A multi-level fingerprint identification method and device, electronic equipment and storage medium

Abstract

The application relates to a multi-level fingerprint identification method and device, electronic equipment and a storage medium. A plurality of identification request packets are sent to each to-be-identified device, and each identification request packet corresponds to a standard identification object; a plurality of pieces of fingerprint information sent by each to-be-identified device are received; for each to-be-identified device, a corresponding first standard identification object is matched in a hotspot fingerprint library based on the plurality of pieces of fingerprint information, the hotspot fingerprint library comprises a plurality of hotspot standard identification objects, and each hotspot standard identification object corresponds to a plurality of pieces of hotspot standard fingerprint information; for any piece of fingerprint information, if the piece of fingerprint information does not have a corresponding first standard identification object, a corresponding second standard identification object is matched in a full fingerprint library based on a hash function and the piece of fingerprint information, the full fingerprint library comprises a plurality of standard identification objects; and the first standard identification object and the plurality of second standard identification objects are determined as to-be-identified objects of the corresponding to-be-identified device.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a multi-level fingerprint recognition method, apparatus, electronic device and storage medium. Background Technology

[0002] With the development of the internet, network security faces increasing challenges. To ensure a successful penetration test or network device monitoring of a system, it is essential to know the service fingerprints within that system. Service fingerprints include service ports, service names, and versions. There may be many target systems to be identified, and each target system may contain many service ports to be identified. Each service port may also correspond to different fingerprint formats. Therefore, efficiently identifying fingerprint information to determine which service ports are present in the target systems is particularly important.

[0003] Currently, fingerprint recognition typically involves comparing the received system response with information in a general fingerprint database to analyze the fingerprint information. However, general fingerprint databases contain numerous service ports to be identified, resulting in a massive amount of fingerprint information. This leads to a lengthy fingerprint recognition process and slow fingerprint recognition speed. Summary of the Invention

[0004] To address the above technical problems, this application provides a multi-level fingerprint recognition method, apparatus, electronic device, and storage medium.

[0005] In a first aspect, this application provides a multi-level fingerprint recognition method, comprising:

[0006] Send several identification request packets to each device to be identified, and each identification request packet corresponds to a standard identification object;

[0007] Receive several fingerprint information messages sent by each device to be identified, where each fingerprint information message is generated by the corresponding device to be identified based on a corresponding identification request packet;

[0008] For each device to be identified, a first standard identification object is matched in the hotspot fingerprint database based on the several fingerprint information. The hotspot fingerprint database includes several hotspot standard identification objects, and each hotspot standard identification object corresponds to several hotspot standard fingerprint information.

[0009] For any fingerprint information, if there is no corresponding first standard identification object for the fingerprint information, then based on the hash function and the fingerprint information, a corresponding second standard identification object is matched in the full fingerprint database. The full fingerprint database includes several standard identification objects, and each standard identification object corresponds to several standard fingerprint information. The number of hot spot standard identification objects is less than the number of standard identification objects, and the number of hot spot standard fingerprint information corresponding to each hot spot standard identification object is less than the number of corresponding standard fingerprint information.

[0010] The first standard identification object and several second standard identification objects are determined as the identification objects of the device to be identified.

[0011] By adopting the above technical solution, the matching speed is faster because the number of standard fingerprint information in the hotspot fingerprint database is relatively small. If a fingerprint does not match the first standard object, it can be matched in the entire fingerprint database. During matching, a hash function can be used, and the amount of data processed is small. Therefore, the matching speed is also fast in the large fingerprint database, thus improving the overall fingerprint recognition speed.

[0012] Optionally, the method further includes:

[0013] Based on big data, several selectable objects to be identified are determined for each device to be identified;

[0014] Obtain several standard request formats corresponding to each selectable object to be identified, and generate several corresponding identification request packages according to the several standard request formats;

[0015] The step of sending several identification request packets to each device to be identified includes:

[0016] Send several identification request packets to each device to be identified.

[0017] By adopting the above technical solution, several selectable objects to be identified for each device to be identified can be determined based on big data, and several identification request packets corresponding to each device to be identified can be generated in a targeted manner. This avoids the time occupied by the device to be identified in responding to irrelevant identification request packets, speeds up the speed at which the fingerprint recognition device receives the corresponding fingerprint information, and speeds up the overall fingerprint recognition speed.

[0018] Optionally, for each device to be identified, matching the corresponding first standard identification object in the hotspot fingerprint database based on the plurality of fingerprint information includes:

[0019] For each device to be identified, analyze the corresponding fingerprint information to determine the number of fingerprint features for each device.

[0020] For any fingerprint information, if the number of corresponding fingerprint features is within the preset range of fingerprint feature numbers, then the corresponding first standard identification object is matched in the hotspot fingerprint database based on the fingerprint information.

[0021] The method further includes:

[0022] Configure the request parameters for the plurality of identification request packets to send a plurality of configured identification request packets to each device to be identified. The request parameters include request frequency, number of retries and timeout settings.

[0023] If any of the fingerprint information is not empty and the corresponding number of fingerprint features is not within the preset number of fingerprint features, then the identification request packet corresponding to the fingerprint information is repeatedly sent to the corresponding identification device according to the corresponding request frequency, the number of retries and the corresponding timeout setting.

[0024] By adopting the above technical solution, it is possible to determine whether each fingerprint can be matched with hotspot standard fingerprint information by comparing the number of fingerprint features in each fingerprint with the preset range of fingerprint feature numbers. If the fingerprint information is incorrect and cannot be matched, the corresponding recognition request packet is resent according to the settings of the request parameters. This avoids wasting a lot of time on directly matching incorrect fingerprint information, thereby maximizing the recognition success rate and reducing erroneous recognition caused by network or device instability.

[0025] Optionally, the construction of the hotspot fingerprint database includes:

[0026] Analyze the general fingerprint information in the general fingerprint database, identify fingerprint information with an access frequency greater than or equal to a preset access frequency threshold, and add it to the hotspot fingerprint database to be built.

[0027] Record the objects to be identified for each device in real time and update the historical objects to be identified.

[0028] Based on the updated historical objects to be identified, the historical objects to be identified are sorted according to the identification frequency of each object;

[0029] For each update, the hotspot fingerprint database to be built is updated based on the latest access frequency of the general fingerprint database, the updated sorting of historical objects to be identified, and the preset update requirements, thus obtaining the hotspot fingerprint database.

[0030] By adopting the above technical solution, a hotspot fingerprint database is built upon the general fingerprint information in the general fingerprint database. Then, based on each update of the historical objects to be identified, the hotspot fingerprint database is updated, ensuring that the objects to be identified in the hotspot fingerprint database are the most recent and frequently identified objects at the current moment. In actual fingerprint recognition, frequently identified objects are generally the majority, making this hotspot fingerprint database highly practical. If fingerprint information is included in the hotspot fingerprint database, there is no need for subsequent comparison with the entire fingerprint database, thus speeding up fingerprint recognition.

[0031] Optional, building a full fingerprint database includes:

[0032] In real time, the local fingerprint information of each device to be identified is acquired from the authorized fingerprint database, the general fingerprint database, and the voluntarily provided fingerprint database, and then summarized into comprehensive fingerprint information.

[0033] Each integrated fingerprint information is stored under the name tag of the corresponding object to be identified;

[0034] The hash value of each comprehensive fingerprint information is calculated based on a hash function, and the relationship between the hash value and the corresponding name tag is established to generate a full fingerprint database. The name tag corresponding to the hash value of the fingerprint information is determined according to the relationship, and the corresponding object to be identified is determined.

[0035] By adopting the above technical solution, comprehensive fingerprint information is updated in real time based on partial fingerprint information from authorized fingerprint databases, general fingerprint databases, and voluntarily provided fingerprint databases. Each piece of comprehensive fingerprint information is converted into a corresponding hash value using a hash function and stored. A relationship is established between this hash value and its corresponding storage location, so that the corresponding storage location, i.e., the name tag of the object to be identified, can be found during subsequent matching. Although the total number of fingerprints in the full fingerprint database is enormous, the relationship between hash values ​​and their corresponding storage locations speeds up fingerprint identification within the entire database.

[0036] Optionally, the step of matching the corresponding second standard identification object in the full fingerprint database based on the hash function and the fingerprint information includes:

[0037] Calculate the hash value corresponding to this fingerprint information;

[0038] Using the corresponding hash value as the query condition, the standard fingerprint information corresponding to the fingerprint information is quickly matched in the full fingerprint database;

[0039] Based on the standard fingerprint information and the relationship, the corresponding second standard identification object is determined.

[0040] By employing the above technical solution, fingerprint information can be converted into hash values. Using these hash values ​​as query criteria, standard fingerprint information with the same hash value can be quickly found in the entire fingerprint database. Then, based on the storage location of this standard fingerprint information, i.e., the name tag corresponding to the hash value, the second standard identification object can be determined. This method achieves the goal of rapid matching in the entire fingerprint database.

[0041] Optionally, the method further includes:

[0042] Activate the third-party plugin to scan the device to be identified;

[0043] The system receives the scanned and identified objects obtained by the third-party plugin, and combines the scanned and identified objects with the objects to be identified to obtain the actual identified objects of the devices to be identified.

[0044] By adopting the above technical solution, the objects to be identified in the hotspot database and the full database, as well as the scanned objects obtained by third-party devices, are used together as the actual objects to be identified by the device, thereby improving the accuracy of fingerprint recognition results.

[0045] Secondly, this application provides a multi-level fingerprint recognition device, comprising:

[0046] The identification request packet sending module is used to send several identification request packets to each device to be identified, and each identification request packet corresponds to a standard identification object.

[0047] The fingerprint information receiving module is used to receive several fingerprint information sent by each device to be identified, and each fingerprint information is generated by the corresponding device to be identified according to a corresponding identification request packet.

[0048] The first standard identification object determination module is used to match the corresponding first standard identification object in the hot spot fingerprint database based on the several fingerprint information. The hot spot fingerprint database includes several hot spot standard identification objects, and each hot spot standard identification object corresponds to several hot spot standard fingerprint information.

[0049] The second standard identification object determination module is used to, for any fingerprint information, if there is no corresponding first standard identification object for the fingerprint information, match the corresponding second standard identification object in the full fingerprint database based on the hash function and the fingerprint information. The full fingerprint database includes a number of standard identification objects, and each standard identification object corresponds to a number of standard fingerprint information. The number of hot spot standard identification objects is less than the number of standard identification objects, and the number of hot spot standard fingerprint information corresponding to each hot spot standard identification object is less than the number of corresponding standard fingerprint information.

[0050] The object to be identified module is used to identify the first standard identification object and a plurality of second standard identification objects as the objects to be identified by the device to be identified.

[0051] Optionally, the multi-level fingerprint recognition device further includes a standard request format acquisition module, used for:

[0052] Based on big data, several selectable objects to be identified are determined for each device to be identified;

[0053] Obtain several standard request formats corresponding to each selectable object to be identified, and generate several corresponding identification request packages according to the several standard request formats;

[0054] The identification request packet sending module is specifically used for:

[0055] Send several identification request packets to each device to be identified.

[0056] Optionally, the first standard identification object determination module is specifically used for:

[0057] For each device to be identified, analyze the corresponding fingerprint information to determine the number of fingerprint features for each device.

[0058] For any fingerprint information, if the number of corresponding fingerprint features is within the preset range of fingerprint feature numbers, then the corresponding first standard identification object is matched in the hotspot fingerprint database based on the fingerprint information.

[0059] The multi-level fingerprint recognition device also includes a recognition request packet retransmission module, used for:

[0060] Configure the request parameters for the plurality of identification request packets to send a plurality of configured identification request packets to each device to be identified. The request parameters include request frequency, number of retries and timeout settings.

[0061] If any of the fingerprint information is not empty and the corresponding number of fingerprint features is not within the preset number of fingerprint features, then the identification request packet corresponding to the fingerprint information is repeatedly sent to the corresponding identification device according to the corresponding request frequency, the number of retries and the corresponding timeout setting.

[0062] Optionally, the multi-level fingerprint recognition device further includes a hotspot fingerprint database construction module, used for:

[0063] Analyze the general fingerprint information in the general fingerprint database, identify fingerprint information with an access frequency greater than or equal to a preset access frequency threshold, and add it to the hotspot fingerprint database to be built.

[0064] Record the objects to be identified for each device in real time and update the historical objects to be identified.

[0065] Based on the updated historical objects to be identified, the historical objects to be identified are sorted according to the identification frequency of each object;

[0066] For each update, the hotspot fingerprint database to be built is updated based on the latest access frequency of the general fingerprint database, the updated sorting of historical objects to be identified, and the preset update requirements, thus obtaining the hotspot fingerprint database.

[0067] Optionally, the multi-level fingerprint recognition device further includes a full fingerprint database construction module, used for:

[0068] In real time, the local fingerprint information of each device to be identified is acquired from the authorized fingerprint database, the general fingerprint database, and the voluntarily provided fingerprint database, and then summarized into comprehensive fingerprint information.

[0069] Each integrated fingerprint information is stored under the name tag of the corresponding object to be identified;

[0070] The hash value of each comprehensive fingerprint information is calculated based on a hash function, and the relationship between the hash value and the corresponding name tag is established to generate a full fingerprint database. The name tag corresponding to the hash value of the fingerprint information is determined according to the relationship, and the corresponding object to be identified is determined.

[0071] Optionally, the object determination module is specifically used for:

[0072] Calculate the hash value corresponding to this fingerprint information;

[0073] Using the corresponding hash value as the query condition, the standard fingerprint information corresponding to the fingerprint information is quickly matched in the full fingerprint database;

[0074] Based on the standard fingerprint information and the relationship, the corresponding second standard identification object is determined.

[0075] Optionally, the multi-level fingerprint recognition device further includes an actual identification object determination module, used for:

[0076] Activate the third-party plugin to scan the device to be identified;

[0077] The system receives the scanned and identified objects obtained by the third-party plugin, and combines the scanned and identified objects with the objects to be identified to obtain the actual identified objects of the devices to be identified.

[0078] Thirdly, this application provides an electronic device, including: a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute the method of the first aspect.

[0079] Fourthly, this application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and execute the method of the first aspect.

[0080] Fifthly, this application provides a computer program product, comprising: a computer program; wherein, when the computer program is executed by a processor, it implements the method described in any of the first aspects. Attached Figure Description

[0081] To more clearly illustrate the technical solutions in the embodiments of this application 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 some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0082] Figure 1 This is a schematic diagram illustrating an application scenario provided in one embodiment of this application;

[0083] Figure 2 A flowchart illustrating a multi-level fingerprint recognition method provided in an embodiment of this application;

[0084] Figure 3 A schematic flowchart of a multi-level fingerprint recognition process provided in an embodiment of this application;

[0085] Figure 4 A flowchart illustrating a general request packet format generation process provided in an embodiment of this application;

[0086] Figure 5 A schematic diagram illustrating the source of fingerprint information in a full fingerprint database, provided as an embodiment of this application;

[0087] Figure 6 A schematic diagram of the structure of a multi-level fingerprint recognition device provided in an embodiment of this application;

[0088] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0089] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0090] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.

[0091] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0092] With the rapid development of the internet and the increasing prevalence of network applications, more and more data is stored on networks, correspondingly leading to greater challenges to network security. To successfully conduct penetration testing or network device monitoring of a system, it's necessary to know which service ports exist within that system and then conduct targeted testing on these ports to mitigate potential future security vulnerabilities. Currently, one approach is to send a fingerprint recognition request and compare the fingerprint information in the system's response with fingerprints in a general fingerprint database. This general fingerprint database is currently the most commonly used and comprehensive fingerprint database for fingerprint comparison. However, because it contains fingerprint information corresponding to many different service ports, and each service port has various fingerprint formats, the total amount of fingerprint information is enormous. The fingerprint comparison process is time-consuming, making the process of identifying which service ports the system uses based on the fingerprint comparison results very slow overall.

[0093] Based on this, this application provides a multi-level fingerprint recognition method, apparatus, electronic device, and storage medium. Frequently recognized service ports and their frequently used fingerprint formats are placed in a hotspot fingerprint database. When several fingerprints returned by the device to be identified are not included in the hotspot fingerprint database, these fingerprints are then matched against standard fingerprints in a pre-configured full fingerprint database, thus achieving multi-level fingerprint recognition. A hash function can be used in this process to achieve a fast matching process, improving the overall fingerprint recognition speed.

[0094] Figure 1 This illustration illustrates an application scenario provided by this application. A batch of devices to be identified store a significant amount of important data; interception of this data could result in substantial financial losses. In this case, it is necessary to perform fingerprint recognition on each device to determine which service ports are used on each device, thus identifying them as potential targets. This facilitates subsequent targeted testing of each target to patch vulnerabilities. Figure 1In application scenarios, fingerprint recognition devices can be used to execute the methods of this application. The fingerprint recognition device can send several recognition request packets to each device to be recognized and receive several corresponding fingerprint information packets. Then, these fingerprint information packets are compared layer by layer. When a fingerprint information is not included in the hotspot information database, it is matched with the fingerprint information in the next level's full fingerprint database. Simultaneously, a hash function is used, which improves the overall speed of fingerprint recognition.

[0095] For specific implementation details, please refer to the following examples.

[0096] Figure 2 This is a flowchart illustrating a multi-level fingerprint recognition method according to an embodiment of this application. The method of this embodiment can be applied to fingerprint recognition devices in the above scenarios. Figure 2 As shown, the method includes:

[0097] S201. Send several identification request packets to each device to be identified, with each identification request packet corresponding to a standard identification object.

[0098] The device to be identified can be a device that requires fingerprint recognition, and the identification request packet can be used to transmit signals for fingerprint information recognition. The standard identification object can be any service port that the fingerprint recognition device obtains through big data and that can be used by the device to be identified. The number of standard identification objects is greater than the number of service ports actually used by any given device to be identified. Each identification request packet can be used to request recognition of a corresponding standard identification object. When the same identification object is used on different devices to be identified, the format of the requests that the identification object can receive will differ due to the differences in the devices. For example, for the same identification request packet for the same identification object, device A can only read request a, but not requests b, c, etc., while device B can only read request c, but not requests a, b, etc. Therefore, the identification request packet for each standard identification object can contain several request formats.

[0099] Since the identification request packet is sent to the device to be identified to request identification of the service ports on the device, several identical identification request packets can be generated uniformly based on all standard identification objects. The fingerprint device can then send these generated identification request packets indiscriminately to each device to be identified. In some implementations, the identification request packets can also be generated separately based on the service ports that the device to be identified may have installed.

[0100] S202. Receive several fingerprint information sent by each device to be identified, where each fingerprint information is generated by the corresponding device to be identified based on a corresponding identification request packet.

[0101] When the device to be identified has one of the aforementioned standard identification objects, it can respond to the identification request packet corresponding to that standard identification object, and the response content is fingerprint information. Each identification request packet contains several request formats, so the standard identification object corresponding to the identification request packet can correspond to many different response formats. When the device to be identified responds to the identification request packet, it responds with the fingerprint information corresponding to the request format that it can read. Each device to be identified can contain several service ports, that is, it can contain several of the aforementioned standard identification objects. Each standard identification object corresponds to one identification request packet, but a response fingerprint information can be generated based on each identification request packet, and thus several fingerprint information corresponding to several identification request packets in step S201 above can be received.

[0102] Specifically, a fingerprint recognition device can receive several fingerprints from each device to be recognized.

[0103] S203. For each device to be identified, match the corresponding first standard identification object in the hot spot fingerprint database based on several fingerprint information. The hot spot fingerprint database includes several hot spot standard identification objects, and each hot spot standard identification object corresponds to several hot spot standard fingerprint information.

[0104] The hotspot fingerprint database can store fingerprint information corresponding to frequently identified standard recognition objects in big data. In addition, since each standard recognition object can have several fingerprint information formats, the hotspot fingerprint database can also store hotspot standard fingerprint information for frequently identified standard recognition objects. Hotspot standard fingerprint information can be several fingerprints corresponding to several request formats frequently received by fingerprint recognition devices. The standard recognition objects in the hotspot fingerprint database can serve as hotspot standard fingerprint objects.

[0105] The preset number of identification objects can be determined based on big data. When the number of standard identification objects in the hotspot fingerprint database is less than the preset number, fingerprint recognition is faster. For example, all objects to be identified can be sorted from highest to lowest frequency of identification, once a week. The top 3% of objects can be used, in whole or in part, as standard identification objects in the hotspot fingerprint database. The number of these top 3% can be used as the preset number of identification objects. Then, the fingerprint information corresponding to these standard identification objects can be sorted from highest to lowest frequency of response from the device to be identified to the fingerprint recognition device. The top 50% of fingerprint information can be used as the hotspot standard fingerprint information in the hotspot fingerprint database.

[0106] The standard identification object matched in the hotspot fingerprint database can be used as the first standard identification object.

[0107] In some implementations, batch analysis can be performed on each device to be identified. Several fingerprints responded by each device are matched against hotspot standard fingerprints in a hotspot fingerprint database. The matching result can include successful and unsuccessful matches. If successful, the standard identification object corresponding to the successfully matched fingerprints is taken as the first standard identification object. If unsuccessful, there are two possibilities: First, the fingerprint information is empty, meaning no match can be made. This indicates that the identification request packet corresponding to that fingerprint cannot be responded to, meaning the standard identification object corresponding to that identification request packet is not used by the device to be identified. Second, the fingerprint information is not frequently used and cannot be matched in the hotspot fingerprint database. Therefore, when a match fails, the first standard identification object can be empty.

[0108] In other implementations, a hash function can be used to calculate the fingerprint information of several fingerprints. Then, the calculation results can be matched with the corresponding calculation results in a hot fingerprint database to determine the matching result in the above implementation.

[0109] S204. For any fingerprint information, if there is no corresponding first standard identification object for the fingerprint information, then based on the hash function and the fingerprint information, a corresponding second standard identification object is matched in the full fingerprint database. The full fingerprint database includes several standard identification objects, and each standard identification object corresponds to several standard fingerprint information. The number of hot spot standard identification objects is less than the number of standard identification objects, and the number of hot spot standard fingerprint information corresponding to each hot spot standard identification object is less than the number of corresponding standard fingerprint information.

[0110] A hash function can map the content of an element to the storage location of that element; specifically, it can establish a correspondence between the content of the element and the storage location. The full fingerprint database can include the general fingerprint database in the above embodiments, the fingerprint database used by the fingerprint recognition device to store fingerprint information during the recognition process, etc., and contains the most comprehensive set of standard recognition objects and their corresponding fingerprint information. The full fingerprint database can include the hotspot fingerprint database in step S203 above, wherein the number of standard recognition objects in the full fingerprint database is greater than the number of hotspot standard recognition objects in the hotspot fingerprint database. Specifically, the number of standard recognition objects in the full fingerprint database is greater than the number of standard recognition objects in the hotspot fingerprint database, i.e., greater than the number of hotspot standard recognition objects. For each standard recognition object, the number of corresponding hotspot standard fingerprint information is less than the number of standard fingerprint information.

[0111] The standard identification object matched in the full fingerprint database can be used as the second standard identification object.

[0112] Specifically, if in step S203 above, the matching result shows that any fingerprint information is not included in the hot spot fingerprint database, that is, the fingerprint information does not have a corresponding first standard identification object, a relationship can be established based on the hash function between the name of the standard identification object corresponding to each standard fingerprint information in the full fingerprint database and the storage location corresponding to the standard fingerprint information. Through this relationship, the standard identification object corresponding to the storage location of the fingerprint information can be quickly found in the full fingerprint database. The standard identification object is then used as the second standard identification object corresponding to the fingerprint information.

[0113] S205. The first standard identification object and several second standard identification objects are identified as the identification objects of the device to be identified.

[0114] Specifically, the first standard identification object obtained in step S203 and several second standard identification objects obtained in step S204 can be collectively determined as the identification object of the device to be identified.

[0115] This embodiment can, after receiving several fingerprint information messages from each device to be identified, first match these fingerprint messages in a hotspot fingerprint database. Since the number of standard fingerprint messages in the hotspot fingerprint database is relatively small, the matching speed is fast. If a first standard identification object corresponding to each fingerprint message can be matched in the hotspot fingerprint database, then all first standard identification objects can be directly identified as the devices to be identified. If no first standard object is matched for any fingerprint message, then the fingerprint message can be matched based on a hash function in a large full fingerprint database. The resulting second standard identification object is the second standard identification object for that fingerprint message. Then, the first standard identification object and the second standard identification object are integrated into the corresponding device to be identified, thus accelerating the overall fingerprint recognition speed.

[0116] In some embodiments, several different request packets can be generated for each device to be identified, based on the corresponding object to be identified and the standard request format of the object. Specifically, several optional objects to be identified for each device to be identified are determined based on big data; several standard request formats corresponding to each optional object to be identified are obtained, and several corresponding identification request packets are generated based on the several standard request formats.

[0117] Correspondingly, several identification request packets are sent to each device to be identified.

[0118] The optional identification targets can be service ports that may exist on the device to be identified from different environments, determined by big data, such as school computer labs or enterprise back-end computer labs. Different optional identification targets can have corresponding standard request formats pre-defined and stored; these standard request formats can be universally applicable to big data. The environmental source of each device to be identified can be stored in the fingerprint recognition device.

[0119] Specifically, based on big data, the possible identification targets for each device to be identified can be determined, and then the standard request formats corresponding to various pre-stored possible identification targets can be obtained. The parameters involved in the request are then organized according to the standard request format to generate the corresponding identification request packet. Then, several identification request packets can be sent to each device to be identified.

[0120] This embodiment can determine several selectable objects to be identified for each device based on big data, and generate several identification request packets corresponding to each device to be identified in a targeted manner. This avoids the time occupied by the device to be identified in responding to irrelevant identification request packets, speeds up the speed at which the fingerprint recognition device receives the corresponding fingerprint information, and speeds up the overall fingerprint recognition speed.

[0121] In some embodiments, the number of fingerprint features in each fingerprint information returned by each device to be identified can be compared with a preset range of fingerprint feature numbers. Fingerprint information with fingerprint feature numbers within the preset range is then matched with hotspot standard fingerprint information in a hotspot fingerprint database. Simultaneously, request parameters can be configured for the identification request packet. When a fingerprint is not empty and its fingerprint feature number is outside the preset range, the identification request packet corresponding to that fingerprint can be resent according to the configured request parameters. Specifically, for each device to be identified, several corresponding fingerprint information are analyzed to determine their respective fingerprint feature numbers. For any fingerprint information, if the corresponding fingerprint feature number is within the preset range, then a first standard identification object is matched in the hotspot fingerprint database based on that fingerprint information.

[0122] Correspondingly, several identification request packets are configured with request parameters to send several configured identification request packets to each device to be identified. The request parameters include request frequency, number of retries, and timeout settings. If any fingerprint information is not empty and the corresponding number of fingerprint features is not within the preset number of fingerprint features, the identification request packet corresponding to the fingerprint information is repeatedly sent to the corresponding device to be identified according to the corresponding request frequency, number of retries, and corresponding timeout settings.

[0123] The number of fingerprint features can refer to the number of characters such as symbols, letters, and numbers that make up a fingerprint. By analyzing the fingerprint information received for each target object during historical fingerprint recognition, the number of valid fingerprint features that can be matched with subsequent fingerprint information can be determined, along with the number of invalid fingerprint features that could not be matched due to transmission errors. A preset range for the number of fingerprint features can then be defined.

[0124] The request frequency can be used to indicate how often an identification request packet is resent; the number of retries can be used to indicate the maximum number of times an identification request packet can be resent when it needs to be resent; since resending an identification request packet requires a transmission period to complete, the timeout setting can be used to set the action to be taken if resending fails within that period.

[0125] As explained in the above embodiments, the fingerprint information may be empty or not. When it is empty, it directly indicates that the standard identification object corresponding to the identification request packet responded to by this fingerprint information is not the identification object of the device to be identified; when it is not empty, there may be a situation where the fingerprint information is incorrect. If there is an error, subsequent fingerprint information matching cannot be performed, and it is impossible to know who the identification object corresponding to this fingerprint information is.

[0126] Specifically, analysis can be performed on each device to be identified to determine the number of fingerprint features contained in each fingerprint information. Then, by comparing the number of fingerprint features with a preset range of fingerprint feature counts, it can be determined whether the fingerprint information can be matched subsequently. If the number of fingerprint features in a fingerprint information is not within the preset range, and the fingerprint information is not empty, it indicates that the fingerprint information has an error. In this case, the corresponding identification request packet needs to be resent according to the pre-configured request frequency, number of retries, and timeout settings.

[0127] This embodiment determines whether each fingerprint can be matched with hotspot standard fingerprint information by comparing the number of fingerprint features in each fingerprint with a preset range of fingerprint feature counts. If the fingerprint is incorrect and cannot be matched, the corresponding recognition request packet is resent according to the settings of the request parameters. This avoids wasting a lot of time on directly matching incorrect fingerprints, thereby maximizing the recognition success rate and reducing erroneous recognitions caused by network or device instability.

[0128] In some embodiments, a hotspot fingerprint database can be built by combining historical objects to be identified and general fingerprint information from a general fingerprint database. Specifically, the general fingerprint information in the general fingerprint database is analyzed to identify fingerprint information with an access frequency greater than or equal to a preset access frequency threshold, and this information is added to the hotspot fingerprint database to be built. The objects to be identified for each device to be identified are recorded in real time, and historical objects to be identified are updated. Based on the updated historical objects to be identified, the historical objects to be identified are sorted according to the identification frequency of each object. For each update, the hotspot fingerprint database to be built is updated according to the latest access frequency of the general fingerprint database, the updated sorting of historical objects to be identified, and the preset update requirements, thus obtaining the hotspot fingerprint database.

[0129] A general fingerprint database can be any publicly available fingerprint database on the internet that contains a wide range of fingerprint information.

[0130] Access frequency can be used to represent the number of times a fingerprint is accessed per unit of time. A preset access frequency threshold can be determined based on large datasets; for example, the fingerprint with the fewest accesses among the top 50% of fingerprints accessed within a year can be used as the preset access frequency threshold. General fingerprint information can include which service ports are in the general fingerprint database, and also the formats of the fingerprint information corresponding to each service port.

[0131] Recognition frequency can represent the number of times a fingerprint is performed on a given object within a unit of time. Historical objects to be identified can be service ports successfully identified during historical fingerprint recognition processes. Latest access frequency can be the current access frequency of service ports in the general fingerprint database at each time a historical object to be identified is updated. Preset update requirements can include the need to select the most frequently used historical objects to be identified from the updated historical objects to be identified, for updating the hotspot fingerprint database to be built. For example, after each update, the historical objects to be identified in the hotspot fingerprint database to be created can be updated to the top 10% of historical objects to be identified.

[0132] Specifically, by analyzing the general fingerprint information in the general fingerprint database, the access frequency of each format of fingerprint information for each service port can be determined. Fingerprint information with an access frequency greater than or equal to a preset access frequency threshold is tagged with the corresponding service port and added to the hotspot fingerprint database to be built. The number of objects to be identified on the device may gradually increase over time. Each time fingerprint recognition is performed, the objects to be identified on the device can be recorded. If a change is found in the objects to be identified, the historical objects to be identified can be updated. Then, the objects to be identified in the historical objects to be identified are sorted according to their recognition frequency, and the sorted objects to be identified are updated to the hotspot fingerprint database to be built according to preset update requirements, thus obtaining the hotspot fingerprint database.

[0133] Preferably, the historical objects to be identified are sorted according to their recognition frequency. While updating the hotspot fingerprint database to be built according to preset update requirements, the recognition frequency of each fingerprint information of each object in the hotspot fingerprint database to be built can also be sorted according to the preset update requirements. The preset update requirements may also include the requirement to select the most frequently used fingerprint information from several fingerprint information of different formats selected from the aforementioned objects to be identified, for updating the hotspot fingerprint database to be built. This ensures that the hotspot fingerprint database contains the most frequently identified objects and the most frequently used fingerprint information of these objects.

[0134] This embodiment establishes a hotspot fingerprint database based on general fingerprint information from a general fingerprint database. Then, it updates the hotspot fingerprint database with each update of historical objects to be identified, ensuring that the objects in the hotspot fingerprint database are the most recent and frequently identified objects at the current moment. In actual fingerprint recognition, frequently identified objects are generally the majority, making this hotspot fingerprint database highly practical. If fingerprint information is included in the hotspot fingerprint database, there is no need for subsequent comparison with the entire fingerprint database, thus speeding up fingerprint recognition.

[0135] In some embodiments, a hash function can be used to build a full fingerprint database. Specifically, local fingerprint information of each device to be identified is acquired in real time from the authorized fingerprint database, the general fingerprint database, and the voluntarily provided fingerprint database, and aggregated into comprehensive fingerprint information. Each comprehensive fingerprint information is stored under the name tag of the corresponding object to be identified. The hash value of each comprehensive fingerprint information is calculated based on the hash function, and the relationship between the hash value and the corresponding name tag is established to generate a full fingerprint database. The name tag corresponding to the hash value of the fingerprint information is determined according to the relationship, and the corresponding object to be identified is determined.

[0136] An authorized fingerprint database can be a fingerprint database associated with a fingerprint recognition device, which has the authority to log in and can legally obtain fingerprints. A voluntarily provided fingerprint database can be a fingerprint database associated with a fingerprint recognition device, which is voluntarily shared by relevant enterprises that need the fingerprint recognition device for fingerprint recognition.

[0137] Local fingerprint information can be fingerprint information contained in authorized fingerprint databases, general fingerprint databases, or voluntarily provided fingerprint databases. Since the fingerprint information in various formats for several objects corresponding to each device to be identified may not be complete in any of the aforementioned fingerprint databases, it can be considered as local fingerprint information. Comprehensive fingerprint information can be a collection of local fingerprint information corresponding to each of the authorized fingerprint database, general fingerprint database, and voluntarily provided fingerprint databases.

[0138] Specifically, local fingerprint information can be acquired in real time and aggregated to obtain comprehensive fingerprint information. Each comprehensive fingerprint can be stored under the name tag of the corresponding object to be identified. Using a hash function, a hash value is calculated for each comprehensive fingerprint. This hash value is then associated with the storage location of the corresponding comprehensive fingerprint, i.e., the corresponding name tag, to establish a relationship and generate a full fingerprint database. Based on this relationship, the name tag corresponding to the hash value of the fingerprint information of the device to be identified can be determined, thereby identifying the corresponding object to be identified.

[0139] This embodiment updates the comprehensive fingerprint information in real time based on partial fingerprint information from authorized fingerprint databases, general fingerprint databases, and voluntarily provided fingerprint databases. Each piece of comprehensive fingerprint information is converted into a corresponding hash value using a hash function and stored. A relationship is established between this hash value and its corresponding storage location, so that the corresponding storage location (i.e., the name tag of the object to be identified) can be found during subsequent matching. Although the total number of fingerprints in the full fingerprint database is enormous, the relationship between hash values ​​and their corresponding storage locations speeds up fingerprint recognition within the entire database.

[0140] In some embodiments, hash values ​​corresponding to several fingerprints to be identified can be calculated to match corresponding standard fingerprint information to determine the corresponding second standard identification object. Specifically, the hash value corresponding to the fingerprint information is calculated; the corresponding hash value is used as a query condition to quickly match the standard fingerprint information corresponding to the fingerprint information in the entire fingerprint database; and the corresponding second standard identification object is determined based on the standard fingerprint information and the above relationship.

[0141] Specifically, the hash value of the fingerprint information is calculated using the hash function in the above embodiment. Then, the standard fingerprint information corresponding to the hash value is quickly matched directly in the full fingerprint database using the hash value as a query condition. The corresponding name tag can then be queried, thereby determining the corresponding second standard identification object.

[0142] This embodiment converts fingerprint information into hash values. Using these hash values ​​as query criteria, it quickly finds standard fingerprint information with the same hash value in the entire fingerprint database. Then, based on the storage location of this standard fingerprint information, i.e., the name tag corresponding to the hash value, it determines the second standard identification object. This method achieves the goal of rapid matching in the entire fingerprint database.

[0143] In some embodiments, the scanned identification objects obtained by the third-party plugin from scanning the device to be identified can be combined with the identification objects obtained in the above embodiments to obtain the final target identification object of the device to be identified. Specifically, the third-party plugin is activated to scan the device to be identified; the scanned identification objects obtained by the third-party plugin are received, and the scanned identification objects and the identification objects are combined to obtain the actual identification object of the device to be identified.

[0144] Third-party plugins can be plugins capable of scanning for objects to be identified on the device to be identified, such as Nmap. The scan results obtained by the third-party plugin when scanning the device to be identified can be used as the scanned identification object. The actual identification object can be the final object to be identified when identifying the device to be identified.

[0145] Specifically, the fingerprint recognition device can activate a third-party plugin, enabling the plugin to scan the device to be recognized. It then receives the scanned object generated by the third-party plugin. The scanned object and the object to be recognized identified in the above embodiments are combined and used together as the actual object to be recognized for the device.

[0146] This embodiment combines the objects to be identified in the hotspot database and the full database with the scanned objects obtained by third-party devices, and uses them together as the actual objects to be identified by the device, thereby improving the accuracy of fingerprint recognition results.

[0147] In other embodiments, current fingerprint recognition methods mainly include the following:

[0148] 1. Single-Source Fingerprint Recognition: Currently, many fingerprint recognition products or processing methods exist on the market based on a single source. For example, fingerprint recognition is achieved by comparing the fingerprint information of the target host with the fingerprint information in the single fingerprint database. However, this method suffers from low compatibility, making it difficult to accurately identify fingerprints not in the database.

[0149] 2. Simple Comparison Methods: Some existing technologies use simple comparison methods, such as comparing the fingerprint information returned by the target host with fixed fingerprint information to determine whether they match. This method is simple and intuitive, but its accuracy is low for complex fingerprint information and fingerprints from multiple sources.

[0150] 3. Single-level fingerprint recognition: Some existing fingerprint recognition methods typically use only one level of fingerprint recognition, such as comparing only hotspot fingerprint databases or full fingerprint databases. This fails to fully utilize multi-level and multi-source fingerprint information, resulting in low recognition performance and compatibility.

[0151] These fingerprint recognition methods have the following shortcomings and defects:

[0152] 1. Low compatibility: Traditional single-source fingerprint recognition methods can usually only recognize fingerprint information in a specific fingerprint database. They are difficult to accurately recognize fingerprint information not in the fingerprint database, resulting in low compatibility.

[0153] 2. Limited recognition accuracy: Some existing technologies use simple comparison methods to compare the fingerprint information returned by the target host with fixed fingerprint information. However, this simple comparison method has low recognition accuracy for complex fingerprint information and fingerprints from multiple sources, and is prone to misidentification or missed identification.

[0154] 3. Single-level recognition: Some existing fingerprint recognition methods typically use only a single-level fingerprint database or comparison method, such as comparing only hotspot fingerprint databases or the entire fingerprint database. This fails to fully utilize multi-level and multi-source fingerprint information, resulting in low recognition performance.

[0155] 4. Lack of optimization methods: Some existing technologies lack ways to optimize the fingerprint recognition process, such as the lack of multi-threading and concurrent processing optimization methods, resulting in low fingerprint recognition efficiency, especially insufficient performance in large-scale fingerprint recognition scenarios;

[0156] 5. Security issues: Some existing technologies have security issues in the storage, transmission and processing of fingerprint information, such as the risk of being vulnerable to hacker attacks or data leakage, which may affect the security of the system.

[0157] Therefore, existing fingerprint recognition methods have some shortcomings and defects in terms of compatibility, recognition accuracy, multi-level recognition, optimization methods and security, and need to be further improved and enhanced to provide higher performance and more secure and reliable fingerprint recognition technology.

[0158] This application introduces a multi-source (multi-fingerprint database, i.e., hotspot fingerprint database and full fingerprint database) fingerprint recognition method, which can process fingerprint information from different sources and in different formats with high compatibility, avoiding the limitation of traditional methods that can only recognize specific fingerprint databases and improving the system's compatibility.

[0159] This application adopts a multi-level fingerprint recognition method (first comparing with fingerprint information in the hot fingerprint database, and if the comparison fails, then comparing with fingerprint information in the full fingerprint database). By comparing fingerprint databases at multiple levels, the accuracy of recognition is improved and the risk of false recognition and missed recognition is reduced. It has higher accuracy, especially for complex fingerprint information and fingerprints from multiple sources.

[0160] This application compares hotspot fingerprint databases and full fingerprint databases, thereby making full use of multi-level and multi-source fingerprint information, improving the recognition performance of the system (fingerprint recognition device), and avoiding the limitation of using only a single level (general fingerprint database) in traditional methods.

[0161] Meanwhile, this application introduces optimization methods such as multi-threading. By using concurrent processing and multi-threading technology (to perform synchronous fingerprint recognition for each device to be identified), the efficiency of fingerprint recognition is improved. In particular, in large-scale fingerprint recognition scenarios, the recognition task can be completed more quickly, thereby improving the performance of the system (fingerprint recognition device).

[0162] The multi-level fingerprint recognition process of this application is as follows: Figure 3 As shown, firstly, packet processing (sending an identification request packet) is performed on the target for fingerprint recognition. The computer software sends a request packet (identification request packet) to the device to be identified. After receiving the fingerprint information, fingerprint recognition is performed. The request packet may contain relevant parameters (fingerprint features) of the fingerprint information to be identified. The packet processing in this application adopts a highly versatile method, which can be referenced. Figure 4 The diagram illustrates a flowchart of a general request packet format generation process. Fingerprint information can originate from various sources, including source 1, source 2, ..., source n, which may correspond to general databases, voluntarily provided databases, etc. Fingerprint information (partial fingerprint information) from various sources can be integrated to obtain a general request packet format. This general request packet format can include request formats corresponding to fingerprint information of all formats for different objects to be identified. Therefore, several request packets corresponding to each object to be identified are generated based on this general request packet format, which can be used for any device to be identified. This reduces the complexity of making different format requests for different devices. It also allows users (operators of fingerprint recognition devices) to easily configure request packet parameters, such as packet (identification request packet) frequency, retries, and timeout settings, to maximize the identification success rate and reduce erroneous identifications caused by network or target instability.

[0163] After packet processing, we batch process the returned results (each fingerprint information). First, to improve fingerprint recognition efficiency, this application performs a comparison with a hotspot fingerprint database, which typically consists of frequently accessed fingerprint information. This application extracts frequently occurring fingerprint information as the basis for constructing the hotspot fingerprint database by recording and statistically analyzing historical fingerprint recognition requests. Furthermore, it filters frequently accessed fingerprint information as the content of the hotspot fingerprint database through analysis and mining of existing fingerprint databases. This ensures that the hotspot fingerprint database contains commonly used fingerprint information in the system, thereby improving the efficiency and accuracy of the comparison.

[0164] We only perform a full fingerprint database comparison when a match in the hot fingerprint database fails. The full fingerprint database can be obtained through various methods; this application collects fingerprint information from multiple sources, which can be referenced. Figure 5 The diagram illustrates the sources of fingerprint information in the full fingerprint database. This fingerprint information can be obtained through legitimate means, such as authorized fingerprint databases, publicly available fingerprint resources, and fingerprint information voluntarily provided by users (such as the enterprise from which the device to be identified originates). By integrating fingerprint information from these different sources, the full fingerprint database can contain all fingerprint information in the system, thus providing a more comprehensive comparison and matching capability. Furthermore, to achieve rapid comparison during the full fingerprint database comparison, a fast fingerprint matching algorithm based on a hash function is used to convert fingerprint information into hash values, thereby enabling fast comparison and matching. In addition, this application also supports the use of third-party detection components, such as Nmap, as detection plugins. By comparing and summarizing the results detected by these third-party detection components (scanning and identifying objects) with the fingerprint recognition results (objects to be identified), the final fingerprint recognition result (the actual identified object) is obtained. Such comprehensive comparison and summarization can further improve the accuracy and reliability of fingerprint recognition.

[0165] The following is an example of fingerprint recognition using the processing described in this application. The specific steps are as follows:

[0166] 1. Highly versatile payload packet transmission: In the fingerprint recognition process, a highly versatile payload packet is first used. This means using a set of fingerprint features that can be widely applied to a variety of different types of targets, thereby improving the compatibility of recognition and covering a variety of different fingerprint recognition scenarios.

[0167] 2. Batch Comparison of Returned Results: The returned fingerprint recognition results are processed using a batch comparison method. This means that a batch of returned fingerprint features are compared, thereby avoiding sending and comparing duplicate payloads multiple times and improving processing efficiency.

[0168] 3. Comparison with Hotspot Fingerprint Databases: Hotspot fingerprint databases typically contain common, frequently occurring fingerprint features (fingerprint information), such as those found in common operating systems and software applications. By efficiently comparing fingerprint features within these databases, it's possible to quickly determine whether a target fingerprint belongs to a feature within the database, thereby improving the accuracy and efficiency of fingerprint recognition.

[0169] 4. Comparison with the full fingerprint database: For fingerprint features (fingerprint information) not in the hotspot fingerprint database, a comparison with the full fingerprint database is used. The full fingerprint database typically contains a more comprehensive set of fingerprint features (fingerprint information), including various types such as those from operating systems, applications, and protocols. By comparing fingerprint features (fingerprint information) from the full fingerprint database, the accuracy of fingerprint recognition can be further improved.

[0170] 5. Summary of scanning results from other third-party plugins: According to the needs of users (enterprises corresponding to the devices to be identified, etc.), this application can use third-party plugins (such as Nmap) to perform scanning, and summarize their results with our scanning results to obtain the final fingerprint recognition result.

[0171] Figure 6 The following is a schematic diagram of the structure of a multi-level fingerprint recognition device provided in an embodiment of this application, as shown below. Figure 6 As shown, the multi-level fingerprint recognition device 600 of this embodiment includes: an identification request packet sending module 601, a fingerprint information receiving module 602, a first standard identification object determination module 603, a second standard identification object determination module 604, and a target identification object determination module 605.

[0172] The identification request packet sending module 601 is used to send several identification request packets to each device to be identified, and each identification request packet corresponds to a standard identification object.

[0173] The fingerprint information receiving module 602 is used to receive several fingerprint information sent by each device to be identified, and each fingerprint information is generated by the corresponding device to be identified according to a corresponding identification request packet.

[0174] The first standard identification object determination module 603 is used to match a number of fingerprint information with a corresponding first standard identification object in the hot spot fingerprint database. The hot spot fingerprint database includes a number of hot spot standard identification objects, and each hot spot standard identification object corresponds to a number of hot spot standard fingerprint information.

[0175] The second standard identification object determination module 604 is used to, for any fingerprint information, if there is no corresponding first standard identification object for the fingerprint information, match the corresponding second standard identification object in the full fingerprint database based on the hash function and the fingerprint information. The full fingerprint database includes several standard identification objects, and each standard identification object corresponds to several standard fingerprint information. The number of hot spot standard identification objects is less than the number of standard identification objects, and the number of hot spot standard fingerprint information corresponding to each hot spot standard identification object is less than the number of corresponding standard fingerprint information.

[0176] The object to be identified module 605 is used to identify the first standard identification object and a number of second standard identification objects as the objects to be identified by the device to be identified.

[0177] Optionally, the multi-level fingerprint recognition device 600 also includes a standard request format acquisition module 606, used for:

[0178] Based on big data, several selectable objects to be identified are determined for each device to be identified;

[0179] Obtain several standard request formats corresponding to each selectable object to be identified, and generate several corresponding identification request packages based on the several standard request formats;

[0180] The identification request packet sending module 601 is specifically used for:

[0181] Send several identification request packets to each device to be identified.

[0182] Optionally, the first standard object identification module 603 is specifically used for:

[0183] For each device to be identified, analyze the corresponding fingerprint information to determine the number of fingerprint features for each device.

[0184] For any fingerprint information, if the number of corresponding fingerprint features is within the preset range of fingerprint feature numbers, then the corresponding first standard identification object is matched in the hot spot fingerprint database based on the fingerprint information.

[0185] The multi-level fingerprint recognition device 600 also includes a recognition request packet retransmission module 607, used for:

[0186] Configure the request parameters for several identification request packets to send several configured identification request packets to each device to be identified. The request parameters include request frequency, number of retries and timeout settings.

[0187] If any fingerprint information is not empty and the corresponding number of fingerprint features is not within the preset number of fingerprint features, then the identification request packet corresponding to the fingerprint information is repeatedly sent to the corresponding device to be identified according to the corresponding request frequency, number of retries and corresponding timeout settings.

[0188] Optionally, the multi-level fingerprint recognition device 600 also includes a hotspot fingerprint database construction module 608, used for:

[0189] Analyze the general fingerprint information in the general fingerprint database, identify fingerprint information with an access frequency greater than or equal to a preset access frequency threshold, and add it to the hotspot fingerprint database to be built.

[0190] Record the objects to be identified for each device in real time and update the historical objects to be identified.

[0191] Based on the updated historical objects to be identified, sort the historical objects to be identified according to the identification frequency of each object;

[0192] For each update, the hotspot fingerprint database to be built is updated based on the latest access frequency of the general fingerprint database, the updated sorting of historical objects to be identified, and the preset update requirements, thus obtaining the hotspot fingerprint database.

[0193] Optionally, the multi-level fingerprint recognition device 600 also includes a full fingerprint database construction module 609, used for:

[0194] In real time, the local fingerprint information of each device to be identified is obtained from the authorized fingerprint database, the general fingerprint database, and the voluntarily provided fingerprint database, and then summarized into comprehensive fingerprint information.

[0195] Each integrated fingerprint information is stored under the name tag of the corresponding object to be identified;

[0196] The hash value of each integrated fingerprint information is calculated based on a hash function, and the relationship between the hash value and the corresponding name tag is established to generate a full fingerprint database. The name tag corresponding to the hash value of the fingerprint information is determined according to the relationship, and the corresponding object to be identified is determined.

[0197] Optionally, the object determination module 604 is specifically used for:

[0198] Calculate the hash value corresponding to this fingerprint information;

[0199] Using the corresponding hash value as the query condition, quickly match the standard fingerprint information corresponding to the fingerprint information in the entire fingerprint database;

[0200] Based on the standard fingerprint information and relationships, the corresponding second standard identification objects are determined.

[0201] Optionally, the multi-level fingerprint recognition device 600 also includes an actual identification object determination module 610, used for:

[0202] Activate the third-party plugin to enable it to scan for the device to be identified;

[0203] It receives scanned and identified objects obtained from third-party plugins, and combines the scanned and identified objects with the objects to be identified to obtain the actual objects to be identified for the device.

[0204] The apparatus of this embodiment can be used to execute the method of any of the above embodiments, and its implementation principle and technical effect are similar, so they will not be described again here.

[0205] Figure 7 This is a schematic diagram of the structure of an electronic device provided in one embodiment of this application, such as... Figure 7As shown, the electronic device 700 of this embodiment may include a memory 701 and a processor 702.

[0206] The memory 701 stores a computer program that can be loaded by the processor 702 and execute the methods described in the above embodiments.

[0207] The processor 702 and the memory 701 are connected, for example, via a bus.

[0208] Optionally, the electronic device 700 may also include a transceiver. It should be noted that in practical applications, the transceiver is not limited to one, and the structure of the electronic device 700 does not constitute a limitation on the embodiments of this application.

[0209] Processor 702 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 702 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0210] A bus can include a pathway for transmitting information between the aforementioned components. The bus can be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, only one thick line is used in the diagram, but this does not imply that there is only one bus or one type of bus.

[0211] The memory 701 may be a ROM (Read Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0212] The memory 701 is used to store application code that executes the solution of this application, and its execution is controlled by the processor 702. The processor 702 is used to execute the application code stored in the memory 701 to implement the content shown in the foregoing method embodiments.

[0213] Electronic devices include, but are not limited to: mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (such as in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Servers can also be included. Figure 7 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.

[0214] The electronic device in this embodiment can be used to execute the method of any of the above embodiments, and its implementation principle and technical effect are similar, so they will not be described again here.

[0215] This application also provides a computer-readable storage medium storing a computer program that can be loaded by a processor and execute the methods described in the above embodiments.

[0216] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

Claims

1. A multi-level fingerprint recognition method, characterized in that, include: Send several identification request packets to each device to be identified, and each identification request packet corresponds to a standard identification object; Receive several fingerprint information messages sent by each device to be identified, where each fingerprint information message is generated by the corresponding device to be identified based on a corresponding identification request packet; For each device to be identified, a first standard identification object is matched in the hotspot fingerprint database based on the several fingerprint information. The hotspot fingerprint database includes several hotspot standard identification objects, and each hotspot standard identification object corresponds to several hotspot standard fingerprint information. For any fingerprint information, if there is no corresponding first standard identification object for the fingerprint information, then based on the hash function and the fingerprint information, a corresponding second standard identification object is matched in the full fingerprint database. The full fingerprint database includes several standard identification objects, and each standard identification object corresponds to several standard fingerprint information. The number of hot spot standard identification objects is less than the number of standard identification objects, and the number of hot spot standard fingerprint information corresponding to each hot spot standard identification object is less than the number of corresponding standard fingerprint information. The first standard identification object and several second standard identification objects are determined as the identification objects of the device to be identified; The method further includes: Based on big data, several selectable objects to be identified are determined for each device to be identified; Obtain several standard request formats corresponding to each selectable object to be identified, and generate several corresponding identification request packages according to the several standard request formats; The step of sending several identification request packets to each device to be identified includes: Send several identification request packets to each device to be identified; For each device to be identified, matching the corresponding first standard identification object in the hotspot fingerprint database based on the plurality of fingerprint information includes: For each device to be identified, analyze the corresponding fingerprint information to determine the number of fingerprint features for each device. For any fingerprint information, if the number of corresponding fingerprint features is within the preset range of fingerprint feature numbers, then the corresponding first standard identification object is matched in the hotspot fingerprint database based on the fingerprint information. The method further includes: Configure the request parameters for the plurality of identification request packets to send a plurality of configured identification request packets to each device to be identified. The request parameters include request frequency, number of retries and timeout settings. If any of the fingerprint information is not empty and the corresponding number of fingerprint features is not within the preset number of fingerprint features, then the identification request packet corresponding to the fingerprint information is repeatedly sent to the corresponding identification device according to the corresponding request frequency, the number of retries and the corresponding timeout setting.

2. The method according to claim 1, characterized in that, The construction of the hotspot fingerprint database includes: Analyze the general fingerprint information in the general fingerprint database, identify fingerprint information with an access frequency greater than or equal to a preset access frequency threshold, and add it to the hotspot fingerprint database to be built. Record the objects to be identified for each device in real time and update the historical objects to be identified; Based on the updated historical objects to be identified, the historical objects to be identified are sorted according to the identification frequency of each object; For each update, the hotspot fingerprint database to be built is updated based on the latest access frequency of the general fingerprint database, the updated sorting of historical objects to be identified, and the preset update requirements, thus obtaining the hotspot fingerprint database.

3. The method according to claim 1, characterized in that, The construction of a full fingerprint database includes: In real time, the local fingerprint information of each device to be identified is obtained from the authorized fingerprint database, the general fingerprint database, and the voluntarily provided fingerprint database, and then summarized into comprehensive fingerprint information. Each integrated fingerprint information is stored under the name tag of the corresponding object to be identified; The hash value of each comprehensive fingerprint information is calculated based on a hash function, and the relationship between the hash value and the corresponding name tag is established to generate a full fingerprint database. The name tag corresponding to the hash value of the fingerprint information is determined according to the relationship, and the corresponding object to be identified is determined.

4. The method according to claim 3, characterized in that, The process of matching the corresponding second standard identification object in the entire fingerprint database based on the hash function and the fingerprint information includes: Calculate the hash value corresponding to this fingerprint information; Using the corresponding hash value as the query condition, the standard fingerprint information corresponding to the fingerprint information is quickly matched in the full fingerprint database; Based on the standard fingerprint information and the relationship, the corresponding second standard identification object is determined.

5. The method according to any one of claims 1-4, characterized in that, Also includes: Activate the third-party plugin to scan the device to be identified; The system receives the scanned and identified objects obtained by the third-party plugin, and combines the scanned and identified objects with the objects to be identified to obtain the actual identified objects of the devices to be identified.

6. A multi-level fingerprint recognition device, characterized in that, include: The identification request packet sending module is used to send several identification request packets to each device to be identified, and each identification request packet corresponds to a standard identification object. The fingerprint information receiving module is used to receive several fingerprint information sent by each device to be identified, and each fingerprint information is generated by the corresponding device to be identified according to a corresponding identification request packet. The first standard identification object determination module is used to match the corresponding first standard identification object in the hot spot fingerprint database for each device to be identified based on the several fingerprint information. The hot spot fingerprint database includes several hot spot standard identification objects, and each hot spot standard identification object corresponds to several hot spot standard fingerprint information. The second standard identification object determination module is used to, for any fingerprint information, if there is no corresponding first standard identification object for the fingerprint information, match the corresponding second standard identification object in the full fingerprint database based on the hash function and the fingerprint information. The full fingerprint database includes a number of standard identification objects, and each standard identification object corresponds to a number of standard fingerprint information. The number of hot spot standard identification objects is less than the number of standard identification objects, and the number of hot spot standard fingerprint information corresponding to each hot spot standard identification object is less than the number of corresponding standard fingerprint information. The object to be identified module is used to identify the first standard identification object and a plurality of second standard identification objects as the objects to be identified by the device to be identified. The multi-level fingerprint recognition device also includes a standard request format acquisition module, used for: Based on big data, several selectable objects to be identified are determined for each device to be identified; Obtain several standard request formats corresponding to each selectable object to be identified, and generate several corresponding identification request packages according to the several standard request formats; The identification request packet sending module is specifically used for: Send several identification request packets to each device to be identified; The first standard identification object determination module is specifically used for: For each device to be identified, analyze the corresponding fingerprint information to determine the number of fingerprint features for each device. For any fingerprint information, if the number of corresponding fingerprint features is within the preset range of fingerprint feature numbers, then the corresponding first standard identification object is matched in the hotspot fingerprint database based on the fingerprint information. The multi-level fingerprint recognition device also includes a recognition request packet retransmission module, used for: Configure the request parameters for the plurality of identification request packets to send a plurality of configured identification request packets to each device to be identified. The request parameters include request frequency, number of retries and timeout settings. If any of the fingerprint information is not empty and the corresponding number of fingerprint features is not within the preset number of fingerprint features, then the identification request packet corresponding to the fingerprint information is repeatedly sent to the corresponding identification device according to the corresponding request frequency, the number of retries and the corresponding timeout setting.

7. An electronic device, characterized in that, include: Memory and processor; The memory is used to store program instructions; The processor is configured to call and execute program instructions in the memory to perform the multi-level fingerprint recognition method as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program; when the computer program is executed by a processor, it implements the multi-level fingerprint recognition method as described in any one of claims 1-5.

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