A security management method and system for electronic seal cloud signing based on big data

Abstract

The application relates to the technical field of information security, in particular to a security management method and system for electronic seal cloud signing based on big data, wherein the method ensures the security of electronic seal signing through multi-layer identity authentication, and after the electronic seal is signed, the security of the signing result is ensured by tracking the moving track of the signed electronic seal and calculating the similarity between the track sequence constructed based on the moving track and the track verification sequence constructed based on social data. The method improves the security of electronic seal cloud signing by combining multi-layer identity authentication and digital seal tracking marks, and further ensures the security of the signing result by verifying the moving track of the signing result by using the social data of the user.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of information security, and particularly relates to a security management method and system for electronic seal cloud signing based on big data. BACKGROUND

[0002] Under the background of rapid development of big data-based digitization and cloud computing, electronic seal, as a key tool to ensure the legality and security of documents, has increasingly strategic significance. With the continuous evolution of information security regulations and industry standards, the demand for building an efficient and stable electronic seal management system is growing in various fields, not only to meet the requirements of legal compliance, but also to strengthen the foundation of user trust. However, the existing technology has some deficiencies in the security management after the completion of the signing behavior, especially in the integration of social data for comprehensive security monitoring.

[0003] Therefore, the present application proposes an innovative security management method and system for electronic seal cloud signing based on big data, which is committed to improving the security management efficiency of electronic seal cloud signing. SUMMARY

[0004] The present application provides a security management method and system for electronic seal cloud signing based on big data to solve the problem of neglecting security management after the completion of the signing behavior in the prior art, and improve the overall security of electronic seal.

[0005] In a first aspect, some embodiments of the present application provide a security management method for electronic seal cloud signing based on big data, which comprises:

[0006] In response to receiving an electronic seal signing request sent by a user terminal, performing multi-layer identity verification on a user currently logged in the user terminal; wherein the multi-layer identity verification includes operation environment verification, biometric identification verification and biological behavior verification;

[0007] When the multi-layer identity verification passes, performing electronic seal signing;

[0008] Returning an electronic seal signing result to the user terminal, the electronic seal signing result including a signed digital seal and a digital seal tracking mark, the digital seal tracking mark being used to return a movement trajectory of the signed digital seal to a security management system when a preset condition is triggered;

[0009] Receiving a movement trajectory of the signed digital seal by the user terminal after receiving the electronic seal signing result; the movement trajectory reflects the flow direction of the electronic seal signing result among different devices;

[0010] Constructing a trajectory sequence Sa based on trajectory points in the movement trajectory;

[0011] obtaining social data of the user in a preset time period, and constructing a trajectory verification sequence Ya based on device locations of social objects in the social data;

[0012] calculating similarity between the trajectory sequence Sa and the trajectory verification sequence Ya by the following formula: wherein d represents similarity between the trajectory sequence Sa and the trajectory verification sequence Ya, λ is a preset adjustment parameter, f is frequency of coincident elements between two sequences, and fs is total frequency of elements appearing in two sequences;

[0013] when the similarity is greater than a preset threshold, adding a security mark to the electronic seal signature result.

[0014] Further, in some embodiments, wherein,

[0015] the operation environment verification comprises:

[0016] obtaining a one-time password input by the user, matching the one-time password with a verification code sent through a short message or an email; and

[0017] obtaining an operation environment in which the user inputs the one-time password, and performing anomaly verification on the operation environment;

[0018] the biological verification comprises:

[0019] identifying the identity of the user through at least one of fingerprint recognition, face recognition and voiceprint recognition;

[0020] the biological behavior verification comprises:

[0021] obtaining typing speed, key force and mouse movement trajectory of the user in a past preset time period;

[0022] performing anomaly verification on the typing speed, key force and mouse movement trajectory based on historical biological behaviors of the user.

[0023] Further, in some embodiments, the method further comprises:

[0024] when the similarity is less than the preset threshold, performing an invalid management procedure on the electronic seal signature result, comprising:

[0025] sending an abnormal prompt information to the user terminal;

[0026] receiving, from the user terminal, appeal information returned by the user according to the abnormal prompt information;

[0027] determining an appeal type based on the appeal information;

[0028] determining whether the type of the complaint is within a preset type range, and if so, determining whether the complaint is passed based on historical complaint information of the user;

[0029] in response to the complaint being passed, adding a security mark to the electronic seal signature result;

[0030] in response to the complaint not being passed, adding an invalid mark to the electronic seal signature result.

[0031] Further, in some embodiments, the determining whether the complaint is passed based on the historical complaint information of the user comprises:

[0032] determining a historical complaint frequency and a historical complaint reason based on the historical complaint information of the user;

[0033] determining whether the historical complaint frequency exceeds a first allowed value and whether the historical complaint reason repeats a second allowed value;

[0034] in response to the historical complaint frequency not exceeding the first allowed value and the historical complaint reason not repeating the second allowed value, determining that the complaint of the user is passed.

[0035] Further, in some embodiments, the method further comprises:

[0036] obtaining an average complaint frequency of other users;

[0037] determining whether the historical complaint frequency of the user exceeds the average complaint frequency;

[0038] if so, adding an observation mark to the user.

[0039] Further, in some embodiments, the mobile trajectory of the signed digital seal is obtained by:

[0040] obtaining geographical position information, MAC address information and storage time of a device storing the signed digital seal;

[0041] generating a trajectory point based on the geographical position information, the MAC address information and the storage time;

[0042] sorting the trajectory points corresponding to each device based on the order of the signed digital seal flowing among different devices to obtain the mobile trajectory.

[0043] Further, in some embodiments, the method further comprises:

[0044] monitoring whether the signed digital seal is copied from the device or transferred to a removable storage device;

[0045] in response to monitoring that the signed digital seal is transferred to a removable storage device;

[0046] determining whether there is an isolated trajectory point in the movement trajectory;

[0047] if yes, adding a trajectory path between the device and the isolated trajectory point which is copied or transferred to a removable storage device.

[0048] In a second aspect, some embodiments of the present application provide a security management system for cloud-based electronic seal signing based on big data, which comprises:

[0049] an identity verification module configured to perform multi-layer identity verification on a user currently logged in to a user terminal in response to receiving an electronic seal signing request sent by the user terminal; wherein the multi-layer identity verification comprises operation environment verification, biological recognition verification and biological behavior verification;

[0050] a seal signing module configured to perform electronic seal signing when the multi-layer identity verification is passed;

[0051] a data sending module configured to return an electronic seal signing result to the user terminal, the electronic seal signing result comprising a signed digital seal and a digital seal tracking mark, the digital seal tracking mark being used to return a movement trajectory of the signed digital seal to the security management system when a preset condition is triggered;

[0052] a data receiving module configured to receive a movement trajectory of the signed digital seal after the user terminal receives the electronic seal signing result; the movement trajectory reflecting the flow direction of the electronic seal signing result among different devices;

[0053] a trajectory verification module configured to construct a trajectory sequence Sa a based on trajectory points in the movement trajectory;

[0054] obtain social data of the user within a preset time period, and construct a trajectory verification sequence Ya based on device locations of social objects in the social data;

[0055] calculate a similarity between the trajectory sequence Sa and the trajectory verification sequence Ya by the following formula: wherein d represents the similarity between the trajectory sequence Sa and the trajectory verification sequence Ya, λ is a preset adjustment parameter, f is the frequency of coincident elements between the two sequences, and fs is the total frequency of elements appearing in the two sequences;

[0056] a marking module configured to add a security mark to the electronic seal signing result when the similarity is greater than a preset threshold.

[0057] Compared with the prior art, the technical scheme provided by the embodiment of the present application has the following advantages: the method improves the security of electronic seal cloud signing by using multi-layer identity verification and digital seal tracking technology including operation environment verification, biometric verification and biological behavior verification, and adds a digital seal tracking mark in the electronic seal signing result, so that the security management system can obtain the destination of the electronic seal signing result after it is returned to the user terminal, and then constructs a trajectory sequence according to the flow direction of the electronic seal signing result, and verifies whether the moving trajectory of the electronic seal signing result is abnormal by using the user's social data, thereby enhancing the security management after the electronic seal signing by combining the user's social big data, and effectively improving the security of the electronic seal signing. BRIEF DESCRIPTION OF DRAWINGS

[0058] The accompanying drawings, which are incorporated herein and form part of the specification, illustrate embodiments consistent with the present application and, together with the description, further serve to explain the principles of the application.

[0059] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without any creative effort.

[0060] Figure 1 A flowchart of a security management method for electronic seal cloud signing based on big data provided by the embodiment of the present application. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical scheme and advantages of the embodiments of the present application more clear, the technical scheme in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without any creative effort belong to the scope of protection of the present application.

[0062] Figure 1 A flowchart of a security management method for electronic seal cloud signing based on big data provided by the embodiment of the present application. In some embodiments, the flow 100 can be executed by a processing device, for example, a computer device or a security management system. As shown in Figure 1 The flow 100 can include the following operations.

[0063] Step 101, in response to receiving an electronic seal signing request sent by a user terminal, performing multi-layer identity verification on a user currently logged in the user terminal.

[0064] Before electronic seal signing, it is crucial to ensure the authenticity and security of the user's identity, and in some embodiments, the multi-layer identity verification includes operating environment verification, biometric verification and biological behavior verification.

[0065] The operating environment verification includes obtaining a one-time password input by the user, matching the one-time password with a verification code sent through SMS or email, and obtaining the operating environment in which the user inputs the one-time password, and performing anomaly verification on the operating environment. By comparing the one-time password input by the user with the verification code sent to the user through SMS or email previously, if they match, it means that the user identity verification is successful; if they do not match, it means that the verification fails. On the basis of the one-time password verification, the current operating environment of the user can be further verified. The verification of the operating environment in which the user inputs the one-time password means that the system detects or records the operating environment in which the user inputs the one-time password, including the type of device used by the user (such as mobile phone, computer), operating system, browser, geographic location (positioned by IP), etc. If the system detects a significant difference from the user's regular operating environment (for example, the user usually logs in from Beijing, but this time the one-time password is input from Shanghai), it can be considered that the user's this login is an abnormal behavior, and further identity verification or login blocking or rejection of electronic seal signing can be required.

[0066] Biometric verification refers to using the physiological characteristics of the user (such as fingerprint, facial recognition, voiceprint, etc.) to perform identity verification. Biometric verification can be considered highly secure because it is difficult to fake and copy. In some embodiments, performing biometric verification includes identifying the identity of the user through at least one of fingerprint recognition, facial recognition and voiceprint recognition. For example, any one of fingerprint recognition, facial recognition and voiceprint recognition can be selected, or a combination of multiple can be selected for verification.

[0067] Specifically, fingerprint recognition refers to identity recognition by analyzing the overall characteristics of the fingerprint pattern, mode area, core point, triangle point, etc. and the node features (such as end point, bifurcation point and turning point) on the fingerprint.

[0068] Facial recognition refers to a series of related technologies that use cameras or cameras to capture face images, detect and track faces, and then perform face recognition on the detected faces.

[0069] Voiceprint recognition, also known as speaker recognition, converts acoustic signals into electrical signals and uses computers to identify them. Different tasks and applications can use different voiceprint recognition technologies.

[0070] Biological behavior verification is a method of confirming the identity of a user by analyzing the biological behavior characteristics of the user.

[0071] The biological behavior verification includes: obtaining typing speed, key force, and mouse movement trajectory of the user in a preset time period in the past; and verifying behavior anomaly based on historical biological behavior of the user.

[0072] The preset time period in the past can be several days in the past, a week in the past, a month in the past, etc. For example, assuming that a user's usual typing speed is 50 words per minute, the key force is moderate, and the mouse movement trajectory also has a certain pattern. When performing biological behavior verification, the system obtains these behavior characteristics of the user in the preset time period, and compares them with the historical biological behavior of the user. If it is found that the user's typing speed suddenly changes to 100 words per minute in the current time period, the key force becomes very light or very heavy, and the mouse movement trajectory is also different from before, the system can determine that it is abnormal behavior.

[0073] In some embodiments, the biological recognition can also include iris recognition, vein recognition, retina recognition, etc.

[0074] Step 102, when the multi-layer identity verification is passed, performing electronic seal signing.

[0075] Once the multi-layer identity verification is passed, the system will allow electronic seal signing to be performed. Electronic seal signing is a kind of electronic signature, which ensures the authenticity and integrity of the document by using digital certificate and encryption technology.

[0076] Step 103, returning the electronic seal signing result to the user terminal.

[0077] In some embodiments, the electronic seal signing result includes a signed digital seal and a digital seal tracking mark. The digital seal tracking mark is used to return the movement trajectory of the signed digital seal to the security management system when a preset condition is triggered.

[0078] The digital seal tracking mark can return the movement trajectory of the signed digital seal to the security management system when a preset condition is triggered, thereby enhancing the security and traceability of the electronic seal. The preset conditions include that the signed electronic seal reaches a new device, the signed electronic seal is used, the signed electronic seal is copied, etc.

[0079] In some embodiments, the movement trajectory of the signed digital seal can be recorded and tracked based on blockchain technology. For example, the tracking mark of the electronic seal can be stored on the blockchain, and when a preset condition is triggered, the system automatically retrieves the relevant records and returns the movement trajectory. Each use or movement of the seal can generate a new block, ensuring the data's non-tamperability and transparency.

[0080] Step 104, receiving a moving track of the signed digital seal by the user terminal after receiving the electronic seal signing result.

[0081] The moving track reflects the flow direction of the electronic seal signing result among different devices. The flow direction is the transfer order and transfer time of the electronic seal signing result among different devices.

[0082] In some embodiments, the use of the electronic seal signing result can also be considered as a flow and be recorded.

[0083] Step 105, constructing a track sequence Sa based on the track points in the moving track.

[0084] In some embodiments, each use or movement of the electronic seal signing result can generate a track point. The system can sort the track points according to the generation time, and then obtain the track sequence Sa.

[0085] Step 106, obtaining social data of the user within a preset time period, and constructing a track verification sequence Ya based on the device locations of the social objects in the social data.

[0086] The social data includes various data generated by the user when using the social media platform, including but not limited to text, pictures, videos, likes, comments, shares, etc., and related information of the devices generating these various data, such as geographic location, device type, and data generation time, etc.

[0087] The social data can reflect the social relationship network of the user, including the people followed, fans, friend list, etc. Therefore, the social data can reflect the potential flow direction of the electronic seal signing result to some extent.

[0088] In some embodiments, the system can determine the communication between the user and other social objects according to the relationship data and data generation time in the social data, and take the communication order (for example, file sending and receiving) and communication time with other social objects as track points, and construct the track verification sequence Ya based on these track points.

[0089] Step 107, calculating the similarity between the track sequence Sa and the track verification sequence Ya by the following formula (1): Wherein, d represents the similarity between the track sequence Sa and the track verification sequence Ya, λ is a preset adjustment parameter, which can be 0.1, 0.5, 0.8, etc., f is the frequency of the overlapping elements between the two sequences, and fs is the total frequency of the elements appearing in the two sequences.

[0090] In some embodiments, the frequency of the inter-sequence coincidence elements and the total frequency of the elements appearing in the sequences can be obtained based on the way of counting the elements in the two sequences.

[0091] Step 108, when the similarity is greater than the preset threshold, adding a security mark to the electronic seal signing result.

[0092] In some embodiments, the preset threshold can be 0.8, 0.9, or 0.95, etc. When the similarity is greater than the preset threshold, it means that the use and transfer of the electronic seal signing result matches the user's recent social comparison, which to some extent can reflect that the use of the electronic seal signing result is as expected, indicating that the electronic seal signing result does not appear to be lost or misused, etc.

[0093] Based on the same inventive concept, in some embodiments, when the similarity is less than the preset threshold, an invalid management procedure can be performed on the electronic seal signing result.

[0094] Exemplarily, performing the invalid management procedure on the electronic seal signing result can include the following operations:

[0095] S10, sending an abnormal prompt information to the user terminal.

[0096] The abnormal prompt information can be used to prompt the user that the use and transfer of the electronic seal signing result do not conform to the specification, ask the user to explain the relevant use and transfer situation, and inform the user that if the user fails to have a reasonable explanation for the abnormal situation, the electronic seal signing result will be invalidated, for example, the electronic seal signing result is marked as invalid, etc.

[0097] S11, receiving the user's feedback information returned according to the abnormal prompt information from the user terminal.

[0098] The feedback information is the feedback information proposed by the user after receiving the abnormal prompt information. For example, if the user encounters system crash or network failure, the user can submit a feedback to the system to explain the situation.

[0099] S12, determining the feedback type based on the feedback information.

[0100] The feedback type refers to the category of the feedback reason in the feedback information. This category reflects the objective type of the feedback reason proposed by the user, for example, an abnormality caused by human factors, an abnormality caused by non-human factors, an abnormality caused by user subjective operation, an abnormality caused by non-user subjective operation, etc.

[0101] S13, judging whether the feedback type is within the preset type range, if yes, determining whether the feedback passes based on the user's historical feedback information.

[0102] The preset type range refers to a preset claimable type. For example, the preset type range can include an abnormality caused by a human factor, an abnormality caused by a non-human factor, an abnormality caused by a non-subjective operation of a user, and the like.

[0103] In some embodiments, when it is determined that the user claim type is within the preset type range, historical claim information of the user can be further acquired, and it is determined whether the claim is passed based on the historical claim information.

[0104] In some embodiments, determining whether the claim is passed based on the historical claim information of the user can include the following operations.

[0105] S131, determining a historical claim frequency and a historical claim reason based on the historical claim information of the user.

[0106] S132, determining whether the historical claim frequency exceeds a first allowable value and whether the historical claim reason repeats a number of times exceeding a second allowable value.

[0107] The first allowable value includes a claimable time and a claim frequency, for example, one claim within half a year is allowed.

[0108] The second allowable value includes whether the claim reason is allowed to repeat and the number of times of repetition. For example, the claim reason is not allowed to repeat, and the number of times of repetition is 0. For another example, the claim reason is allowed to repeat, and the number of times of repetition does not exceed 3 times, and the like.

[0109] S133, determining that the user claim is passed when the historical claim frequency does not exceed the first allowable value and the historical claim reason repeats the number of times not exceeding the second allowable value.

[0110] S14, adding a security mark to the electronic seal signing result in response to the claim being passed.

[0111] S15, adding an invalid mark to the electronic seal signing result in response to the claim not being passed.

[0112] In some embodiments of the present specification, the security of the electronic seal cloud signing is improved by a multi-layer identity verification including operation environment verification, biometric verification, and biological behavior verification, and a digital seal tracking technology, and a digital seal tracking mark is added to the electronic seal signing result, so that the security management system can acquire the whereabouts of the electronic seal signing result after returning to the user terminal, and then construct a track sequence according to the flow direction of the electronic seal signing result, and verify whether the movement track of the electronic seal signing result is abnormal by using the social data of the user, which strengthens the security management after the electronic seal signing by combining the social big data of the user, and effectively improves the security of the electronic seal signing.

[0113] In some embodiments, after the user has filed a complaint, the system can also enhance the security management of the user's electronic seal signature by performing the following operations.

[0114] S20, obtaining the average number of complaints of other users. The average number of complaints can be used as a benchmark to measure whether the user's behavior is normal.

[0115] S21, determining whether the historical number of complaints of the user exceeds the average number of complaints. By determining whether the historical number of complaints of the user exceeds the calculated average number of complaints, if the number of complaints of the user is higher than the average, it indicates that the user account may have abnormal behavior or security risks.

[0116] S22, if yes, adding an observation mark for the user. If the historical number of complaints of the user exceeds the average number of complaints, by adding an observation mark for the user, it is used to remind the system administrator or the security team to conduct more stringent electronic seal signature security management for the user.

[0117] Steps S20 to S22 describe a monitoring system for electronic seal signature users, which is used to evaluate and manage the security of user accounts, by comparing the historical number of complaints of the user with the average number of complaints of other users, to identify accounts that may have security risks.

[0118] In some embodiments, the determination method of the mobile trajectory involved in the security management method of the electronic seal cloud is illustrated.

[0119] In some embodiments, the mobile trajectory of the signed digital seal can be determined by the following method.

[0120] S30, obtaining the geographical location information, MAC address information and storage time of the device storing the signed digital seal.

[0121] The storage time refers to the recording time when the signed digital seal is transferred to the device and stored in the storage space of the device, which can be recorded in the form of a timestamp.

[0122] S31, generating a trajectory point based on the geographical location information, MAC address information and storage time.

[0123] In some embodiments, the system can generate a trajectory point by converting the geographical location information, MAC address information and storage time into a feature vector. That is, one trajectory point can correspond to one feature vector.

[0124] Representing the trajectory point in the form of a feature vector can reduce the recording complexity of the trajectory point, and also facilitate the calculation of the similarity as described above.

[0125] S32, sort the track points corresponding to each device based on the sequence of the signed digital seal passing between different devices, to obtain the movement track.

[0126] In some embodiments, when generating the movement track, the system can also perform the following operations.

[0127] S40, monitor whether the signed digital seal is copied from the device or transferred to a removable storage device. This operation can be used to monitor the use and movement of the signed digital seal, to ensure that any unauthorized copying or transferring behavior can be discovered in a timely manner.

[0128] S41, in response to monitoring that the signed digital seal is transferred to a removable storage device. If the system monitors that the signed digital seal is transferred to a removable storage device, a response mechanism will be triggered.

[0129] S42, determine whether there is an isolated track point in the movement track. An isolated track point refers to a point in the movement track that is not connected to other points, or a point that does not conform to the regular movement pattern.

[0130] S43, if so, add a track path between the device that copies or transfers to the removable storage device and the isolated track point.

[0131] If there is an isolated track point in the movement track, the system will add a track path between the device that copies or transfers to the removable storage device and the isolated track point, thereby obtaining the complete path of the movement of the signed digital seal, including any abnormal or isolated movement points.

[0132] For example, if a signed digital seal is copied from the computer of employee A to a U disk, and the U disk is then taken to another office location, the system will monitor this transfer behavior and check whether there are any unusual isolated points in the movement track. If an isolated point is found, such as the U disk temporarily appearing at an unrelated location, for example, a print shop, during the transfer process, the system will record and display this isolated point in the track, thereby providing a more complete record of the movement path. This helps to ensure that the use and movement of the digital seal is transparent and traceable, preventing any potential misuse or fraudulent behavior, thereby strengthening the security management of electronic seal signing.

[0133] It has to be noted that, in the present document, relational terms are intended only to convey a possible relationship between elements or

[0134] The foregoing is considered as illustrative only of the principles of the application. Numerous modifications and changes will readily occur to those skilled in the art, which modifications and changes are to be understood as intended to be encompassed by the general scope of the application. Accordingly, the application is not to be limited to the above described ones; rather, the above described ones are to serve as a basis for the claims as they follow.

Claims

1. A secure management method for cloud-based electronic seal signing based on big data, characterized in that, The method includes: In response to receiving an electronic seal signing request from a user terminal, the system performs multi-layered authentication on the currently logged-in user of the user terminal; wherein, the multi-layered authentication includes operating environment verification, biometric verification, and biometric behavior verification. When the multi-level authentication is successful, electronic seal signing is performed; The electronic seal signing result is returned to the user terminal. The electronic seal signing result includes the signed digital seal and the digital seal tracking mark. The digital seal tracking mark is used to return the movement trajectory of the signed digital seal to the security management system when a preset condition is triggered. The system receives the movement trajectory of the signed digital seal after the user terminal receives the electronic seal signing result; the movement trajectory reflects the flow direction of the electronic seal signing result between different devices. A trajectory sequence Sa is constructed based on the trajectory points in the movement trajectory; Obtain the user's social data within a preset time period, and construct a trajectory verification sequence Ya based on the device location of the social objects in the social data; The similarity between the trajectory sequence Sa and the trajectory verification sequence Ya is calculated using the following formula: Where d represents the similarity between trajectory sequence Sa and trajectory verification sequence Ya, λ is a preset adjustment parameter, f is the frequency of overlapping elements between the two sequences, and fs is the total frequency of elements appearing in the two sequences; When the similarity is greater than a preset threshold, a security mark is added to the electronic seal signing result; The movement trajectory of the signed digital seal is as follows: Obtain the geographical location information, MAC address information, and storage time of the device storing the signed digital seal; Based on the geographic location information, MAC address information, and storage time, trajectory points are generated; Based on the circulation order of the signed digital seal among different devices, the trajectory points corresponding to each device are sorted to obtain the movement trajectory.

2. The method according to claim 1, characterized in that, in, The operating environment verification includes: Obtain a one-time password entered by the user, and match the one-time password with a verification code sent via SMS or email; and Obtain the operating environment of the user's one-time password input, and perform anomaly verification on the operating environment; The biovalidation includes: The user's identity is identified by at least one of fingerprint recognition, facial recognition, and voiceprint recognition; The biological behavior verification includes: The system obtains the user's typing speed, key pressure, and mouse movement trajectory over a preset time period. Based on the user's historical biometric behavior, anomalies in typing speed, key pressure, and mouse movement trajectory are verified.

3. The method according to claim 1, characterized in that, The method further includes: When the similarity is less than the preset threshold, an invalidation management procedure is executed on the electronic seal signing result, including: Send an error message to the user terminal; Receive the appeal information returned by the user based on the abnormal prompt information from the user terminal; The type of appeal is determined based on the appeal information; Determine whether the appeal type is within a preset range; if so, determine whether the appeal is approved based on the user's historical appeal information. In response to the successful appeal, a security mark is added to the electronic seal signing result; In response to the appeal being rejected, an invalidation mark is added to the electronic seal signing result.

4. The method according to claim 3, characterized in that, The process of determining whether an appeal is approved based on the user's historical appeal information includes: The number of historical complaints and the reasons for those complaints are determined based on the user's historical complaint information; Determine whether the number of historical appeals exceeds the first allowable value, and whether the number of times the reasons for the historical appeals are repeated exceeds the second allowable value; If the number of historical appeals does not exceed a first allowable value, and the number of times the reasons for the historical appeals are repeated does not exceed a second allowable value, the user's appeal is deemed approved.

5. The method according to claim 4, characterized in that, The method further includes: Get the average number of appeals from other users; Determine whether the user's historical number of appeals exceeds the average number of appeals; If so, add an observation tag for the user.

6. The method according to claim 1, characterized in that, The method further includes: Monitor whether the signed digital seal is copied from the device or transferred to a removable storage device; In response to the detection that the signed digital seal has been transferred to a removable storage device; Determine whether there are isolated trajectory points in the movement trajectory; If so, add a trajectory path between the device that was copied or transferred to a removable storage device and the isolated trajectory point.

7. A secure management system for cloud-based electronic seal signing based on big data, characterized in that, The system includes: The authentication module is used to perform multi-level authentication on the currently logged-in user of the user terminal in response to receiving an electronic seal signing request from the user terminal; wherein, the multi-level authentication includes operating environment authentication, biometric authentication and biometric behavior authentication; The seal signing module is used to perform electronic seal signing when the multi-level authentication is successful; The data sending module is used to return the electronic seal signing result to the user terminal. The electronic seal signing result includes the signed digital seal and the digital seal tracking mark. The digital seal tracking mark is used to return the movement trajectory of the signed digital seal to the security management system when a preset condition is triggered. The data receiving module is used to receive the movement trajectory of the signed digital seal after the user terminal receives the electronic seal signing result; the movement trajectory reflects the flow direction of the electronic seal signing result between different devices; The trajectory verification module is used to construct a trajectory sequence Sa based on the trajectory points in the movement trajectory; Obtain the user's social data within a preset time period, and construct a trajectory verification sequence Ya based on the device location of the social objects in the social data; The similarity between the trajectory sequence Sa and the trajectory verification sequence Ya is calculated using the following formula: Where d represents the similarity between trajectory sequence Sa and trajectory verification sequence Ya, λ is a preset adjustment parameter, f is the frequency of overlapping elements between the two sequences, and fs is the total frequency of elements appearing in the two sequences; The marking module is used to add a security mark to the electronic seal signing result when the similarity is greater than a preset threshold; The movement trajectory of the signed digital seal is as follows: Obtain the geographical location information, MAC address information, and storage time of the device storing the signed digital seal; Based on the geographic location information, MAC address information, and storage time, trajectory points are generated; Based on the circulation order of the signed digital seal among different devices, the trajectory points corresponding to each device are sorted to obtain the movement trajectory.

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