Dynamic password generation system for mobile equipment

Abstract

The invention discloses a dynamic password generation system for mobile equipment. The dynamic password generation system comprises a transaction risk assessment module, a user data packaging module, a dynamic factor verification module, an emotion monitoring verification module and an early warning and blocking service module, wherein the transaction risk assessment module is suitable for assessing the current transaction environment risk when the equipment enters a financial transaction period; the user data packaging module is used for collecting associated data of mobile equipment used by a user and packaging and uploading the associated data to the block chain service network; the dynamic factor verification module is used for adding a dynamic factor verification mechanism based on user behaviors after responding to an evaluation result of the transaction risk evaluation module; and the emotion monitoring verification module is used for further adding a user emotion factor verification mechanism on the basis of the dynamic factor verification mechanism of the user behavior after responding to the evaluation result of the transaction risk evaluation module.

Description

Technical Field

[0001] The present invention relates to the technical field of information security, and in particular to a dynamic password generation system for mobile devices. Background Art

[0002] In the digital age, mobile devices, as the central hub of personal information, frequently participate in users' daily financial transactions, social interactions and online services. However, this convenience is also accompanied by huge security risks, especially when users encounter carefully designed telecommunications fraud, especially Ponzi schemes, during the operation of mobile devices, their financial and personal information security is often seriously threatened.

[0003] Traditional authentication mechanisms, such as static passwords or simple dynamic passwords, are powerless in the face of such highly disguised and carefully planned frauds. They often fail to effectively distinguish between legitimate requests and fraud attempts, causing users to leak critical information or funds without knowing it. Therefore, in order to improve users' anti-fraud capabilities when operating on mobile devices, a more powerful dynamic password generation system with intelligent identity authentication and risk identification is urgently needed. Summary of the invention

[0004] The purpose of the present invention is to provide a dynamic password generation system for a mobile device to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a dynamic password generation system for mobile devices, including a transaction risk assessment module, a user data packaging module, a dynamic factor verification module, an emotion monitoring verification module and an early warning and blocking service module, wherein each module is connected through a signal; wherein,

[0006] The transaction risk assessment module is applicable to assess the current transaction environment risk when the device enters into a financial transaction period;

[0007] The user data packaging module is used to collect the associated data of the user using the mobile device and package it and upload it to the blockchain service network;

[0008] The dynamic factor verification module is used to add a dynamic factor verification mechanism based on user behavior in response to the evaluation result of the transaction risk evaluation module;

[0009] The emotion monitoring verification module is used to respond to the evaluation result of the transaction risk evaluation module and further add a user emotion factor verification mechanism based on the dynamic factor verification mechanism of user behavior;

[0010] The early warning and blocking service module is used to warn financial transaction programs and block suspicious transactions based on the verification results of the multi-factor dynamic password mechanism.

[0011] According to the above technical solution, the transaction risk assessment module includes a transaction amount collection module, a transaction frequency collection module and a transaction object collection module; wherein,

[0012] The transaction amount collection module is used to collect the amount of a single transaction during a financial transaction;

[0013] The transaction frequency collection module is used to collect and monitor the user's historical financial transaction frequency based on the financial transaction period;

[0014] The transaction object collection module is used to collect transaction objects during financial transactions.

[0015] According to the above technical solution, the user data packaging module includes a user operation data storage module and a user face data storage module; wherein,

[0016] The user operation data storage module is used to collect and record the standard operation data of the user operating the mobile device;

[0017] The user facial data storage module is used to collect facial data of the user during operation of the mobile device and record and store it.

[0018] According to the above technical solution, the dynamic factor verification module includes a sliding trajectory tracking module, an operation timing module and a touch sensing module; wherein,

[0019] The sliding track tracking module is used to collect and continuously track the sliding track of the user's gestures on the operating screen when operating the mobile device during the financial transaction;

[0020] The operation timing module is adapted to collect and time the operation interval between the previous and next operation actions of the user operating the mobile device during the financial transaction;

[0021] The touch sensing module is used to collect the touch pressure distribution area of ​​the user's gesture on the operating screen when the user operates the mobile device during a financial transaction.

[0022] According to the above technical solution, the emotion monitoring verification module includes a camera call unit, a brow recognition module and a contour fitting module, the camera call unit is connected to the brow recognition module by signal, and the brow recognition module is connected to the contour fitting module by signal; wherein,

[0023] The camera calling unit is used to call the camera permission of the mobile device during the financial transaction based on the evaluation result of the transaction risk evaluation module;

[0024] The eyebrow recognition module is used to monitor the picture in real time according to the camera calling unit, and track the user's eyebrow information in the monitored picture based on the preset eyebrow features;

[0025] The contour fitting module is used to fit the user's eyebrow contour and output eyebrow contour change data during the monitoring period.

[0026] According to the above technical solution, the operation method of the dynamic password generation system includes the following steps:

[0027] Step S1: in response to monitoring that a mobile device enters a transaction program, a transaction risk assessment module is started to collect the current financial transaction amount, the transaction frequency within the period monitored by the system, and the current transaction object data;

[0028] Step S2: Then, based on the collected data in step S1, the risk of the current transaction environment is evaluated, and the evaluation results are divided into a low-risk environment, a medium-risk environment, and a high-risk environment;

[0029] Step S3: When the evaluation result is a low-risk environment, the system outputs a dynamic password in the financial transaction link to perform security verification of the transaction environment;

[0030] Step S4: When the assessment result is a medium-risk environment, the system first outputs a dynamic password in the financial transaction link to perform security verification of the transaction environment. If the dynamic password verification is successful, the dynamic factor verification module is started to perform a secondary verification on the current transaction;

[0031] Step S5: When the evaluation result is a high-risk environment, the system first outputs a dynamic password in the financial transaction link to perform security verification of the transaction environment. If the dynamic password verification is successful, the dynamic factor verification module is started to perform a second verification on the current transaction. If the second verification is successful, the emotion monitoring verification module is started again to perform a third verification on the current transaction.

[0032] Step S6: Obtain the final verification results of steps S3-S5. When the security verification result of any step is "verification failure", it is judged as a "suspicious transaction" and the current financial transaction program is warned and blocked.

[0033] According to the above technical solution, step S2 further includes:

[0034] Step S21: When the single financial transaction amount is less than RMB 1,000, the historical transaction frequency is less than once a day, and the transaction object is not a "new transaction object", the environment is evaluated as a "low-risk environment" when the above three points are met at the same time, where the new transaction object is the object with which the user has made the first transaction within the past three days;

[0035] Step S22: When the trading environment meets only two of the three conditions described in step S21, and does not simultaneously meet any of the following conditions: the amount of a single financial transaction exceeds RMB 10,000, or the historical transaction frequency is higher than once an hour, the trading environment is evaluated as a "medium-risk environment";

[0036] Step S23: When the trading environment meets one or none of the three conditions described in step S21, or when the trading environment meets only two of the three conditions described in step S21 but touches any of the following situations at the same time - the amount of a single financial transaction exceeds RMB 10,000, or the historical transaction frequency is higher than once an hour, then the trading environment is evaluated as a "high-risk environment".

[0037] According to the above technical solution, the method for performing secondary verification on the current transaction in step S4 is:

[0038] Step S41: Collect and continuously track the sliding track length values ​​l1, l2, ..., l2 of the user's gesture when operating the mobile device during the financial transaction on the operating screen. n ;

[0039] Step S42: Collect the operation interval time between the previous and next operation actions of the user when operating the mobile device during the financial transaction, and perform timing to obtain the operation interval time values ​​t1, t2, ..., t m ;

[0040] Step S43: Collect the touch pressure distribution area of ​​the user's gesture on the operation screen when operating the mobile device during the financial transaction, and mark the p corresponding pixels x1, x2, ..., x3 of the mobile device touch screen with the highest number of touches during the period. p , we get the set X = {x1, x2, …, x p};

[0041] Step S44: Calculate the average screen sliding track length using the formula Average operation interval value

[0042] Step S45: Find the set X = {x1, x2, ..., x p} and the set X b ={x b1 ,x b2 ,…,x bp}, and obtain the number of intersections q; where X b ={x b1 ,x b2 ,…,x bp} is the p mobile device touch screen pixel points x with the highest touch times corresponding to the standard operation data of the user operating the mobile device collected and stored in the user data packaging moduleb1 、x b2 , …, x bp ;

[0043] Step S46: When When the dynamic factor verification module responds, it determines that the secondary verification is successful, otherwise it determines that the secondary verification fails, where l b ,t b They are respectively the standard sliding track length value and the standard operation interval time value corresponding to the standard operation data of the user operating the mobile device collected and stored in the user data packaging module, and α, β, and γ are the control parameters of the sliding track length value, the operation interval time value and the touch pressure distribution area ratio value, respectively, and are all constants greater than 0.

[0044] According to the above technical solution, the method of performing three verifications on the current transaction in step S5 is:

[0045] Step S51: In response to the instruction signal of the emotion verification module, the camera calling unit is started to call the front camera module of the mobile device to collect the user's facial image;

[0046] Step S52: using the eyebrow recognition module to obtain an eyebrow image based on the features of the eyebrow on the face;

[0047] Step S53: fitting the user's eyebrow contour in the enlarged image, defining the eyebrow area, and respectively marking the upper and lower eyebrow points of the eyebrows on both sides, namely, upper eyebrow point A, upper eyebrow point B, lower eyebrow point C, and lower eyebrow point D;

[0048] Step S54: establish a plane rectangular coordinate system with the nose tip as the origin, the nose midline as the Y axis, and the straight line of the nose midline rotated 90 degrees at the nose tip as the X axis, and take the distance from the nose tip to the upper lip vertex on the Y axis as the unit distance 1, calibrate the corresponding coordinate system of the facial images of different distances collected during the current transaction, and then respectively obtain the coordinate positions of the upper brow point A, the upper brow point B, the lower brow point C, and the lower brow point D in the current user's facial image;

[0049] Step S55: Finally, the coordinate positions of the upper edge point A, the upper edge point B, the lower edge point C, and the lower edge point D of the brow are compared with the standard data collected and extracted by the user facial data storage module;

[0050] Step S56: When the error distance exceeding the system preset reaches more than u groups of data, the emotion monitoring verification module responds and determines that the three verifications are successful, otherwise it determines that the three verifications are failed.

[0051] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention significantly improves the anti-fraud ability of users when operating mobile devices by combining transaction risk assessment with a multi-factor dynamic password verification mechanism. At the same time, the verification method can be flexibly adjusted according to the risk level of the transaction environment, from a single dynamic password verification, to a secondary verification combined with user behavior characteristics, and then to a tertiary verification of emotional characteristics, thus building a comprehensive and intelligent security line. This not only effectively resists the infringement of telecommunications fraud, especially complex fraud methods such as Ponzi schemes, but also ensures that payment efficiency is not affected in a low-risk environment, providing a more solid guarantee for the safety of user funds. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0053] Figure 1 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in 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] See also Figure 1 The present invention provides a technical solution: a dynamic password generation system for a mobile device, including a transaction risk assessment module, a user data packaging module, a dynamic factor verification module, an emotion monitoring verification module and an early warning and blocking service module, wherein each module is connected by a signal; wherein,

[0056] The transaction risk assessment module is applicable to assessing the current transaction environment risk when the device enters into a financial transaction;

[0057] The user data packaging module is used to collect the associated data of users using mobile devices and package and upload it to the blockchain service network;

[0058] The dynamic factor verification module is used to respond to the evaluation results of the transaction risk assessment module and add a dynamic factor verification mechanism based on user behavior;

[0059] The emotion monitoring verification module is used to respond to the evaluation results of the transaction risk assessment module and further add a user emotion factor verification mechanism based on the dynamic factor verification mechanism of user behavior;

[0060] The early warning and blocking service module is used to issue early warnings to financial transaction programs and block suspicious transactions based on the verification results of the multi-factor dynamic password mechanism; among them, the early warning methods include pop-up reminders, SMS notifications, etc.

[0061] The transaction risk assessment module includes a transaction amount collection module, a transaction frequency collection module and a transaction object collection module; among them,

[0062] The transaction amount collection module is used to collect the amount of a single transaction during a financial transaction;

[0063] The transaction frequency collection module is used to collect and monitor the user's historical financial transaction frequency based on the financial transaction period;

[0064] The transaction object collection module is used to collect transaction objects during financial transactions.

[0065] The user data packaging module includes a user operation data storage module and a user face data storage module; wherein,

[0066] The user operation data storage module is used to collect and record the standard operation data of the user's operation of the mobile device; its collection method includes but is not limited to executing the operation steps according to a set of mobile device operation procedures preset by the system during the initial registration of the dynamic password generation system, during which the system calls the hardware device of the mobile device to complete the recording and storage of the user operation data, wherein the collected operation data includes the user's sliding trajectory, touch pressure distribution and average operation interval time;

[0067] The user facial data storage module is used to collect and record the facial data of the user during the operation of the mobile device; its collection method also includes but is not limited to entering the user's facial data according to the system preset during the initial registration of the dynamic password generation system.

[0068] The dynamic factor verification module includes a sliding trajectory tracking module, an operation timing module and a touch sensing module; among which,

[0069] The sliding track tracking module is used to collect and continuously track the sliding track of the user's gestures on the operating screen when operating the mobile device during financial transactions;

[0070] The operation timing module is used to collect the operation interval time between the previous and next operation actions of the user operating the mobile device during the financial transaction, and to time it;

[0071] The touch sensing module is used to collect the touch pressure distribution area of ​​the user's gesture on the operating screen when the user operates the mobile device during financial transactions; by adding a dynamic factor verification mechanism based on user behavior on the basis of the original dynamic password, it can rely not only on time and keys during financial transactions, but also on the dynamic characteristics of the user's behavior, greatly improving the ability to resist man-in-the-middle attacks.

[0072] The emotion monitoring verification module includes a camera call unit, a brow recognition module and a contour fitting module. The camera call unit is connected to the brow recognition module by signals, and the brow recognition module is connected to the contour fitting module by signals.

[0073] The camera calling unit is used to call the camera permission of the mobile device during the financial transaction based on the assessment result of the transaction risk assessment module;

[0074] The eyebrow recognition module is used to monitor the picture in real time according to the camera calling unit, and track the user's eyebrow information in the monitored picture based on the preset eyebrow features;

[0075] The contour fitting module is used to fit the user's eyebrow contour and output the eyebrow contour change data during the monitoring period; by further adding an emotion monitoring and verification mechanism for users during financial transactions, the user's facial emotion changes can be analyzed and verified again on the basis of dynamic passwords and dynamic factor verifications of user behavior, thereby effectively monitoring the situation in which users, after being deeply involved in financial scams, are reluctant to give up their initial investments and fall into deep doubt and struggle, showing anxiety and fear; and a monitoring and verification mechanism is implemented for the unconscious facial muscle changes such as "frown", "raised eyebrows" and "twisted eyebrows" that are common when users are anxious and fearful, providing all-round and intelligent security protection to effectively resist the infringement of telecommunications fraud such as Ponzi schemes.

[0076] The operation method of the dynamic password generation system includes the following steps:

[0077] Step S1: in response to monitoring that a mobile device enters a transaction program, a transaction risk assessment module is started to collect the current financial transaction amount, the transaction frequency within the period monitored by the system, and the current transaction object data;

[0078] Step S2: Then, based on the collected data in step S1, the current transaction environment risk is evaluated, and the evaluation results are divided into low-risk environment, medium-risk environment and high-risk environment;

[0079] Step S3: When the evaluation result is a low-risk environment, the system outputs a dynamic password in the financial transaction link to perform security verification of the transaction environment;

[0080] Step S4: When the assessment result is a medium-risk environment, the system first outputs a dynamic password in the financial transaction link to perform security verification of the transaction environment. If the dynamic password verification is successful, the dynamic factor verification module is started to perform a secondary verification on the current transaction;

[0081] Step S5: When the evaluation result is a high-risk environment, the system first outputs a dynamic password in the financial transaction link to perform security verification of the transaction environment. If the dynamic password verification is successful, the dynamic factor verification module is started to perform a second verification on the current transaction. If the second verification is successful, the emotion monitoring verification module is started again to perform a third verification on the current transaction.

[0082] Step S6: Get the final verification result of steps S3-S5. When the security verification result of any step is "verification failure", it is judged as a "suspicious transaction", and the current financial transaction program is immediately warned and blocked. Through the above steps, the transaction environment can be risk assessed during the transaction, and a multi-mode transaction verification mechanism can be generated using the risk assessment results. This not only improves the user's anti-fraud ability when using mobile devices, but also reduces the impact of the multi-factor dynamic password mechanism on payment efficiency in a low transaction risk environment.

[0083] Step S2 further comprises:

[0084] Step S21: When the single financial transaction amount is less than RMB 1,000, the historical transaction frequency is less than once a day, and the transaction object is not a "new transaction object", the environment is evaluated as a "low-risk environment" when the above three points are met at the same time, where the new transaction object is the object of the user's first transaction in the past three days;

[0085] Step S22: When the trading environment meets only two of the three conditions in step S21, and does not simultaneously meet any of the following conditions: the amount of a single financial transaction exceeds RMB 10,000, or the historical transaction frequency is higher than once an hour, the trading environment is evaluated as a "medium-risk environment";

[0086] Step S23: When the transaction environment meets one or none of the three conditions in step S21, or when the transaction environment meets only two of the three conditions in step S21 but touches any of the following situations at the same time - the amount of a single financial transaction exceeds 10,000 yuan, or the historical transaction frequency is higher than once an hour, the transaction environment is evaluated as a "high-risk environment"; when a user encounters a carefully designed telecommunications fraud, especially a Ponzi scheme, during the operation of a mobile device, the transaction environment is mainly manifested in multiple transfers to new transaction objects in a short period of time, and the transaction amounts involved are also increasing. If the amount of a single transaction is larger, the one-time loss faced by the user is more serious. Then, through the above steps, a comprehensive analysis and evaluation is conducted on the amount of a single transaction, the historical transaction frequency and the transaction object, and they are divided into corresponding risk levels, so that the characteristics of telecommunications fraud can be effectively targeted. This process not only enhances the accuracy of the system in identifying telecommunications fraud characteristics, but also lays a solid foundation for the subsequent introduction of a multi-factor dynamic password mechanism, ensuring that security measures can be flexibly adjusted with the dynamic changes in risk levels, and providing a more solid guarantee for the security of user funds.

[0087] The method for performing secondary verification on the current transaction in step S4 is:

[0088] Step S41: Collect and continuously track the sliding track length values ​​l1, l2, ..., l2 of the user's gesture when operating the mobile device during the financial transaction on the operating screen. n ;

[0089] Step S42: Collect the operation interval time between the previous and next operation actions of the user when operating the mobile device during the financial transaction, and perform timing to obtain the operation interval time values ​​t1, t2, ..., t m ;

[0090] Step S43: Collect the touch pressure distribution area of ​​the user's gesture on the operation screen when operating the mobile device during the financial transaction, and mark the p corresponding pixels x1, x2, ..., x3 of the mobile device touch screen with the highest number of touches during the period. p , we get the set X = {x1, x2, …, x p};

[0091] Step S44: Calculate the average screen sliding track length using the formula Average operation interval value

[0092] Step S45: Find the set X = {x1, x2, ..., x p} and the set X b ={x b1 ,x b2 ,…,x bp}, and obtain the number of intersections q; where X b ={x b1 ,x b2 ,…,x bp} is the p mobile device touch screen pixel points x with the highest touch times corresponding to the standard operation data of the user operating the mobile device collected and stored in the user data packaging module b1 、x b2 , …, x bp ;

[0093] Step S46: When When the dynamic factor verification module responds, it determines that the secondary verification is successful, otherwise it determines that the secondary verification fails, where l b ,t b are the standard sliding track length value and the standard operation interval time value corresponding to the standard operation data of the user operating the mobile device stored in the user data packaging module, α, β, and γ are the control parameters of the sliding track length value, the operation interval time value, and the touch pressure distribution area ratio value, respectively, and are all constants greater than 0; where The smaller the corresponding value of pq, the smaller the calculated value of the formula, that is, when the average screen sliding track length value, the average operation interval time value, and the touch pressure distribution area on the operation screen are all closer to the standard operation data collected during the initial registration of the dynamic password generation system, the secondary verification mechanism of the final dynamic factor verification module is more likely to succeed; through the above steps, a dynamic factor verification based on user behavior can be added on the basis of the original dynamic password, and the verification of multiple operation behavior results must be comprehensively met before the secondary verification mechanism can be passed, thereby effectively preventing users from encountering financial transactions under external influences such as "remote guidance" and "face-to-face guidance" during telecommunications fraud. Only when users perform coherent mobile device operations according to their operating habits can they meet the verification, which greatly improves transaction security.

[0094] The method for performing three verifications on the current transaction in step S5 is:

[0095] Step S51: In response to the instruction signal of the emotion verification module, the camera calling unit is started to call the front camera module of the mobile device to collect the user's facial image;

[0096] Step S52: using the eyebrow recognition module to obtain an eyebrow image based on the features of the eyebrow on the face;

[0097] Step S53: fitting the user's eyebrow contour in the enlarged image, defining the eyebrow area, and respectively marking the upper and lower eyebrow points of the eyebrows on both sides, namely, upper eyebrow point A, upper eyebrow point B, lower eyebrow point C, and lower eyebrow point D;

[0098] Step S54: establish a plane rectangular coordinate system with the nose tip as the origin, the nose midline as the Y axis, and the straight line of the nose midline rotated 90 degrees at the nose tip as the X axis, and take the distance from the nose tip to the upper lip vertex on the Y axis as the unit distance 1, calibrate the corresponding coordinate system of the facial images of different distances collected during the current transaction, and then respectively obtain the coordinate positions of the upper brow point A, the upper brow point B, the lower brow point C, and the lower brow point D in the current user's facial image;

[0099] Step S55: Finally, the coordinate positions of the upper edge point A, the upper edge point B, the lower edge point C, and the lower edge point D of the brow are compared with the standard data collected and extracted by the user's facial data storage module;

[0100] Step S56: When the error distance exceeds the system preset error distance and reaches more than u groups of data, the emotion monitoring verification module responds and judges that the three verifications are successful, otherwise it judges that the three verifications fail; when the transaction environment is evaluated as a "high-risk environment", it means that the user may be involved in a large amount of money, a high transaction frequency, and a low credibility transaction object during the current financial transaction, especially when the user is deeply involved in a Ponzi scheme, the user loses the ability to think independently, and there will be fear and anxiety due to the fear of missing investment opportunities or facing financial losses. In this emotional state, facial features such as frowning, raising eyebrows, and twisting eyebrows generally appear inadvertently. Therefore, for high-risk transaction environments, the system not only performs dual verification of the user's dynamic password and dynamic factors based on user behavior, but also further analyzes and judges the user's emotional characteristics at this moment. If the analysis shows that there are potential tension, anxiety, fear and other emotions, the verification fails, and the current financial transaction program is warned and blocked in time, which ultimately aims to provide users with all-round and intelligent security protection when operating mobile devices, and effectively resist the infringement of telecommunications fraud such as Ponzi schemes.

[0101] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0102] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A dynamic password generation system for a mobile device, characterized in that: The dynamic password generation system includes a transaction risk assessment module, a user data packaging module, a dynamic factor verification module, an emotion monitoring verification module and an early warning and blocking service module, and each module is connected through a signal; wherein, The transaction risk assessment module is applicable to assess the current transaction environment risk when the device enters into a financial transaction period; The user data packaging module is used to collect the associated data of the user using the mobile device and package it and upload it to the blockchain service network; The dynamic factor verification module is used to add a dynamic factor verification mechanism based on user behavior in response to the evaluation result of the transaction risk evaluation module; The emotion monitoring verification module is used to respond to the evaluation result of the transaction risk evaluation module and further add a user emotion factor verification mechanism based on the dynamic factor verification mechanism of user behavior; The early warning and blocking service module is used to warn financial transaction programs and block suspicious transactions based on the verification results of the multi-factor dynamic password mechanism.

2. The dynamic password generation system for mobile devices according to claim 1, characterized in that: The transaction risk assessment module includes a transaction amount collection module, a transaction frequency collection module and a transaction object collection module; wherein, The transaction amount collection module is used to collect the amount of a single transaction during a financial transaction; The transaction frequency collection module is used to collect and monitor the user's historical financial transaction frequency based on the financial transaction period; The transaction object collection module is used to collect transaction objects during financial transactions.

3. The dynamic password generation system for mobile devices according to claim 1, characterized in that: The user data packaging module includes a user operation data storage module and a user face data storage module; wherein, The user operation data storage module is used to collect and record the standard operation data of the user operating the mobile device; The user facial data storage module is used to collect facial data of the user during operation of the mobile device and record and store it.

4. The dynamic password generation system for mobile devices according to claim 3, characterized in that: The dynamic factor verification module includes a sliding trajectory tracking module, an operation timing module and a touch sensing module; wherein, The sliding track tracking module is used to collect and continuously track the sliding track of the user's gestures on the operating screen when operating the mobile device during the financial transaction; The operation timing module is adapted to collect and time the operation interval between the previous and next operation actions of the user operating the mobile device during the financial transaction; The touch sensing module is used to collect the touch pressure distribution area of ​​the user's gesture on the operating screen when the user operates the mobile device during a financial transaction.

5. The dynamic password generation system for mobile devices according to claim 3, characterized in that: The emotion monitoring verification module includes a camera call unit, a brow recognition module and a contour fitting module, wherein the camera call unit is connected to the brow recognition module by signal, and the brow recognition module is connected to the contour fitting module by signal; wherein, The camera calling unit is used to call the camera permission of the mobile device during the financial transaction based on the evaluation result of the transaction risk evaluation module; The eyebrow recognition module is used to monitor the picture in real time according to the camera calling unit, and track the user's eyebrow information in the monitored picture based on the preset eyebrow features; The contour fitting module is used to fit the user's eyebrow contour and output eyebrow contour change data during the monitoring period.

6. A dynamic password generation system for a mobile device as claimed in any one of claims 1 to 5, characterized in that: The operation method of the dynamic password generation system comprises the following steps: Step S1: in response to monitoring that a mobile device enters a transaction program, a transaction risk assessment module is started to collect the current financial transaction amount, the transaction frequency within the period monitored by the system, and the current transaction object data; Step S2: Then, based on the collected data in step S1, the risk of the current transaction environment is evaluated, and the evaluation results are divided into a low-risk environment, a medium-risk environment, and a high-risk environment; Step S3: When the evaluation result is a low-risk environment, the system outputs a dynamic password in the financial transaction link to perform security verification of the transaction environment; Step S4: When the assessment result is a medium-risk environment, the system first outputs a dynamic password in the financial transaction link to perform security verification of the transaction environment. If the dynamic password verification is successful, the dynamic factor verification module is started to perform a secondary verification on the current transaction; Step S5: When the evaluation result is a high-risk environment, the system first outputs a dynamic password in the financial transaction link to perform security verification of the transaction environment. If the dynamic password verification is successful, the dynamic factor verification module is started to perform a second verification on the current transaction. If the second verification is successful, the emotion monitoring verification module is started again to perform a third verification on the current transaction. Step S6: Obtain the final verification results of steps S3-S5. When the security verification result of any step is "verification failure", it is judged as a "suspicious transaction", and the current financial transaction program is immediately warned and blocked.

7. The dynamic password generation system for mobile devices according to claim 6, characterized in that: The step S2 further comprises: Step S21: When the single financial transaction amount is less than RMB 1,000, the historical transaction frequency is less than once a day, and the transaction object is not a "new transaction object", the environment is evaluated as a "low-risk environment" when the above three points are met at the same time, where the new transaction object is the object with which the user has made the first transaction within the past three days; Step S22: When the trading environment meets only two of the three conditions described in step S21, and does not meet any of the following conditions at the same time: the single financial transaction amount exceeds RMB 10,000, or the historical transaction frequency is higher than once an hour, the trading environment is evaluated as a "medium risk environment"; Step S23: When the trading environment meets one or none of the three conditions described in step S21, or when the trading environment meets only two of the three conditions described in step S21 but touches any of the following situations at the same time - the amount of a single financial transaction exceeds RMB 10,000, or the historical transaction frequency is higher than once an hour, then the trading environment is evaluated as a "high-risk environment".

8. The dynamic password generation system for mobile devices according to claim 6, characterized in that: The method for performing secondary verification on the current transaction in step S4 is: Step S41: Collect and continuously track the sliding track length values ​​l1, l2, ..., l2 of the user's gesture when operating the mobile device during the financial transaction on the operating screen. n ; Step S42: Collect the operation interval time between the previous and next operation actions of the user when operating the mobile device during the financial transaction, and perform timing to obtain the operation interval time values ​​t1, t2, ..., t m ; Step S43: Collect the touch pressure distribution area of ​​the gesture on the operation screen when the user operates the mobile device during the financial transaction, and mark the p corresponding pixels x1, x2, ..., x3 of the mobile device touch screen with the highest number of touches during the period. p , we get the set X = {x1, x2, ..., x p }; Step S44: Calculate the average screen sliding track length using the formula Average operation interval value Step S45: Find the set X = {x1, x2, ..., x p } and the set X b ={x b1 , x b2 , ..., x bp }, and obtain the number of intersections q; where X b ={x b1 , x b2 , ..., x bp } is the p mobile device touch screen pixel points x with the highest touch times corresponding to the standard operation data of the user operating the mobile device collected and stored in the user data packaging module b1 、x b2 , ..., x bp ; Step S46: When When the dynamic factor verification module responds, it determines that the secondary verification is successful, otherwise it determines that the secondary verification fails, where l b ,t b They are respectively the standard sliding track length value and the standard operation interval time value corresponding to the standard operation data of the user operating the mobile device collected and stored in the user data packaging module, and α, β, and γ are the control parameters of the sliding track length value, the operation interval time value and the touch pressure distribution area ratio value, respectively, and are all constants greater than 0.

9. The dynamic password generation system for mobile devices according to claim 6, characterized in that: The method for performing three verifications on the current transaction in step S5 is: Step S51: In response to the instruction signal of the emotion verification module, the camera calling unit is started to call the front camera module of the mobile device to collect the user's facial image; Step S52: using the eyebrow recognition module to obtain an eyebrow image based on the features of the eyebrow on the face; Step S53: fitting the user's eyebrow contour in the enlarged image, defining the eyebrow area, and respectively marking the upper and lower eyebrow points of the eyebrows on both sides, namely, upper eyebrow point A, upper eyebrow point B, lower eyebrow point C, and lower eyebrow point D; Step S54: establish a plane rectangular coordinate system with the nose tip as the origin, the nose midline as the Y axis, and the straight line of the nose midline rotated 90 degrees at the nose tip as the X axis, and take the distance from the nose tip to the upper lip vertex on the Y axis as the unit distance 1, calibrate the corresponding coordinate system of the facial images of different distances collected during the current transaction, and then respectively obtain the coordinate positions of the upper brow point A, the upper brow point B, the lower brow point C, and the lower brow point D in the current user's facial image; Step S55: Finally, the coordinate positions of the upper edge point A, the upper edge point B, the lower edge point C, and the lower edge point D of the brow are compared with the standard data collected and extracted by the user facial data storage module; Step S56: When the error distance exceeding the system preset reaches more than u groups of data, the emotion monitoring verification module responds and determines that the three verifications are successful, otherwise it determines that the three verifications are failed.

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