A cross-domain traffic control method and device

Abstract

The application provides a cross-domain traffic control method and device, including: obtaining each service information of network traffic, and obtaining a similar feature character set of the service information; establishing a service feature fingerprint library according to the similar feature character set; obtaining a target traffic control strategy matched with the service feature fingerprint library from a traffic control strategy; and performing traffic control on the service information according to the target traffic control strategy. By obtaining the similar feature character set corresponding to the service information, establishing the service feature fingerprint library based on the similar feature character set, and making the service information have the fingerprint characteristics through the service feature fingerprint library, the traffic control strategy can accurately issue the target traffic control strategy based on the fingerprint characteristics, greatly improving the accuracy of the traffic control strategy in identifying the content of the service information, and effectively improving the fine management capability of the network traffic.

Description

Technical Field

[0001] This application relates to the field of network data transmission technology, and in particular to a cross-domain traffic control method and apparatus. Background Technology

[0002] Traffic control strategies typically employ principles like token rings and leaky buckets to drop specific business information at a fixed rate. However, this approach struggles to achieve precise flow control over specific content, leading to the mismanagement of traffic from shared business information under the same IP address. For instance, existing traffic control strategies have difficulty distinguishing between specific business functions such as live streaming, video-on-demand, advertising, video, and images. If the controlled business is live streaming, since all of these functions reuse the same IP / domain, video-on-demand, advertising, video, and image traffic will be mismanaged.

[0003] It should be noted that the above introduction to the technical background is only for the purpose of providing a clear and complete explanation of the technical solutions of this application and facilitating understanding by those skilled in the art. It should not be assumed that these technical solutions are known to those skilled in the art simply because they have been described in the background section of this application. Summary of the Invention

[0004] This application provides a cross-domain traffic control method and apparatus.

[0005] The first aspect of this application proposes a cross-domain traffic control method, including:

[0006] Obtain each service information of the network traffic, and obtain a set of similar feature characters of the service information;

[0007] Based on the set of similar characteristic characters, a business feature fingerprint database is established;

[0008] Obtain the target traffic control policy that matches the business feature fingerprint database from the traffic control policies;

[0009] Traffic control is applied to the business information according to the target traffic control strategy.

[0010] A second aspect of this application provides a cross-domain flow control device, comprising:

[0011] The first acquisition module is used to acquire each service information of the network traffic and a set of similar feature characters of the service information.

[0012] The module is configured to establish a business feature fingerprint database based on the set of similar feature characters.

[0013] The second acquisition module is used to acquire a target traffic control policy that matches the business feature fingerprint database from the traffic control policy.

[0014] The management module is used to manage the traffic of the business information according to the target traffic management strategy.

[0015] A third aspect of this application provides an electronic device, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the cross-domain flow control method proposed in the first aspect of this application.

[0016] A fourth aspect of this application provides a non-transitory computer-readable storage medium that, when instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to perform the method proposed in the first aspect of this application.

[0017] A fifth aspect of this application provides a computer program product including a computer program that, when executed by a processor in a communication device, implements the method proposed in the first aspect of this application.

[0018] The technical solutions provided by the embodiments of this application bring at least the following beneficial effects:

[0019] By acquiring a set of similar characteristic characters corresponding to business information, a business characteristic fingerprint database is established based on the set of similar characteristic characters. The business characteristic fingerprint database gives the business information fingerprint characteristics. Traffic control policies are accurately issued to the target traffic control policies based on the fingerprint characteristics, which greatly improves the accuracy of traffic control policies in identifying business information content and effectively enhances the ability to manage network traffic in a refined manner.

[0020] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0021] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0022] Figure 1 This is a schematic flowchart of a cross-domain traffic control method provided in an embodiment of this application;

[0023] Figure 2 This is a schematic diagram of another cross-domain traffic control method provided in an embodiment of this application;

[0024] Figure 3This is a schematic diagram of the structure of a cross-domain flow control device provided in an embodiment of this application;

[0025] Figure 4 This is a schematic diagram illustrating a set of similar feature characters for obtaining business information provided in an embodiment of this application.

[0026] Figure 5 A schematic diagram illustrating the process of establishing a business feature fingerprint database as provided in an embodiment of this application;

[0027] Figure 6 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application;

[0028] Figure 7 This is a schematic diagram of the structure of another electronic device provided according to an embodiment of this application. Detailed Implementation

[0029] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0030] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the embodiments of this application. The singular forms “a” and “the” as used in the embodiments of this application and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0031] It should be understood that although the terms first, second, third, etc., may be used to describe various information in the embodiments of this application, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words "if" and "suppose" as used herein can be interpreted as "when," "when," or "in response to a determination."

[0032] Embodiments of this application 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 throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0033] It should be noted that the cross-domain traffic control method provided in any embodiment of this application can be executed alone, or can be executed together with possible implementation methods in other embodiments, or can be executed together with any technical solution in related technologies.

[0034] The cross-domain traffic control method and apparatus of this application are described below with reference to the accompanying drawings.

[0035] Figure 1 This is a schematic flowchart of a cross-domain traffic control method provided in an embodiment of this application. Figure 1 As shown, the method includes, but is not limited to, the following steps:

[0036] S101, Obtain each service information of the network traffic, and obtain a set of similar feature characters of the service information.

[0037] In an optional implementation, the service information of the network traffic is related to the network domain in which the network traffic resides. If the network traffic belongs to the XDR domain (Extended Detection and Response, a unified security solution that integrates security data from various sources and layers, such as networks and terminal devices, into a single platform to achieve broader and deeper threat detection, analysis, and response. XDR is an integrated, automated, and intelligent security solution that provides broader and deeper threat detection, analysis, and response. XDR aims to improve the efficiency and effectiveness of enterprise security teams through automation, intelligence, and high integration), the service functions of the XDR domain are traversed through a service device (e.g., an application, i.e., an APP). During the operation, the network traffic passes through the interface gateway of the service device in real time, receives the collection request from the service device, identifies the service information of the network traffic, and obtains the target routing information database and target content information database from the collection request. Specifically, based on the target content information database, each type of character in the network traffic is obtained.

[0038] As examples, type characters include URL (Uniform Resource Locator, used to locate resources on the Internet, also known as a website address or network address. A URL typically consists of a protocol, domain name, port number, path, query string, and fragment identifier. The URL is the foundation for locating Internet resources; by entering or clicking a URL through a browser or other tools, users can access the corresponding network resources), web server (host, which can communicate with other machines, specifies how data is transmitted over the network, and defines the format and path of the data transmitted over the network), urilength (usually refers to the length of the URI; URI stands for Uniform Resource Identifier. A URI is a standard format used to identify resources on the Internet, including a Uniform Resource Locator and a Uniform Resource Name. When designing and using URIs, it is essential to control their length appropriately, follow relevant standards and best practices, to ensure system compatibility, availability, and security), content-type (defining the type of network file and the encoding of the webpage, determining how the browser will read the file in what form and encoding), and content length (the size of the entity in the message in bytes, including all the content of the entity), etc. Based on the characteristics of the type characters themselves, type characters are reasonably classified, and similar type characters are grouped together to form a set of similar characteristic characters, that is, like groups are grouped together and dissimilar groups are dissimilar.

[0039] S102, Establish a business feature fingerprint database based on the set of similar feature characters.

[0040] In an optional implementation, functional fingerprints are mined from sets of similar characteristic characters. Functional fingerprint mining involves collecting and storing features from sets of similar characteristic characters in a data warehouse. This involves deep analysis and processing of these sets to extract various feature parameters, such as protocols, traffic patterns, and packet sizes, to obtain feature fingerprints corresponding to each set of similar character characters. Feature fingerprints can be used to identify and distinguish different content, such as video, audio, and images. The ability to identify feature fingerprints is crucial for content delivery networks (CDNs) because fingerprints are unique. This identification capability helps CDNs intelligently distribute and cache content based on its type, thereby improving content transmission efficiency and user access speed. With the increasing threat of network security, a large amount of malicious traffic exists in the network, such as viruses, Trojans, and DDoS attacks. A business feature fingerprint database can quickly and accurately identify this malicious traffic based on its feature extraction and matching capabilities, thereby helping CDNs filter and process it, ensuring network security. The business feature fingerprint database can also analyze the network characteristics of users accessing content, understanding user behavior and preferences, and thus providing more personalized services. This analytical capability has significant commercial value for CDN operators, providing data support for precision marketing and personalized recommendations.

[0041] S103: Obtain the target traffic control policy that matches the business feature fingerprint database from the traffic control policy.

[0042] In optional implementations, traffic control, also known as traffic management, is based on the current network traffic status and relevant legal regulations. It involves identifying and classifying network traffic and performance, and implementing traffic control, optimization, and protection for critical IT applications. As an example, the network traffic in the XDR domain, from acquiring business information and extracting similar characteristic character sets to establishing a business characteristic fingerprint database, all have significant time attributes. That is, each process from acquiring business information to establishing the business characteristic fingerprint database has a corresponding timestamp associated with it. The timestamp is data generated using digital signature technology. The signed object includes original file information, signature parameters, signature time, etc., used to prove that the content of each process is complete and has not been altered. As an example, the domain implementing the traffic control policy includes the NetFlow traffic control domain. NetFlow is a network packet switching technology used for network monitoring. It can collect the number and information of IP packets entering and leaving the network interface, and analyze them to obtain the source and destination of the packets, the type of network service, and the causes of network congestion. Specifically, by monitoring network traffic information in real time and matching it with historical data patterns or abnormal patterns, network administrators can view the overall network status in real time, monitor potential network performance bottlenecks, and automatically handle or display alarms to ensure efficient and reliable network operation. NetFlow provides a session-level view of network traffic, recording information for each TCP / IP transaction. By simply matching feature fingerprints, the target content of network traffic in the XDR domain can be obtained. As an example, NetFlow can correlate information such as the five-tuple information, the number of uplink and downlink packets, and data traffic in network traffic based on timestamps to obtain target traffic control policies that match the service feature fingerprint database.

[0043] S104, Perform traffic control on business information according to the target traffic control strategy.

[0044] In optional implementations, the target traffic control policy monitors and adjusts network traffic based on information about the source and destination of network traffic, the protocols and ports used in end-to-end sessions, and effectively allocates bandwidth to the network. If the content of the network traffic complies with relevant laws and regulations, the target traffic control policy only needs to monitor information such as the packet forwarding rate of device ports, network latency, packet loss rate, and changes in the CPU utilization of network devices. If the content of the network traffic does not comply with relevant laws and regulations, the target traffic control policy can filter or restrict abnormal network traffic to reduce the negative impact and losses caused by abnormal network traffic.

[0045] In summary, by acquiring a set of similar characteristic characters corresponding to business information, establishing a business characteristic fingerprint database based on the set of similar characteristic characters, and using the business characteristic fingerprint database to give business information fingerprint characteristics, traffic control strategies can accurately issue target traffic control strategies based on fingerprint characteristics, which greatly improves the accuracy of traffic control strategies in identifying business information content and effectively enhances the ability to manage network traffic in a refined manner.

[0046] Figure 2 This is a schematic diagram of another cross-domain traffic control method provided in an embodiment of this application. Figure 2 As shown, the method includes, but is not limited to, the following steps:

[0047] S201, extract each type of character from the business information.

[0048] For a detailed description of step S201, please refer to the relevant content in the above embodiments, which will not be repeated here.

[0049] S202, quantify the degree of difference of type characters based on target routing information and target content information, and obtain a set of similar feature fields.

[0050] In an optional implementation, edit distance is calculated for the type character based on the target routing information and target content information to obtain the edit distance value corresponding to the type character. It should be noted that edit distance, also known as Levinstein distance, is a quantitative measure of the difference between two strings. The measurement method is to see the minimum number of processing steps required to transform one string into another; the fewer the processing steps, the smaller the difference between the two strings. Specifically, a format conversion operation is performed on the type character to obtain the corresponding string; the string is discretized and preprocessed to obtain the first sequence corresponding to the string; and the edit distance operation is performed on each element in the first sequence to obtain the edit distance value corresponding to the type character.

[0051] After obtaining the edit distance values ​​corresponding to the type characters, hierarchical clustering is performed on these edit distance values ​​to obtain the feature fields of the type characters. Then, similarity matching is performed on these feature fields to obtain a set of similar feature fields. Specifically, the similarity between each pair of feature fields is obtained; pairs of feature fields with similarity greater than a similarity threshold are selected as candidate feature fields. The similarity threshold should be set according to actual needs; the specific setting process will not be elaborated here. Based on the candidate feature fields, a set of similar feature fields is obtained; and based on the obtained set of similar feature fields, a clustering structure tree diagram of the similar feature field set is obtained.

[0052] As an example, hierarchical clustering can be used to obtain a set of similar feature fields. Hierarchical clustering is a clustering method whose basic idea is to initially treat each sample as a cluster, then find the two clusters with the closest edit distance and merge them, repeating this process until a preset stopping condition is met (such as the number of clusters reaching a certain threshold, or the distance between clusters exceeding a certain threshold). Hierarchical clustering operations include:

[0053] ① Initialization: Treat each feature field as a separate cluster. If there are n feature fields, there will be n clusters.

[0054] Where n≥1, and n is a positive integer;

[0055] ② Calculate the edit distance between clusters. Based on the selected hierarchical clustering method (such as single link, full link, average link, centroid link, etc.), calculate the edit distance between clusters.

[0056] ③ Merge the nearest clusters: Find the two clusters with the closest edit distance and merge them into a new cluster;

[0057] ④ Update the distance between clusters and recalculate the edit distance between clusters based on the new cluster set;

[0058] ⑤ Repeat steps ③ and ④, continuously merging and updating the edit distance until the stopping condition is met (such as a preset number of clusters, or the distance between clusters reaching a certain threshold).

[0059] ⑥ Output the results; the final cluster is the result of hierarchical clustering.

[0060] It should be noted that the operation of obtaining the set of similar feature fields includes, but is not limited to, hierarchical clustering. Other methods for obtaining the set of similar feature fields include balanced iterative reduction clustering, centroid-based and representative object-based clustering, and merging based on inter-cluster interconnection. The specific acquisition process will not be elaborated here, and the appropriate method should be selected according to the actual needs.

[0061] For further details on step S202, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0062] S203. Establish a business feature fingerprint database based on the set of similar feature characters.

[0063] In an optional implementation, target content recognition is performed on each candidate feature field in the set of similar feature characters to obtain feature fingerprints corresponding to each set of similar feature characters. Feature fingerprints can be used to identify and distinguish different content. Due to the uniqueness of feature fingerprints, their recognition capability is crucial for content delivery networks. This recognition capability can help content delivery networks intelligently distribute and cache content based on content type, thereby improving content transmission efficiency and user access speed.

[0064] For further details on step S203, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0065] S204. Obtain the target traffic control policy that matches the business feature fingerprint database from the traffic control policy.

[0066] In an optional implementation, a target traffic control policy matching the business feature fingerprint database is obtained from the traffic control policy based on the time information of the business information. According to the target traffic control policy, network traffic and performance are identified and classified, and traffic control, optimization, and protection of critical IT applications are implemented.

[0067] For further details on step S204, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0068] S205, Perform traffic control on business information according to the target traffic control strategy.

[0069] In an optional implementation, a session request is generated according to the target traffic control policy, and traffic control of the service information is performed based on the control information carried in the session request.

[0070] For further details on step S205, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0071] In summary, by acquiring a set of similar characteristic characters corresponding to business information, establishing a business characteristic fingerprint database based on the set of similar characteristic characters, and using the business characteristic fingerprint database to give business information fingerprint characteristics, traffic control strategies can accurately issue target traffic control strategies based on fingerprint characteristics, which greatly improves the accuracy of traffic control strategies in identifying business information content and effectively enhances the ability to manage network traffic in a refined manner.

[0072] Figure 3 This is a schematic diagram of a cross-domain flow control device provided in an embodiment of this application. Figure 3 As shown, the cross-domain flow control device 300 includes:

[0073] like Figure 3As shown, the first acquisition module 301 is used to acquire each service information of the network traffic and a set of similar feature characters of the service information. As an example, the network traffic is provided by the XDR domain.

[0074] Alternatively, as an example, Figure 4 This is a schematic diagram illustrating a set of similar feature characters for obtaining business information, as provided in an embodiment of this application. For example... Figure 4 As shown, the first acquisition module extracts each type of character from the business information, and quantifies the degree of difference of the type characters based on the target routing information and the target content information to obtain a set of similar feature fields.

[0075] Among these, quantifying the degree of difference in type characters includes:

[0076] Based on the target routing information and the target content information, the edit distance of the type character is calculated to obtain the edit distance value corresponding to the type character. Further, a format conversion operation is performed on the type character to obtain the corresponding string; the string is discretized and preprocessed to obtain a first sequence corresponding to the string; and an edit distance operation is performed on each element in the first sequence to obtain the edit distance value corresponding to the type character.

[0077] Hierarchical clustering is performed on the edit distance values ​​corresponding to the type characters to obtain the feature fields of the type characters, and similarity matching is performed on the feature fields to obtain the set of similar feature fields. Further, the similarity between pairwise feature fields is obtained; pairwise feature fields with similarity greater than a similarity threshold are selected as candidate feature fields; and a set of similar feature fields is obtained based on the candidate feature fields.

[0078] For further details on obtaining the set of similar feature fields, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0079] like Figure 3 As shown, module 302 is used to establish a business feature fingerprint database based on a set of similar feature characters.

[0080] Alternatively, as an example, Figure 5 This is a schematic diagram illustrating the process of establishing a business feature fingerprint database as provided in an embodiment of this application. Figure 5 As shown, the module performs target content recognition on each candidate feature field in the similar feature character set to obtain the feature fingerprint corresponding to each similar feature character set.

[0081] For further details on establishing a business feature fingerprint database, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0082] like Figure 3As shown, the second acquisition module 303 is used to acquire a target traffic control policy that matches the business feature fingerprint database from the traffic control policies. As an example, the traffic control policy is provided by the NetFlow traffic control domain.

[0083] Optionally, as an example, based on the time information of the business information, the target traffic control policy that matches the business feature fingerprint database is obtained from the traffic control policy.

[0084] For further details on obtaining target traffic control policies, please refer to the relevant descriptions in the above embodiments, which will not be repeated here.

[0085] like Figure 3 As shown, the control module 304 is used to control the traffic of business information according to the target traffic control strategy.

[0086] Optionally, as an example, a session request is generated according to the target traffic control policy, and traffic control of business information is performed based on the control information carried in the session request.

[0087] For further details on traffic control of business information, please refer to the relevant content in the above embodiments, which will not be repeated here.

[0088] In summary, by acquiring a set of similar characteristic characters corresponding to business information, establishing a business characteristic fingerprint database based on the set of similar characteristic characters, and using the business characteristic fingerprint database to give business information fingerprint characteristics, traffic control strategies can accurately issue target traffic control strategies based on fingerprint characteristics, which greatly improves the accuracy of traffic control strategies in identifying business information content and effectively enhances the ability to manage network traffic in a refined manner.

[0089] Figure 6 This is a block diagram of an electronic device according to an exemplary embodiment. Figure 6 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0090] like Figure 6As shown, the electronic device 600 includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from memory 606 into a random access memory (RAM) 603. The RAM 603 also stores various programs and data required for the operation of the electronic device 600. The processor 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0091] The following components are connected to I / O interface 605: memory 606 including hard disk; and communication section 607 including network interface card such as LAN (Local Area Network) card, modem, etc., which performs communication processing via a network such as the Internet; and driver 608 is also connected to I / O interface 605 as needed.

[0092] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 607. When the computer program is executed by processor 601, it performs the functions defined in the methods of this application.

[0093] In an exemplary embodiment, a storage medium including instructions is also provided, such as a memory including instructions, which can be executed by a processor 601 of an electronic device 600 to perform the above-described method. Optionally, the storage medium may be a non-transitory computer-readable storage medium, such as a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device.

[0094] In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can transmit, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wireline, optical fiber, RF, etc., or any suitable combination thereof.

[0095] Figure 7 This is a structural block diagram of an electronic device according to an exemplary embodiment. Figure 7 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of this application. Figure 7 As shown, the electronic device 700 includes a processor 701 and a memory 702. The memory 702 is used to store program code, and the processor 701 is connected to the memory 702 to read program code from the memory 702 to implement the cross-domain flow control method in the above embodiment.

[0096] Alternatively, the number of processors 701 can be one or more.

[0097] Optionally, the electronic device may also include an interface 703, and there may be multiple interfaces 703. The interface 703 can be connected to an application and can receive data from external devices such as sensors.

[0098] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0099] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A cross-domain flow control method, characterized in that, include: Obtain each service information of the network traffic, and obtain a set of similar feature characters of the service information; Based on the set of similar characteristic characters, a business feature fingerprint database is established; Obtain the target traffic control policy that matches the business feature fingerprint database from the traffic control policies; Traffic control is applied to the business information according to the target traffic control strategy. Specifically, each type of character in the business information is extracted; The difference degree of the type characters is quantified based on the target routing information and the target content information to obtain the set of similar feature characters. Specifically, the edit distance of the type characters is calculated based on the target routing information and the target content information to obtain the edit distance value corresponding to the type characters. Furthermore, the type characters undergo format conversion to obtain the corresponding strings; the strings are discretized and preprocessed to obtain a first sequence corresponding to the strings; and edit distance operations are performed on each element in the first sequence to obtain the edit distance value corresponding to the type characters. Hierarchical clustering is performed on the edit distance values ​​corresponding to the type characters to obtain the feature fields of the type characters, and similarity matching is performed on the feature fields to obtain the set of similar feature characters.

2. The method according to claim 1, characterized in that, The step of performing similarity matching on the feature fields to obtain the set of similar feature characters includes: Obtain the similarity between pairwise feature fields; Select pairwise feature fields with a similarity greater than the similarity threshold as candidate feature fields; Based on the candidate feature fields, obtain a set of similar feature characters.

3. The method according to claim 1, characterized in that, The step of establishing a business feature fingerprint database based on the set of similar feature characters includes: Target content recognition is performed on each candidate feature field in the set of similar feature characters to obtain feature fingerprints corresponding to each set of similar feature characters.

4. The method according to claim 1, characterized in that, The step of obtaining the target traffic control policy that matches the business feature fingerprint database from the traffic control policies includes: Based on the time information of the business information, the target traffic control policy that matches the business feature fingerprint database is obtained from the traffic control policy.

5. The method according to claim 1, characterized in that, The step of controlling traffic to the service information according to the target traffic control strategy includes: Based on the target traffic control policy, a session request is generated, and traffic control is performed on the service information based on the control information carried in the session request.

6. A cross-domain flow control device, characterized in that, include: The first acquisition module is used to acquire each service information of the network traffic and a set of similar feature characters of the service information. The module is configured to establish a business feature fingerprint database based on the set of similar feature characters. The second acquisition module is used to acquire a target traffic control policy that matches the business feature fingerprint database from the traffic control policy. The control module is used to control the traffic of the service information according to the target traffic control strategy; The first acquisition module is further configured to extract each type of character from the business information; The difference degree of the type characters is quantified based on the target routing information and the target content information to obtain the set of similar feature characters. Specifically, the edit distance of the type characters is calculated based on the target routing information and the target content information to obtain the edit distance value corresponding to the type characters. Furthermore, the type characters undergo format conversion to obtain the corresponding strings; the strings are discretized and preprocessed to obtain a first sequence corresponding to the strings; and edit distance operations are performed on each element in the first sequence to obtain the edit distance value corresponding to the type characters. Hierarchical clustering is performed on the edit distance values ​​corresponding to the type characters to obtain the feature fields of the type characters, and similarity matching is performed on the feature fields to obtain the set of similar feature characters.

7. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the method as described in any one of claims 1 to 5.

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