An artificial intelligence-based electronic signature security management system

Abstract

The present invention relates to the technical field of electronic signature security management, and in particular to an electronic signature use security management system based on artificial intelligence, which is used to solve the problem that the storage and use security and reliability of the existing electronic signature use security management system are not high, and are easy to cause huge losses to enterprises and individuals; the system comprises a storage management module, a data analysis module, a security evaluation module, an abnormality alarm module and a use management module; the system uses multi-faceted monitoring to cover the entire process of storage and use of electronic signatures, and uses artificial intelligence algorithms to perform abnormality identification and risk warning, ensuring that potential security risks are monitored without omission, improving the accuracy and efficiency of monitoring, and effectively improving the security and reliability of electronic signatures. The system can provide enterprises and individuals with safer, more convenient and efficient electronic signature services, and promote the wide application and development of electronic signature technology in various fields.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic signature security management, and in particular to an electronic signature use security management system based on artificial intelligence. Background Art

[0002] Electronic signature is a form of electronic signature. It uses image processing technology to transform the electronic signature operation into the same visual effect as the paper document stamping operation. At the same time, it uses electronic signature technology to ensure the authenticity and integrity of electronic information and the non-repudiation of the signer. With the rapid development of information technology and the popularization of online office, electronic signature, as an important means of authentication, plays an increasingly important role in contract signing, document confirmation and other fields. However, the security risks in the storage and use of electronic signatures cannot be ignored. Traditional electronic signature monitoring systems often rely on manual inspection or simple rule matching, which makes it difficult to comprehensively and efficiently respond to complex and changing security threats, such as storage medium damage, data leakage, illegal tampering, and abnormal operations during use.

[0003] In view of the above-mentioned technical defects, the present invention proposes an artificial intelligence-based electronic signature usage security management system, which is of great significance for improving the security and reliability of the storage and use of electronic signatures. Summary of the invention

[0004] In order to overcome the above-mentioned technical problems, the purpose of the present invention is to provide an electronic signature security management system based on artificial intelligence, which solves the problem that the storage and usage security management systems of existing electronic signatures are not secure and reliable, and are prone to cause huge losses to enterprises and individuals.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] An artificial intelligence-based electronic signature security management system, including:

[0007] The storage management module is used to monitor the storage status of the electronic signature, obtain the storage management information of the storage detection object, and send the storage management information to the data analysis module; wherein the storage management information includes read-write information DX, access information FW, remaining storage information YC and count information SCa;

[0008] A data analysis module, used for obtaining a storage management analysis coefficient CX according to the storage management information, and sending the storage management analysis coefficient CX to the safety evaluation module;

[0009] The specific process of the data analysis module obtaining the storage management analysis coefficient CX is as follows:

[0010] Normalizing the read / write information DX, the access information FW, the remaining storage information YC and the number of times information SCa, and performing quantization operation on the values ​​of the read / write information DX, the access information FW, the remaining storage information YC and the number of times information SCa according to a preset storage management analysis model to obtain a storage management analysis coefficient CX;

[0011] The storage management analysis model is as follows: Where:

[0012] λ is the preset error adjustment factor, and λ=1.104 is taken;

[0013] π and e are both mathematical constants;

[0014] α1, α2, α3 and α4 are respectively the preset weight factors corresponding to the set read / write information DX, access information FW, remaining storage information YC and number of times information SCa, α1, α2, α3 and α4 satisfy α2>α1>α3>α4>1.629, α1=2.76, α2=3.18, α3=2.24, α4=1.89;

[0015] A safety evaluation module, used for generating a storage abnormality instruction or a usage management instruction according to the storage management analysis coefficient CX, and sending the storage abnormality instruction to the abnormal alarm module, and sending the usage management instruction to the usage management module;

[0016] The abnormality alarm module is used to sound a storage abnormality alarm ring after receiving a storage abnormality instruction.

[0017] As a further solution of the present invention: the specific process of the storage management module obtaining storage management information is as follows:

[0018] Marking the storage medium storing the electronic signature as a storage detection object;

[0019] Obtain the data reading and writing rate during the most recent use of the storage detection object and the data reading and writing rate during the initial use, obtain the difference between the two, and mark it as reading and writing information DX;

[0020] Obtain the number of unauthorized successful accesses, the number of data lost bytes, and the number of data tampered bytes of the storage detection object within the recent preset time, and mark them as access value FC, loss value DS, and tampered value CG respectively, quantify the access value FC, loss value DS, and tampered value CG, extract the values ​​of the access value FC, loss value DS, and tampered value CG, and substitute them into the formula for calculation. Get access information FW; where e is a mathematical constant, f1, f2 and f3 are preset proportional coefficients corresponding to the set access value FC, loss value DS and tampering value CG respectively, f1, f2 and f3 satisfy f1+f2+f3=1, 0<f2<f3<f1<1, f1=0.42, f2=0.25, f3=0.33; where the storage detection object needs account password verification when being accessed, access after successful verification is authorized successful access, and access after failed verification is unauthorized successful access;

[0021] Obtain the remaining storage capacity and the total storage capacity of the storage detection object, and mark them as the remaining capacity value YR and the total capacity value ZR respectively, obtain the ratio of the remaining capacity value YR to the total capacity value ZR, and mark it as the remaining storage information YC;

[0022] Obtain the total number of stored data and the total number of times the stored data is stored in the storage detection object, and mark them as the storage value CS and the storage value CC respectively, draw an ellipse figure with the storage value CS and the storage value CC as the semi-major axis and the semi-minor axis of the ellipse respectively, obtain the area of ​​the ellipse figure, and mark it as the number of times information SCa;

[0023] The read / write information DX, access information FW, remaining storage information YC and number of times information SCa are sent to the data analysis module.

[0024] As a further solution of the present invention: the specific process of the security evaluation module generating a storage exception instruction or a use management instruction is as follows:

[0025] The storage management analysis coefficient CX is compared with the preset storage management analysis threshold CXy. The comparison results are as follows:

[0026] If the storage management analysis coefficient CX≥ the storage management analysis threshold CXy, a storage abnormality instruction is generated and sent to the abnormality alarm module;

[0027] If the storage management analysis coefficient CX<storage management analysis threshold CXy, a usage management instruction is generated and sent to the usage management module.

[0028] As a further solution of the present invention: the artificial intelligence-based electronic signature use security management system further includes:

[0029] The usage management module is used to monitor the usage of the electronic signature after receiving the usage management instruction, obtain the usage management information of the electronic signature, and send the usage management information to the data analysis module; wherein the usage management information includes time information SJ, input number information SCb and distance information JL.

[0030] As a further solution of the present invention: the specific process of the usage management module obtaining the usage management information is as follows:

[0031] After receiving the use management instruction, the time when the account and password input window is displayed when the storage detection object is accessed and the time when the account and password are correctly entered and the electronic signature is displayed are obtained, and the time difference between the two is obtained and marked as the input time value SS, the median of all the input time values ​​SS in the historical data is obtained and marked as the duration value LS, and the difference between the input time value SS and the duration value LS is obtained and marked as the time information SJ; wherein, if the account and password are continuously not correctly entered and the electronic signature cannot be displayed, the time information SJ=ζ, and ζ is a preset mathematical constant;

[0032] Obtain the total number of times the detection object enters the account and password within a preset time period from the moment the account and password input window is displayed, and mark it as input number information SCb;

[0033] Obtain the location where the storage detection object is accessed and mark it as the real-time location, obtain all the real-time locations in the storage detection object history data and mark them as the historical locations, obtain the sum of the distances between the real-time location and all the historical locations and mark it as the distance information JL;

[0034] The time information SJ, input frequency information SCb and distance information JL are sent to the data analysis module.

[0035] As a further solution of the present invention: the data analysis module is also used to obtain the usage management analysis coefficient SX according to the usage management information, and send the usage management analysis coefficient SX to the safety evaluation module.

[0036] As a further solution of the present invention: the specific process of the data analysis module obtaining the usage management analysis coefficient SX is as follows:

[0037] Normalize the time information SJ, the input frequency information SCb and the distance information JL, and quantify the values ​​of the time information SJ, the input frequency information SCb and the distance information JL according to a preset usage management analysis model to obtain a usage management analysis coefficient SX;

[0038] Among them, the usage management analysis model is as follows: Where:

[0039] κ is the preset error adjustment factor, taking κ=0.936;

[0040] e and π are both mathematical constants;

[0041] β1, β2 and β3 are preset weight factors corresponding to the set time information SJ, input frequency information SCb and distance information JL respectively, β1, β2 and β3 satisfy β1>β2>β3>2.012, and β1=3.15, β2=2.74, β3=2.18;

[0042] The usage management analysis coefficient SX is sent to the safety evaluation module.

[0043] As a further solution of the present invention: the safety evaluation module is also used to generate an abnormal usage instruction according to the usage management analysis coefficient SX, and send the abnormal usage instruction to the abnormal alarm module.

[0044] As a further solution of the present invention: the specific process of the safety evaluation module generating and using abnormal instructions is as follows:

[0045] The usage management analysis coefficient SX is compared with the preset usage management analysis threshold SXy, and the comparison results are as follows:

[0046] If the usage management analysis coefficient SX ≥ the usage management analysis threshold SXy, a usage abnormality instruction is generated and sent to the abnormality alarm module.

[0047] As a further solution of the present invention: the abnormal alarm module is also used to sound an abnormal use alarm ring after receiving an abnormal use instruction.

[0048] Beneficial effects of the present invention:

[0049] The electronic signature use security management system based on artificial intelligence of the present invention first collects data on the storage of electronic signatures to obtain storage management information, then uses an artificial intelligence algorithm to obtain a storage management analysis coefficient based on the storage management information to comprehensively measure the degree of storage anomaly of the electronic signature, and the larger the storage management analysis coefficient, the higher the degree of storage anomaly, then collects data on the use of the electronic signature to obtain use management information, then uses an artificial intelligence algorithm to obtain a use management analysis coefficient based on the use management information to comprehensively measure the degree of use anomaly of the electronic signature, and the larger the use management analysis coefficient, the higher the degree of use anomaly, and finally issues an abnormal alarm;

[0050] The electronic signature security management system based on artificial intelligence of the present invention can cover the entire process of storage and use of electronic signatures through multi-faceted monitoring, and uses artificial intelligence algorithms for abnormality identification and risk warning, ensuring that potential security risks are monitored without omissions, improving the accuracy and efficiency of monitoring, and effectively improving the security and reliability of electronic signatures. The system can provide enterprises and individuals with safer, more convenient and efficient electronic signature services, and promote the widespread application and development of electronic signature technology in various fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The present invention will be further described below in conjunction with the accompanying drawings.

[0052] Figure 1 It is a structural diagram of an artificial intelligence-based electronic signature security management system in the present invention;

[0053] Figure 2 It is a flow chart of a working method of an artificial intelligence-based electronic signature security management system in the present invention. DETAILED DESCRIPTION

[0054] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] Example 1

[0056] This embodiment is an artificial intelligence-based electronic signature use security management system, which includes the following modules: a storage management module, a data analysis module, a security evaluation module, an abnormal alarm module, and a use management module;

[0057] The storage management module is used to monitor the storage status of the electronic signature, obtain the storage management information of the storage detection object, and send the storage management information to the data analysis module; wherein the storage management information includes read-write information DX, access information FW, remaining storage information YC and number of times information SCa;

[0058] The data analysis module is used to obtain a storage management analysis coefficient CX according to the storage management information, and send the storage management analysis coefficient CX to the safety evaluation module; and is also used to obtain a usage management analysis coefficient SX according to the usage management information, and send the usage management analysis coefficient SX to the safety evaluation module;

[0059] The safety evaluation module is used to generate a storage abnormality instruction or a usage management instruction according to the storage management analysis coefficient CX, and send the storage abnormality instruction to the abnormal alarm module, and send the usage management instruction to the usage management module; it is also used to generate a usage abnormality instruction according to the usage management analysis coefficient SX, and send the usage abnormality instruction to the abnormal alarm module;

[0060] The abnormal alarm module is used to sound a storage abnormality alarm ring after receiving a storage abnormality instruction; and is also used to sound a use abnormality alarm ring after receiving a use abnormality instruction;

[0061] Among them, the usage management module is used to monitor the usage of the electronic signature after receiving the usage management instruction, obtain the usage management information of the electronic signature, and send the usage management information to the data analysis module; wherein the usage management information includes time information SJ, input information SCb and distance information JL.

[0062] Example 2

[0063] This embodiment is a working method of an electronic signature security management system based on artificial intelligence, including the following steps:

[0064] Step 1: The storage management module monitors the storage status of the electronic signature, obtains the storage management information of the storage detection object, wherein the storage management information includes read-write information DX, access information FW, remaining storage information YC and count information SCa, and sends the storage management information to the data analysis module;

[0065] Step 2: The data analysis module obtains the storage management analysis coefficient CX according to the storage management information, and sends the storage management analysis coefficient CX to the safety evaluation module;

[0066] Step 3: The safety evaluation module generates a storage abnormality instruction or a usage management instruction according to the storage management analysis coefficient CX, and sends the storage abnormality instruction to the abnormal alarm module, and sends the usage management instruction to the usage management module;

[0067] Step 4: After receiving the storage abnormality instruction, the abnormality alarm module sounds the storage abnormality alarm bell;

[0068] Step 5: After receiving the usage management instruction, the usage management module monitors the usage of the electronic signature, obtains the usage management information of the electronic signature, wherein the usage management information includes time information SJ, input number information SCb and distance information JL, and sends the usage management information to the data analysis module;

[0069] Step 6: The data analysis module obtains the usage management analysis coefficient SX according to the usage management information, and sends the usage management analysis coefficient SX to the safety evaluation module;

[0070] Step 7: The safety evaluation module generates an abnormal use instruction according to the use management analysis coefficient SX, and sends the abnormal use instruction to the abnormal alarm module;

[0071] Step 8: After receiving the abnormal use instruction, the abnormal use alarm module sounds an abnormal use alarm bell.

[0072] Example 3

[0073] Based on any of the above embodiments, Embodiment 3 of the present invention is a storage management module. The function of the storage management module is to obtain storage management information, wherein the storage management information includes read-write information DX, access information FW, remaining storage information YC and number of times information SCa. The specific process is as follows:

[0074] The storage management module marks the storage medium storing the electronic signature as a storage detection object;

[0075] The storage management module obtains the data reading and writing rate during the most recent use of the storage detection object and the data reading and writing rate during the initial use, obtains the difference between the two, and marks it as the reading and writing information DX;

[0076] The storage management module obtains the number of unauthorized successful accesses, the number of data lost bytes, and the number of data tampered bytes of the storage detection object within the recent preset time, and marks them as access value FC, loss value DS, and tampered value CG, respectively, quantifies the access value FC, loss value DS, and tampered value CG, extracts the values ​​of the access value FC, loss value DS, and tampered value CG, and substitutes them into the formula for calculation. Get access information FW; where e is a mathematical constant, f1, f2 and f3 are preset proportional coefficients corresponding to the set access value FC, loss value DS and tampering value CG respectively, f1, f2 and f3 satisfy f1+f2+f3=1, 0<f2<f3<f1<1, f1=0.42, f2=0.25, f3=0.33; where the storage detection object needs account password verification when being accessed, access after successful verification is authorized successful access, and access after failed verification is unauthorized successful access;

[0077] The storage management module obtains the remaining storage capacity and the total storage capacity of the storage detection object, and marks them as the remaining capacity value YR and the total capacity value ZR respectively, obtains the ratio of the remaining capacity value YR to the total capacity value ZR, and marks it as the remaining storage information YC;

[0078] The storage management module obtains the total amount of data stored in the storage detection object and the total number of times the data is stored, and marks them as a storage value CS and a storage value CC respectively, draws an ellipse figure with the storage value CS and the storage value CC as the semi-major axis and the semi-minor axis of the ellipse respectively, obtains the area of ​​the ellipse figure, and marks it as the number of times information SCa;

[0079] The storage management module sends the read / write information DX, access information FW, remaining storage information YC and count information SCa to the data analysis module.

[0080] Example 4

[0081] Based on any of the above embodiments, Embodiment 4 of the present invention is a data analysis module, and the data analysis module has two functions:

[0082] One of the functions is to obtain the storage management analysis coefficient CX. The specific process is as follows:

[0083] The data analysis module normalizes the read / write information DX, the access information FW, the remaining storage information YC and the number of times information SCa, and quantifies the values ​​of the read / write information DX, the access information FW, the remaining storage information YC and the number of times information SCa according to a preset storage management analysis model to obtain a storage management analysis coefficient CX;

[0084] The storage management analysis model is as follows: Where:

[0085] λ is the preset error adjustment factor, and λ=1.104 is taken;

[0086] π and e are both mathematical constants;

[0087] α1, α2, α3 and α4 are respectively the preset weight factors corresponding to the set read / write information DX, access information FW, remaining storage information YC and number of times information SCa, α1, α2, α3 and α4 satisfy α2>α1>α3>α4>1.629, α1=2.76, α2=3.18, α3=2.24, α4=1.89;

[0088] The data analysis module sends the storage management analysis coefficient CX to the safety evaluation module;

[0089] The second function is to obtain the usage management analysis coefficient SX. The specific process is as follows:

[0090] The data analysis module normalizes the time information SJ, the input frequency information SCb and the distance information JL, and quantifies the values ​​of the time information SJ, the input frequency information SCb and the distance information JL according to the preset usage management analysis model to obtain the usage management analysis coefficient SX;

[0091] Among them, the usage management analysis model is as follows: Where:

[0092] κ is the preset error adjustment factor, taking κ=0.936;

[0093] e and π are both mathematical constants;

[0094] β1, β2 and β3 are preset weight factors corresponding to the set time information SJ, input frequency information SCb and distance information JL respectively, β1, β2 and β3 satisfy β1>β2>β3>2.012, and β1=3.15, β2=2.74, β3=2.18;

[0095] The data analysis module sends the usage management analysis coefficient SX to the safety evaluation module.

[0096] Example 5

[0097] Based on any of the above embodiments, Embodiment 5 of the present invention is a safety evaluation module, which has two functions:

[0098] One of the functions is to generate storage exception instructions or use management instructions. The specific process is as follows:

[0099] The safety evaluation module compares the storage management analysis coefficient CX with the preset storage management analysis threshold CXy. The comparison results are as follows:

[0100] If the storage management analysis coefficient CX≥ the storage management analysis threshold CXy, a storage abnormality instruction is generated and sent to the abnormality alarm module;

[0101] If the storage management analysis coefficient CX is less than the storage management analysis threshold CXy, a usage management instruction is generated and sent to the usage management module;

[0102] The second function is to generate and use exception instructions. The specific process is as follows:

[0103] The safety evaluation module compares the usage management analysis coefficient SX with the preset usage management analysis threshold SXy. The comparison results are as follows:

[0104] If the usage management analysis coefficient SX ≥ the usage management analysis threshold SXy, a usage abnormality instruction is generated and sent to the abnormality alarm module.

[0105] Example 6

[0106] Based on any of the above embodiments, Embodiment 6 of the present invention is an abnormal alarm module, and the abnormal alarm module has two functions:

[0107] One function is to sound a storage abnormality alarm bell after receiving a storage abnormality instruction;

[0108] The second function is to sound an abnormal use alarm bell after receiving an abnormal use instruction.

[0109] Example 7

[0110] Based on any of the above embodiments, Embodiment 7 of the present invention is a usage management module, and the usage management module is used to obtain usage management information, wherein the usage management information includes time information SJ, input times information SCb and distance information JL. The specific process is as follows:

[0111] After receiving the usage management instruction, the usage management module obtains the time when the account and password input window is displayed when the storage detection object is accessed and the time when the account and password are correctly entered and the electronic signature is displayed, obtains the time difference between the two, and marks it as the input time value SS, obtains the median of all the input time values ​​SS in the historical data, and marks it as the duration value LS, obtains the difference between the input time value SS and the duration value LS, and marks it as time information SJ; wherein, if the account and password are continuously not correctly entered and the electronic signature cannot be displayed, then the time information SJ=ζ, and ζ is a preset mathematical constant;

[0112] Use the management module to obtain the total number of times the storage detection object enters the account and password within a preset time period from the moment the account and password input window is displayed, and mark it as input number information SCb;

[0113] Use the management module to obtain the location where the storage detection object is accessed, and mark it as a real-time location, obtain all real-time locations in the storage detection object history data, and mark them as historical locations, obtain the sum of the distances between the real-time location and all historical locations, and mark it as distance information JL;

[0114] The usage management module sends the time information SJ, input frequency information SCb and distance information JL to the data analysis module.

[0115] Based on the above embodiments 1-7, the working principle of the present invention is as follows:

[0116] The present invention provides an artificial intelligence-based electronic signature usage security management system, which monitors the storage status of the electronic signature through a storage management module, obtains storage management information of the storage detection object, wherein the storage management information includes read-write information, access information, remaining storage information and number of times information, obtains a storage management analysis coefficient according to the storage management information through a data analysis module, generates a storage abnormality instruction or a usage management instruction according to the storage management analysis coefficient through a security evaluation module, sounds a storage abnormality alarm bell after receiving the storage abnormality instruction through an abnormal alarm module, monitors the usage status of the electronic signature after receiving the usage management instruction through a usage management module, obtains the usage management information of the electronic signature, wherein the usage management information includes time information, input times information and distance information, obtains a usage management analysis coefficient according to the usage management information through a data analysis module, generates a usage abnormality instruction according to the usage management analysis coefficient through a security evaluation module, and sounds a usage abnormality alarm bell after receiving the usage abnormality instruction through an abnormal alarm module; the system first First, data collection is performed on the storage status of the electronic signature to obtain storage management information. Then, the storage management analysis coefficient obtained based on the storage management information using an artificial intelligence algorithm can comprehensively measure the degree of storage anomalies of the electronic signature, and the larger the storage management analysis coefficient, the higher the degree of storage anomalies. Then, data collection is performed on the usage of the electronic signature to obtain usage management information. Then, the usage management analysis coefficient obtained based on the usage management information using an artificial intelligence algorithm can comprehensively measure the degree of usage anomalies of the electronic signature, and the larger the usage management analysis coefficient, the higher the degree of usage anomalies. Finally, an abnormal alarm is issued; the system uses multi-faceted monitoring to cover the entire process of storage and use of electronic signatures, and uses artificial intelligence algorithms for anomaly identification and risk warning, ensuring that potential security risks are monitored without omissions, improving the accuracy and efficiency of monitoring, and effectively improving the security and reliability of electronic signatures. The system can provide enterprises and individuals with safer, more convenient and efficient electronic signature services, and promote the widespread application and development of electronic signature technology in various fields.

[0117] It should be further explained that the above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The coefficients in the formula are set by technical personnel in this field according to actual conditions.

[0118] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0119] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.

Claims

1. An artificial intelligence-based electronic signature security management system, characterized in that: include: The storage management module is used to monitor the storage status of the electronic signature, obtain the storage management information of the storage detection object, and send the storage management information to the data analysis module; wherein the storage management information includes read-write information DX, access information FW, remaining storage information YC and count information SCa; According to the formula Access information FW is obtained; wherein e is a mathematical constant, and f1, f2 and f3 are preset proportional coefficients corresponding to the set access value FC, loss value DS and tampering value CG respectively; Obtain the remaining storage capacity and the total storage capacity of the storage detection object, and mark them as the remaining capacity value YR and the total capacity value ZR respectively, obtain the ratio of the remaining capacity value YR to the total capacity value ZR, and mark it as the remaining storage information YC; Obtain the total number of stored data and the total number of times the stored data is stored in the storage detection object, and mark them as the storage value CS and the storage value CC respectively, draw an ellipse figure with the storage value CS and the storage value CC as the semi-major axis and the semi-minor axis of the ellipse respectively, obtain the area of ​​the ellipse figure, and mark it as the number of times information SCa; A data analysis module, used for obtaining a storage management analysis coefficient CX according to the storage management information, and sending the storage management analysis coefficient CX to the safety evaluation module; The specific process of the data analysis module obtaining the storage management analysis coefficient CX is as follows: The values ​​of the read / write information DX, the access information FW, the remaining storage information YC and the number of times information SCa are quantified according to a preset storage management analysis model to obtain a storage management analysis coefficient CX; The storage management analysis model is as follows: Where: λ is the preset error adjustment factor; π and e are both mathematical constants; α1, α2, α3 and α4 are respectively the preset weight factors corresponding to the set read / write information DX, access information FW, remaining storage information YC and number of times information SCa; A safety evaluation module, used for generating a storage abnormality instruction or a usage management instruction according to the storage management analysis coefficient CX, and sending the storage abnormality instruction to the abnormal alarm module, and sending the usage management instruction to the usage management module; The abnormality alarm module is used to sound a storage abnormality alarm ring after receiving a storage abnormality instruction.

2. According to the artificial intelligence-based electronic signature security management system of claim 1, it is characterized in that: The specific process of the security assessment module generating a storage exception instruction or a usage management instruction is as follows: The storage management analysis coefficient CX is compared with the preset storage management analysis threshold CXy. The comparison results are as follows: If the storage management analysis coefficient CX≥ the storage management analysis threshold CXy, a storage abnormality instruction is generated and sent to the abnormality alarm module; If the storage management analysis coefficient CX<storage management analysis threshold CXy, a usage management instruction is generated and sent to the usage management module.

3. According to the artificial intelligence-based electronic signature security management system of claim 1, it is characterized in that: Also includes: The usage management module is used to monitor the usage of the electronic signature after receiving the usage management instruction, obtain the usage management information of the electronic signature, and send the usage management information to the data analysis module; wherein the usage management information includes time information SJ, input number information SCb and distance information JL.

4. According to claim 3, the artificial intelligence-based electronic signature security management system is characterized in that: The specific process of the usage management module obtaining usage management information is as follows: After receiving the use management instruction, obtain the time when the account and password input window is displayed when the storage detection object is accessed and the time when the account and password are correctly entered and the electronic signature is displayed, obtain the time difference between the two, and mark it as the input time value SS, obtain the median of all the input time values ​​SS in the historical data, and mark it as the duration value LS, obtain the difference between the input time value SS and the duration value LS, and mark it as time information SJ; Obtain the total number of times the detection object enters the account and password within a preset time period from the moment the account and password input window is displayed, and mark it as input number information SCb; Obtain the location where the storage detection object is accessed and mark it as the real-time location, obtain all the real-time locations in the storage detection object history data and mark them as the historical locations, obtain the sum of the distances between the real-time location and all the historical locations and mark it as the distance information JL; The time information SJ, input frequency information SCb and distance information JL are sent to the data analysis module.

5. According to the artificial intelligence-based electronic signature security management system of claim 1, it is characterized in that: The data analysis module is also used to obtain a usage management analysis coefficient SX according to the usage management information, and send the usage management analysis coefficient SX to the safety evaluation module.

6. According to claim 5, the artificial intelligence-based electronic signature security management system is characterized in that: The specific process of the data analysis module obtaining the usage management analysis coefficient SX is as follows: The values ​​of the time information SJ, the input frequency information SCb and the distance information JL are quantified according to the preset usage management analysis model to obtain the usage management analysis coefficient SX; Among them, the usage management analysis model is as follows: Where: κ is the preset error adjustment factor; e and π are both mathematical constants; β1, β2 and β3 are preset weight factors corresponding to the set time information SJ, input frequency information SCb and distance information JL respectively; The usage management analysis coefficient SX is sent to the safety evaluation module.

7. According to the artificial intelligence-based electronic signature security management system of claim 1, it is characterized in that: The safety evaluation module is also used to generate an abnormal usage instruction according to the usage management analysis coefficient SX, and send the abnormal usage instruction to the abnormal alarm module.

8. According to claim 7, the artificial intelligence-based electronic signature security management system is characterized in that: The specific process of the safety evaluation module generating and using abnormal instructions is as follows: The usage management analysis coefficient SX is compared with the preset usage management analysis threshold SXy, and the comparison results are as follows: If the usage management analysis coefficient SX ≥ the usage management analysis threshold SXy, a usage abnormality instruction is generated and sent to the abnormality alarm module.

9. According to the artificial intelligence-based electronic signature security management system of claim 1, it is characterized in that: The abnormal alarm module is also used to sound an abnormal use alarm ring after receiving an abnormal use instruction.

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