored, an abnormal frequency is recorded, and an abnormal score is obtained; the real-time trust degree is calculated according to the completion frequency, the abnormal frequency and the abnormal score.

6. The communication method of claim 1, wherein, The calculation formula of the real-time trust degree is as follows: ， wherein, is a real-time trustworthiness, is a comprehensive trustworthiness, is a number of abnormal behavior categories, is an abnormal score of the abnormal behavior, is a number of abnormalities of the abnormal behavior, is a normal score, is a number of consultation completions.

7. The communication method of claim 1, wherein, The access permission is managed according to the real-time trust degree, which comprises the following steps: the real-time trust degree is compared with a trust threshold value; when the real-time trust degree is less than the trust threshold value, a consultation session of the user is terminated; when the real-time trust degree is greater than or equal to the trust threshold value, a real-time difference value is calculated; when the real-time difference value is greater than or equal to zero, the access permission is expanded; when the real-time difference value is less than zero, the access permission is reduced; when the consultation session is ended, a consultation score is recorded, and the consultation score is added to the historical access data. 8.A network information consulting platform based on a zero-trust architecture, applying a communication method of a network information consulting platform based on a zero-trust architecture according to any one of claims 1 to 7, characterized in that, It comprises: an identity management module, a data acquisition module, a trust evaluation module, an access management module, a real-time monitoring module and an access management module; the identity management module is used for identity authentication of a user; the data acquisition module is used for obtaining user data when the identity authentication is passed; the trust evaluation module is used for inputting the user data into a trust evaluation model to output a comprehensive trust degree; the access management module is used for obtaining access permission according to the comprehensive trust degree; the real-time monitoring module is used for monitoring consultation behavior of the user in real time to calculate a real-time trust degree; The access management module is configured to manage the access right according to the real-time trust degree.

9. An electronic device, comprising: The electronic device comprises a processor and a memory, and the memory is configured to store computer program code, the computer program code comprising computer instructions, when the processor executes the computer instructions, the electronic device executes the communication method of the network information consulting platform based on the zero trust architecture according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program comprises program instructions, when the program instructions are executed by the processor of the electronic device, the processor executes the communication method of the network information consulting platform based on the zero trust architecture according to any one of claims 1 to 7.

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