A method and system for intelligently generating random graphic connection sequences

Abstract

The present application relates to a method and system for intelligently generating a random graphic connection sequence, the method comprising generating a plurality of random graphics and a plurality of connection sequences, using the generated plurality of random graphics and a plurality of connection sequences to generate a verification interface and adding interference graphics and counting the number of verification errors in the verification interface, when the number of verification errors is greater than or equal to a set number, randomly generating round(L*(1+q),0) random graphics and regenerating the connection sequence, q is less than 1, and the q value is positively correlated with the number of verification errors. The method and system for intelligently generating a random graphic connection sequence disclosed in the present application gradually increases the difficulty of correct clicking by adding graphic interference and changing the connection sequence, so as to improve the security of graphic authentication.

Description

Technical Field

[0001] The present application relates to the field of authentication security technology, and in particular to a method and system for intelligently generating a random graphic connection sequence. Background Art

[0002] The advantage of graphic authentication is that the graphic verification code requires human visual recognition to be correctly entered, which can effectively prevent automated tools (such as crawlers or scripts) from performing malicious operations. Application scenarios include:

[0003] Registration / snap-up / inquiry: During high-traffic events, such as new product launches, promotions, or important data inquiries, graph authentication can help filter out requests from robots and automated tools. Business operation protection: Graph authentication can be used to protect customers' business operations from malicious crawlers and automated scripts, ensuring that real users can operate smoothly.

[0004] Human-machine identification: In scenarios where it is necessary to distinguish between human users and automated programs, graphic authentication can help clarify the boundaries of human-machine requests and resist abnormal machine requests. Preventing false traffic: Graphic authentication can reduce the impact of false traffic on corporate operations and help companies focus on real user traffic and services.

[0005] Of course, graphic authentication also has certain limitations. This is mainly because with the development of artificial intelligence and the application of automatic image recognition technology, graphic authentication has been able to be machine-operated. Some defense measures, such as increasing image noise and distorting text, have also begun to be recognizable with the development of training models. Summary of the invention

[0006] The present application provides a method and system for intelligently generating a random graphic connection sequence, which gradually increases the difficulty of correct clicking by adding graphic interference and changing the connection sequence, so as to improve the security of graphic authentication.

[0007] The above-mentioned purpose of the present application is achieved through the following technical solutions:

[0008] In a first aspect, the present application provides a method for intelligently generating a random graphic connection sequence, comprising:

[0009] Generate multiple random graphics and multiple connection sequences;

[0010] Generate a verification interface using the generated multiple random graphics and multiple connection sequences and add interference graphics to the verification interface;

[0011] Count the number of verification errors. When the number of verification errors is greater than or equal to the set number, randomly generate round(L*(1+q),0) random graphics and regenerate the connection sequence, where q is less than 1;

[0012] Among them, the q value is positively correlated with the number of verification errors.

[0013] In a possible implementation manner of the first aspect, an interference source is further added to at least one random pattern, where the random pattern is located inside the interference source.

[0014] In a possible implementation manner of the first aspect, adding an interference source to the random pattern includes:

[0015] Determine the edge contour of the random figure, the edge contour includes an inner edge contour and an outer edge contour;

[0016] Determine the interference range according to the inner edge contour and the outer edge contour;

[0017] Determine the color of the random pattern and establish reference lines on the inner edge contour and / or the outer edge contour respectively;

[0018] The interference range is filled in the direction of the baseline according to the color of the random pattern, and the filling methods include color enhancement and color attenuation.

[0019] In a possible implementation manner of the first aspect, the method further includes establishing reference points on the reference line, and at least two reference points on the reference line have different distances from adjacent inner edge contours or outer edge contours.

[0020] In a possible implementation manner of the first aspect, the contour of the interference source is different from the inner edge contour and / or the outer edge contour.

[0021] In a possible implementation manner of the first aspect, the method further includes:

[0022] Segmenting the baseline into multiple sequentially connected baseline segments;

[0023] Determine the color difference between the starting point and the end point of the baseline;

[0024] A color enhancement coefficient or a color attenuation coefficient is assigned to each reference line segment according to the color difference, so that the color enhancement or color attenuation on the reference line is smoothly transitioned.

[0025] In a possible implementation manner of the first aspect, the method further includes inserting a profiling pattern on the random pattern, wherein the profiling pattern includes a plurality of profiling pattern areas;

[0026] There are contour pattern areas at the intersection positions on the random figures;

[0027] The distance between any two contour pattern areas is less than or equal to the allowed distance.

[0028] In a second aspect, the present application provides a device for intelligently generating a random graphic connection sequence, comprising:

[0029] A first content generation unit, used to generate a plurality of random graphics and a plurality of connection sequences;

[0030] A second content generating unit, configured to generate a verification interface using the generated multiple random graphics and multiple connection sequences and to add interference graphics to the verification interface;

[0031] The adjustment unit is used to count the number of verification errors. When the number of verification errors is greater than or equal to the set number, round(L*(1+q),0) random graphics are randomly generated and the connection sequence is regenerated, where q is less than 1;

[0032] Among them, the q value is positively correlated with the number of verification errors.

[0033] In a third aspect, the present application provides a system for intelligently generating a random graphic connection sequence, the system comprising:

[0034] one or more memories for storing instructions; and

[0035] One or more processors, used to call and run the instructions from the memory to execute the method as described in the first aspect and any possible implementation of the first aspect.

[0036] In a fourth aspect, the present application provides a computer-readable storage medium, the computer-readable storage medium comprising:

[0037] Program, when the program is executed by a processor, the method described in the first aspect and any possible implementation of the first aspect is executed.

[0038] In a fifth aspect, the present application provides a computer program product, comprising program instructions. When the program instructions are executed by a computing device, the method described in the first aspect and any possible implementation of the first aspect is executed.

[0039] In a sixth aspect, the present application provides a chip system, which includes a processor for implementing the functions involved in the above aspects, for example, generating, receiving, sending, or processing the data and / or information involved in the above methods.

[0040] The chip system may be composed of chips, or may include chips and other discrete devices.

[0041] In a possible design, the chip system also includes a memory, which is used to store necessary program instructions and data. The processor and the memory can be decoupled and respectively set on different devices, connected by wired or wireless means, or the processor and the memory can also be coupled on the same device. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a schematic diagram of the steps of a method for intelligently generating a random graphic connection sequence provided by the present application.

[0043] Figure 2 It is a schematic diagram of a verification interface provided by this application.

[0044] Figure 3 This is a schematic diagram of a verification interface provided by the present application for the presence of interference sources.

[0045] Figure 4 This is a schematic diagram of the existence of overlapping areas between interference sources on a verification interface provided by the present application.

[0046] Figure 5 It is a schematic diagram for establishing a baseline provided by this application.

[0047] Figure 6 This is a schematic diagram of inserting a profiling pattern into a random pattern provided by the present application. DETAILED DESCRIPTION

[0048] The technical solution in this application is further described in detail below in conjunction with the accompanying drawings.

[0049] This application discloses a method for intelligently generating a random graphic connection sequence. Figure 1 In some examples, the method disclosed in the present application for intelligently generating a random graphic connection sequence includes the following steps:

[0050] S101, generating a plurality of random graphics and a plurality of connection sequences;

[0051] S102, using the generated multiple random graphics and multiple connection sequences to generate a verification interface and adding interference graphics to the verification interface;

[0052] S103, counting the number of verification errors, when the number of verification errors is greater than or equal to the set number, randomly generating round(L*(1+q),0) random graphics and regenerating the connection sequence, q is less than 1;

[0053] Among them, the q value is positively correlated with the number of verification errors.

[0054] Specifically, in step S101, a plurality of random graphics and a plurality of connection sequences are firstly generated. The random graphics have two functions: one is to generate a verification interface in conjunction with the connection sequence, and the other is to be used as an interference graphic.

[0055] In some possible implementations, the method of generating random patterns is to obtain true random numbers, such as the operating parameters of electrical components on the device or the environmental noise, and then input them into a random number sequence generator. At this time, a true random number sequence will be obtained, and then a fixed number of bits on the true random number sequence is specified to represent the number of edges of the random pattern, the number of random patterns, the number of bits of the connection sequence, and the number of interference patterns.

[0056] After determining the number of digits of the connection sequence, the number of random graphics participating in the selection can be determined. At this time, all the arrangements of the random graphics are listed to obtain the connection sequence, and then one is selected from all the obtained connection sequences for use.

[0057] Of course, when selecting one from all connection sequences, you can also use a true random number sequence generated by a random number generator to make the selection.

[0058] In step S102, the generated multiple random graphics and multiple connection sequences are used to generate a verification interface and add interference graphics to the verification interface, such as Figure 2 As shown, Figure 2 The solid line figures in the figure are three randomly selected figures, and the dotted line figures are interference figures, two in number.

[0059] Of course, at this time, the selected random pattern and the interference pattern may have the same pattern. At this time, it is necessary to select one or several random numbers in the true random number sequence according to the rules in the true random number sequence as the length value of the top of the pattern.

[0060] Then in step S103, the number of verification errors is counted. When the number of verification errors is greater than or equal to the set number, round(L*(1+q),0) random graphics are randomly generated and the connection sequence is regenerated, q is less than 1, and the q value is positively correlated with the number of verification errors.

[0061] For round(L*(1+q),0), the specific explanation is as follows:

[0062] round(L*(1+q),0) is a mathematical expression that uses Python’s round() function.

[0063] What this expression does is calculate the result of multiplying L by (1+q) and rounding the result to the nearest integer. Here is a detailed explanation of the expression:

[0064] L: This is a variable that represents a value, which can be any real number (integer or decimal).

[0065] q: This is another variable that also represents a numerical value. It can be any real number that is added to 1 and then multiplied by L. This variable is often used to represent growth rates, proportional changes, etc.

[0066] L*(1+q): This expression first calculates 1+q and then multiplies the result by L. This is usually used to calculate the value of L after increasing it by a factor of q.

[0067] round(..., 0) : The round() function is used to round its argument to a specified precision.

[0068] In this expression, the second argument is 0, which means the result will be rounded to the nearest integer. If the second argument is not specified (or None), the default is to round to the nearest integer.

[0069] That is, as the number of verification errors increases, the number of random graphics involved in the selection will increase, and the connection sequence will be regenerated at the same time. This method can avoid brute force cracking.

[0070] It should be noted that the brute force cracking method is to make all possible attempts in a fixed parameter environment. This application breaks the fixed parameter environment by counting the number of verification errors, making it impossible for the brute force cracking method to try out all possibilities.

[0071] In some examples, the method further includes adding an interference source to at least one random pattern. Figure 3 As shown, Figure 3 The thick solid line in the figure is the interference source, and the random pattern is located inside the interference source. The purpose of the interference source is to prevent the random pattern from being recognized by the machine.

[0072] The specific function of the interference source is to increase the difficulty of the random pattern being recognized by the machine, but it does not affect the difficulty of the random pattern being recognized by real people.

[0073] The purpose of adding an interference source to at least one random graphic is to avoid the random graphic being processed in the same way, because one way of machine recognition is to process the verification interface as a whole, but in the technical solution of the present application, the way of processing the verification interface as a whole will cause information loss.

[0074] In some possible implementations, there is an overlapping area between at least two adjacent interference sources.

[0075] The specific method of adding interference sources to random graphics is as follows:

[0076] S201, determining an edge contour of a random graphic, where the edge contour includes an inner edge contour and an outer edge contour;

[0077] S202, determining an interference range according to the inner edge contour and the outer edge contour;

[0078] S203, determining the color of the random pattern and establishing a reference line on the inner edge contour and / or the outer edge contour respectively;

[0079] S204, filling the interference range in the direction of the baseline according to the color of the random pattern, and the filling method includes color enhancement and color attenuation.

[0080] In step S201 to step S204, the edge contour of the random pattern is first determined. The edge contour includes an inner edge contour and an outer edge contour. The number of the inner edge contours may be zero or more, and the number of the outer edge contour is one.

[0081] Then, the interference range is determined according to the inner edge contour and the outer edge contour. The specific method is to determine the entire range within the area surrounded by the inner edge contour as the interference range, and determine the specified range outside the outer edge contour as the interference range. The specific rules are as follows:

[0082] The contour of the interference source is different from the inner edge contour and / or the outer edge contour, Figure 3 As shown;

[0083] There is an overlapping area between at least two adjacent interference sources. Figure 4 shown.

[0084] Then determine the color of the random pattern and establish a reference line on the inner edge contour and / or the outer edge contour respectively. Figure 5 As shown, the interference range is then filled in the direction of the baseline according to the color of the random pattern, and the filling methods include color enhancement and color attenuation.

[0085] The specific selection method of color enhancement or color attenuation is determined according to the color difference. If the color depth in the direction of the baseline deepens, the color enhancement filling method is selected, otherwise the color attenuation filling method is selected.

[0086] The specific method of color filling is transition, that is, firstly a fixed width is selected in the direction of the baseline to fill and complete the transition, and the unfilled area between adjacent baselines is processed using the difference transition method.

[0087] In some examples, the method further includes establishing reference points on the reference line, and at least two reference points on the reference line have different distances from the adjacent inner edge contour or outer edge contour. The reference points are used to simulate the adjacent inner edge contour or outer edge contour. Figure 5 As shown, but the same simulation is not performed, which can reduce the probability of being recognized by the machine.

[0088] It should be understood that one way of machine recognition is through comparison. When the simulated adjacent inner edge contours or outer edge contours are not similar to the inner edge contours or outer edge contours, the difficulty of machine recognition judgment will increase. Even if the results are obtained after recognition, it is possible that an interference range rather than a random pattern is obtained.

[0089] Furthermore, the following steps are added:

[0090] S301, segmenting the baseline into a plurality of sequentially connected baseline segments;

[0091] S302, determining the color difference between the starting point and the end point of the reference line;

[0092] S303, assigning a color enhancement coefficient or a color attenuation coefficient to each reference line segment according to the color difference, so that the color enhancement or color attenuation on the reference line is smoothly transitioned.

[0093] The above method is to segment the baseline and use color enhancement or color attenuation in each segment. This method can further increase the shape complexity of the interference range, because the interference range has multiple shapes at this time, which can further increase the difficulty of machine recognition.

[0094] For some examples, see Figure 6 , including inserting contour patterns on random graphics ( Figure 6 The purpose of the profiling pattern is to reduce the difficulty of identifying a real person. Specifically, the profiling pattern includes multiple profiling pattern areas, and there are profiling pattern areas at the intersection positions on the random pattern. At the same time, the distance between any two profiling pattern areas is required to be less than or equal to the allowed distance.

[0095] Through the profiling pattern, the shape of the random figure can be roughly described rather than accurately described. After receiving the random figure with the profiling pattern, the real person can imagine the complete shape of the random figure, which will combine partial information of the random figure and partial information of the profiling pattern.

[0096] The present application also provides a device for intelligently generating a random graphic connection sequence, comprising:

[0097] A first content generation unit, used to generate a plurality of random graphics and a plurality of connection sequences;

[0098] A second content generating unit, configured to generate a verification interface using the generated multiple random graphics and multiple connection sequences and to add interference graphics to the verification interface;

[0099] The adjustment unit is used to count the number of verification errors. When the number of verification errors is greater than or equal to the set number, round(L*(1+q),0) random graphics are randomly generated and the connection sequence is regenerated, where q is less than 1;

[0100] Among them, the q value is positively correlated with the number of verification errors.

[0101] Furthermore, the method further includes adding an interference source on at least one random pattern, wherein the random pattern is located inside the interference source.

[0102] Furthermore, it also includes:

[0103] A first determining unit is used to determine an edge contour of the random pattern, where the edge contour includes an inner edge contour and an outer edge contour;

[0104] A second determining unit, configured to determine an interference range according to the inner edge contour and the outer edge contour;

[0105] A reference line establishment unit is used to determine the color of the random pattern and to establish reference lines on the inner edge contour and / or the outer edge contour respectively;

[0106] The filling unit is used to fill the interference range in the direction of the baseline according to the color of the random pattern, and the filling methods include color enhancement and color attenuation.

[0107] Furthermore, it also includes establishing reference points on the reference line, and there are at least two reference points on the reference line that have different distances from adjacent inner edge contours or outer edge contours.

[0108] Further, the contour of the interference source is different from the inner edge contour and / or the outer edge contour.

[0109] Furthermore, it also includes:

[0110] A segmentation processing unit, used for segmenting the baseline, dividing the baseline into a plurality of sequentially connected baseline segments;

[0111] A color difference determination unit, used to determine the color difference between the starting point and the end point of the reference line;

[0112] The coefficient adjustment unit is used to assign a color enhancement coefficient or a color attenuation coefficient to each reference line segment according to the color difference, so that the color enhancement or color attenuation on the reference line is smoothly transitioned.

[0113] Further, the method further includes inserting a profiling pattern on the random pattern, wherein the profiling pattern includes a plurality of profiling pattern areas;

[0114] There are contour pattern areas at the intersection positions on the random figures;

[0115] The distance between any two contour pattern areas is less than or equal to the allowed distance.

[0116] In one example, the unit in any of the above devices can be one or more integrated circuits configured to implement the above methods, such as: one or more application specific integrated circuits (ASICs), or, one or more digital signal processors (DSPs), or, one or more field programmable gate arrays (FPGAs), or a combination of at least two of these integrated circuit forms.

[0117] For another example, when the units in the device can be implemented in the form of a processing element scheduling program, the processing element can be a general-purpose processor, such as a central processing unit (CPU) or other processor that can call a program. For another example, these units can be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0118] Various objects such as various messages / information / equipment / network elements / systems / devices / actions / operations / processes / concepts that may appear in this application are named. It can be understood that these specific names do not constitute a limitation on the relevant objects. The names assigned may change with factors such as scenarios, contexts or usage habits. The understanding of the technical meaning of the technical terms in this application should be mainly determined from the functions and technical effects embodied / executed in the technical scheme.

[0119] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0120] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0121] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0122] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0123] It should also be understood that in various embodiments of the present application, the first, second, etc. are only used to indicate that multiple objects are different. For example, the first time window and the second time window are only used to indicate different time windows. They should not have any impact on the time window itself, and the first, second, etc. mentioned above should not impose any limitations on the embodiments of the present application.

[0124] It should also be understood that in the various embodiments of the present application, unless otherwise specified or there is a logical conflict, the terms and / or descriptions between different embodiments are consistent and can be referenced to each other, and the technical features in different embodiments can be combined to form new embodiments according to their internal logical relationships.

[0125] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a computer-readable storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned computer-readable storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0126] The present application also provides a system for intelligently generating a random graphic connection sequence, the system comprising:

[0127] one or more memories for storing instructions; and

[0128] One or more processors are used to call and run the instructions from the memory to execute the method as described above.

[0129] The present application also provides a computer program product, which includes instructions. When the instructions are executed, the terminal device and the network device perform operations of the terminal device and the network device corresponding to the above method.

[0130] The present application also provides a chip system, which includes a processor for implementing the functions involved in the above content, such as generating, receiving, sending, or processing the data and / or information involved in the above method.

[0131] The chip system may be composed of chips, or may include chips and other discrete devices.

[0132] The processor mentioned in any of the above places can be a CPU, a microprocessor, an ASIC, or one or more integrated circuits for executing programs for controlling the above-mentioned feedback information transmission method.

[0133] In a possible design, the chip system also includes a memory, which is used to store necessary program instructions and data. The processor and the memory can be decoupled and respectively set on different devices, connected by wire or wireless means to support the chip system to implement various functions in the above embodiments. Alternatively, the processor and the memory can also be coupled on the same device.

[0134] Optionally, the computer instructions are stored in a memory.

[0135] Optionally, the memory is a storage unit within the chip, such as a register, a cache, etc. The memory can also be a storage unit within the terminal located outside the chip, such as a ROM or other types of static storage devices that can store static information and instructions, RAM, etc.

[0136] It can be understood that the memory in the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories.

[0137] The non-volatile memory may be a ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), or a flash memory.

[0138] The volatile memory may be a RAM, which is used as an external cache. There are many different types of RAM, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct memory bus RAM.

[0139] The embodiments of this specific implementation method are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Therefore, all equivalent changes made based on the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method for intelligently generating a random graphic connection sequence, characterized in that: include: Generate multiple random graphics and multiple connection sequences; Generate a verification interface using the generated multiple random graphics and multiple connection sequences and add interference graphics to the verification interface; Count the number of verification errors. When the number of verification errors is greater than or equal to the set number, randomly generate round(L*(1+q),0) random graphics and regenerate the connection sequence, where q is less than 1; Among them, the q value is positively correlated with the number of verification errors, L is a variable representing a certain value, which is any real number; Also included is adding an interference source to at least one random pattern, the random pattern being located inside the interference source; Adding interference sources to random graphics includes: Determine the edge contour of the random figure, the edge contour includes an inner edge contour and an outer edge contour; Determine the interference range according to the inner edge contour and the outer edge contour; Determine the color of the random pattern and establish reference lines on the inner edge contour and / or the outer edge contour respectively; The interference range is filled in the direction of the baseline according to the color of the random pattern, and the filling methods include color enhancement and color attenuation. Also includes: Segmenting the baseline into multiple sequentially connected baseline segments; Determine the color difference between the starting point and the end point of the baseline; A color enhancement coefficient or a color attenuation coefficient is assigned to each reference line segment according to the color difference, so that the color enhancement or color attenuation on the reference line is smoothly transitioned.

2. The method for intelligently generating a random graphic connection sequence according to claim 1, characterized in that: The method further includes establishing reference points on the reference line, wherein at least two reference points on the reference line have different distances from adjacent inner edge contours or outer edge contours.

3. The method for intelligently generating a random graphic connection sequence according to claim 1, characterized in that: The contour of the interference source is different from the inner edge contour and / or the outer edge contour.

4. The method for intelligently generating a random graphic connection sequence according to claim 3, characterized in that: Also included is inserting a contoured pattern on the random pattern, the contoured pattern comprising a plurality of contoured pattern areas; There are contour pattern areas at the intersection positions on the random figures; The distance between any two contour pattern areas is less than or equal to the allowed distance.

5. A device for intelligently generating a random graphic connection sequence, characterized in that: include: A first content generation unit, used to generate a plurality of random graphics and a plurality of connection sequences; A second content generating unit, configured to generate a verification interface using the generated multiple random graphics and multiple connection sequences and to add interference graphics to the verification interface; The adjustment unit is used to count the number of verification errors. When the number of verification errors is greater than or equal to the set number, round(L*(1+q),0) random graphics are randomly generated and the connection sequence is regenerated, where q is less than 1; Among them, the q value is positively correlated with the number of verification errors, L is a variable representing a certain value, which is any real number; Also included is adding an interference source to at least one random pattern, the random pattern being located inside the interference source; Adding interference sources to random graphics includes: Determine the edge contour of the random figure, the edge contour includes an inner edge contour and an outer edge contour; Determine the interference range according to the inner edge contour and the outer edge contour; Determine the color of the random pattern and establish reference lines on the inner edge contour and / or the outer edge contour respectively; Fill the interference range in the direction of the baseline according to the color of the random pattern, and the filling methods include color enhancement and color attenuation; Also includes: Segmenting the baseline into multiple sequentially connected baseline segments; Determine the color difference between the starting point and the end point of the baseline; A color enhancement coefficient or a color attenuation coefficient is assigned to each reference line segment according to the color difference, so that the color enhancement or color attenuation on the reference line is smoothly transitioned.

6. A system for intelligently generating random graphic connection sequences, characterized in that: The system comprises: one or more memories for storing instructions; and One or more processors, configured to call and execute the instructions from the memory to perform the method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: The computer readable storage medium comprises: The program, when the program is executed by a processor, the method according to any one of claims 1 to 4 is executed.

Images