Password space generation system and method based on user personal information, medium, program product and terminal

Abstract

According to the password space generation system and method based on the user personal information, the medium, the program product and the terminal, the personalized user personal information is analyzed and extracted, and targeted password spaces are rapidly generated in batches in combination with general materials in an existing material library module; the decoding and decryption success rate in the actual combat environment can be effectively improved. Meanwhile, the password generation module can be deployed in a multi-instance and cross-node mode, high-speed parallel work can be achieved, and the overall use efficiency of the decoding and decryption system is improved.

Description

Technical Field

[0001] The present application relates to the technical field of decryption and decoding, and in particular to a password space generation system, method, medium, program product and terminal based on user personal information. Background Art

[0002] In the field of decryption, the existing mainstream practices mainly include two methods: dictionary cracking and mask-based brute force cracking. The basic principle of dictionary cracking is to use a pre-compiled dictionary containing a large number of possible password combinations (usually called a "dictionary"), and try the passwords in the dictionary one by one through an automated program to match the password of the target system (such as computer accounts, network device accounts, encrypted files, etc.). Mask-based brute force cracking sets a specific format mask for the password, and then performs brute force attempts according to the mask rules to find the correct password. The mask can specify the character type, length, position and other information contained in the password. In addition, some researchers have adopted more advanced technologies, such as Markov chains and contextual probability algorithms, to achieve the expansion of existing passwords, and have achieved certain results.

[0003] However, these technical measures ultimately generate broad, majority-oriented decryption strategies. In the real world, many actual cases of password cracking are aimed at specific individuals or groups, which requires that the cracking method can be customized according to the characteristics of individuals or groups. At present, some patents have been published for decryption strategies for specific groups of people, but there are still some limitations.

[0004] For example, the patent "Small Sample Password Set Guessing Method Based on Multi-Task Learning" with publication number CN115098848A discloses a password analysis and guessing method based on small samples. By extracting and training the structural features of small samples, the desired target password structure is generated, and then the password structure is filled with password materials extracted from the small sample training set and the auxiliary training set to generate a new password. However, this small sample is essentially still a bunch of passwords.

[0005] For another example, the patent with publication number CN115549919A, "A dictionary and mask attack method, system, device and storage medium based on artificial intelligence", discloses a framework description of the overall process of decryption. The social engineering library unit in the patent can generate passwords based on personal information, but the specific method of generating passwords based on personal information is not elaborated. Summary of the invention

[0006] In view of the above-mentioned shortcomings of the prior art, the present invention provides a password space generation system, method, medium, program product and terminal based on user personal information, which are used to solve the problem of limitations in password decryption for specific persons or groups in the prior art.

[0007] To achieve the above-mentioned purpose and other related purposes, the first aspect of the present application provides a password space generation system based on user personal information, including: a material library module, used to provide general materials for password generation; a personal information input module, used to input user personal information; the user personal information includes: password information and non-password information; a password structure analysis module, connected to the personal information input module, used to analyze the password information to extract structural expressions and fields; the set composed of each structural expression is a structural expression data set; a material decomposition and extraction module, respectively connected to the personal information input module and the password structure analysis module, used to extract and classify materials from the non-password information in the personal information input module to extract each field to form a first field data set; the fields in the password structure analysis module are semantically divided into types, and the set composed of fields of each semantic type is a second field data set; the first field data set and the second field data set are combined into a single data set. The data sets are integrated into field data sets, and the total number of each structural expression and each semantic type of field in the structural expression data set and the field data set is counted respectively to obtain statistical results; a weight processing module is connected to the material decomposition and extraction module and the material library module respectively, and is used to assign weights to each structural expression and each semantic type of field according to the statistical results in the material decomposition and extraction module to obtain a user personal material library; the weight value in the user personal material library is adjusted according to the general material in the material library module, and the adjusted user personal material library is integrated with the general material to obtain a final password generation material library; a password generation module is connected to the weight processing module, and is used to calculate the weight value of the password according to the weight calculation formula based on the weight values ​​of the structural expressions and fields in the final password generation material library, and generate new passwords in descending order of the weight values ​​of the passwords to reconstruct the password space; wherein the new passwords are generated in parallel.

[0008] In some embodiments of the first aspect of the present application, the method for adjusting the weight value in the user's personal material library according to the common material in the material library module is as follows: the maximum weight value of the structural expression or field in the user's personal material library is slightly higher than the maximum weight value of the corresponding structural expression or field in the common material.

[0009] In some embodiments of the first aspect of the present application, the weight calculation formula is: Among them, Q is the weight value of the password, X is the weight value of the structural expression, N is the sum of the weight values ​​of the semantic types corresponding to each field in the password, and M is the number of fields.

[0010] In some embodiments of the first aspect of the present application, the process of generating the new password in parallel includes: dividing the password space into several intervals, and assigning a computing unit to each interval for password generation; wherein, taking the starting point of the first interval as a reference, setting a corresponding offset for the starting point of each interval, and each computing unit skips its corresponding offset and then generates the password in the corresponding interval.

[0011] In some embodiments of the first aspect of the present application, the password structure analysis module, the material decomposition and extraction module, and the weight processing module are deployed on a management server; and the password generation module is deployed on a decryption platform.

[0012] In some embodiments of the first aspect of the present application, the structure expression includes the data type, length and position of the field.

[0013] To achieve the above-mentioned purpose and other related purposes, the second aspect of the present application provides a password space generation method based on user personal information, which is applied to the password space generation system based on user personal information, and the method includes: providing general materials for password generation; inputting user personal information; the user personal information includes: password information and non-password information; analyzing the password information to extract structural expressions and fields; the set composed of each structural expression is a structural expression data set; extracting and classifying materials from the non-password information in the personal information input module to extract each field to form a first field data set; dividing the fields in the password structure analysis module into semantic types, and the set composed of fields of each semantic type is a second field data set; combining the first field data set and the second field data set The data sets are integrated into field data sets, and the total number of fields of each structural expression and each semantic type in the structural expression data sets and the field data sets are counted respectively to obtain statistical results; weight values ​​are assigned to each structural expression and each semantic type of field according to the statistical results in the material decomposition and extraction module to obtain a user personal material library; the weight value in the user personal material library is adjusted according to the common materials in the material library module, and the adjusted user personal material library is integrated with the common materials to obtain a final password generation material library; based on the weight values ​​of the structural expressions and fields in the final password generation material library, the weight value of the password is calculated according to the weight calculation formula, and new passwords are generated in descending order of the weight values ​​of the passwords to reconstruct the password space; wherein the new passwords are generated in parallel.

[0014] To achieve the above-mentioned purpose and other related purposes, the third aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for generating a password space based on user personal information is implemented.

[0015] To achieve the above-mentioned purpose and other related purposes, the fourth aspect of the present application provides a computer program product, which includes a computer program code. When the computer program code runs on a computer, the computer implements the password space generation method based on user personal information.

[0016] To achieve the above-mentioned purpose and other related purposes, the fifth aspect of the present application provides an electronic terminal, including a memory, a processor and a computer program stored in the memory; the processor executes the computer program to implement the password space generation method based on user personal information.

[0017] As described above, the password space generation system, method, medium, program product and terminal provided by the present application based on user personal information have the following beneficial effects:

[0018] This application analyzes and extracts personalized user personal information, combines the common materials in the existing material library module to quickly generate targeted password spaces in batches, and can effectively improve the success rate of decryption in actual combat environments. At the same time, the password generation module of the present invention can be deployed across multiple nodes in multiple instances, which can achieve high-speed parallel work and improve the overall efficiency of the decryption system. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 Shown is a structural diagram of a password space generation system based on user personal information in one embodiment of the present application.

[0020] Figure 2 Shown is a flowchart of a method for generating a password space based on user personal information in one embodiment of the present application.

[0021] Figure 3 Shown is a schematic diagram of the structure of an electronic terminal in one embodiment of the present application. DETAILED DESCRIPTION

[0022] The following describes the embodiments of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0023] To facilitate understanding of the embodiments of the present application, first Figure 1 Detailed description. Figure 1The present invention shows a schematic diagram of a password space generation system based on user personal information in an embodiment of the present invention. The system includes: a material module 110, a personal information input module 120, a password structure analysis module 130, a material decomposition and extraction module 140, a weight processing module 150 and a password generation module 160.

[0024] In one embodiment, if Figure 1 As shown, the material library module 110 is used to provide general materials for password generation.

[0025] It should be understood that the material library module 110 includes general materials such as structural expressions and fields for password generation, and the general materials include names of people, places, names of objects, common phrases, poems, lyrics, mobile phone numbers, ID numbers, numbers, phrases, special characters, etc. The acquisition method of general materials includes: collecting and collating from the Internet and analyzing and extracting existing password dictionaries. The general materials in the material library module in this embodiment are processed by priority weight allocation, that is, different weight values ​​are assigned to the materials according to the probability of their occurrence in known passwords. The higher the weight value of the material, the more priority it is used for password generation, which can increase the effectiveness or security of the generated password.

[0026] In one embodiment, if Figure 1 As shown, the personal information input module 120 is used to input user personal information; the user personal information includes: password information and non-password information.

[0027] Specifically, the personal information input module 120 can import user personal information through the user interface input, database reading, API interface input or command line. The user personal information refers to the personalized identity information of the user, which is divided into two types: password information and non-password information. Password information includes the user's personal mobile phone password, bank card password, email password, social software password, etc., and non-password information includes the user's personal name, nickname, birthday, mobile phone number, anniversary, etc. By analyzing the user's personal information to obtain the user's password habits and preferences, the system generates passwords that are more in line with the user's habits according to the user's different needs and preferences, and can flexibly adjust the password generation strategy, which is more personalized and targeted, and has higher decryption efficiency.

[0028] In one embodiment, if Figure 1 As shown, the password structure analysis module 130 is connected to the personal information input module 120 and is used to analyze the password information to extract structure expressions and fields; the set composed of each structure expression is a structure expression data set.

[0029] In some examples, the structure expression includes the data type, length, and position of the fields.

[0030] It should be noted that the password structure analysis module 130 receives the password information in the personal information input module 120, analyzes it, and extracts the password structure expression and fields. The structure expression is the structure of the password, including the data type, length and position of the field. The data type of the field includes a letter field, a number field and a special symbol field.

[0031] For example, password information includes the following passwords:

[0032] (1) password, letmein, qwerty (structural expression: pure letter field structure);

[0033] (2) welcome123, secure789, hello456 (structural expression: letter field + number field structure);

[0034] (3) 123@!, 456#$, 789&* (the structure expression is: digital field + special symbol field structure);

[0035] (4) hello@, secure#, admin! (Structural expression: letter field + special symbol field structure);

[0036] (5) John123!, Alice456@, admin789# (the structure expression is: letter field + number field + special symbol field structure).

[0037] It should be understood that the field length refers to the number of characters in the field, for example, in the password "admin789#", the field length of "admin" is 5, the field length of "789" is 3, and the field length of "#" is 1. The position of the field refers to the order in which the fields are arranged in the password, for example, in the password "admin789#", "admin" is the first field, "789" is the second field, and "#" is the third field. The structural expression extracted from the password of the above password-related information is:

[0038] (1) <alphabetic field>;

[0039] (2) <alphabetic field><numeric field>;

[0040] (3) <Numeric field> <Special symbol field>;

[0041] (4) <letter field> <special symbol field>;

[0042] (5) <letter field><number field><special symbol field>.

[0043] Furthermore, the structural expressions extracted from the password information are organized into a structural expression data set.

[0044] In one embodiment, if Figure 1 As shown, the material decomposition and extraction module 140 is connected to the personal information input module 120 and the password structure analysis module 130 respectively, and is used to extract and classify the non-password information in the personal information input module 120 to extract each field to form a first field data set; to divide the fields in the password structure analysis module 130 into semantic types, and the set composed of fields of each semantic type is a second field data set; to integrate the first field data set and the second field data set into a field data set, and to count the total number of fields of each structural expression and each semantic type in the structural expression data set and the field data set respectively to obtain statistical results.

[0045] It should be noted that the personal information input module 120 also includes non-password information, and the password-generating materials are extracted and classified from the non-password information, that is, the fields are semantically divided, and the processing steps include: further dividing the semantic types of the letter fields, numeric fields and special symbol fields based on semantic attributes; wherein the semantic types of the letter fields include one or more combinations of names of people, places, names of objects, common phrases, poems and lyrics, and the semantic types of the numeric fields include one or more combinations of telephone numbers, ID numbers, dates and postal codes.

[0046] Each field in the non-password information is classified and organized into a first field data set. For example, the classification results of the fields in the non-password information are as follows:

[0047] (1) Alphabetical field:

[0048] Names: Bob, Charlie;

[0049] Place names: Paris, London, Tokyo.

[0050] (2) Numeric fields:

[0051] Common years: 1990, 2000, 2023;

[0052] Telephone prefix: 400, 800.

[0053] The fields extracted in the password structure analysis module 130 are divided into the same semantic types and organized into a second field data set. For example, the classification results of the fields of the password information in the above example are as follows:

[0054] (1) Alphabetical field:

[0055] Words: password, letmein, qwerty, welcome, secure, hello, admin;

[0056] Names: John, Alice;

[0057] (2) Numeric fields:

[0058] Common numbers: 123, 456, 789;

[0059] (3) Special symbol field:

[0060] Common symbol combinations: @, #, !, @!, #$, &*;

[0061] Semantic special symbols: ##, ! ! (emphasis), ￥￥ (currency type).

[0062] Furthermore, the first field data set and the second field data set are merged into a field data set, and the total number of fields of each structural expression and each semantic type in the structural expression data set and the field data set are counted respectively. For example, in the above example, the structural expressions are: (1) <letter field> (2) <letter field><numeric field> (3) <numeric field><special symbol field> (4) <letter field><special symbol field> (5) <letter field><numeric field><special symbol field>, a total of five types.

[0063] The field statistics of each semantic type in the above field dataset are as follows:

[0064] (1) Alphabetical field:

[0065] Words: password, letmein, qwerty, welcome, secure, hello, admin (7 in total);

[0066] Names: Bob, Charlie, John, Alice (4 in total);

[0067] Place names: Paris, London, Tokyo (3 in total);

[0068] (2) Numeric fields:

[0069] Common years: 1990, 2000, 2023 (3 in total);

[0070] Telephone prefix: 400, 800 (2 in total);

[0071] Common numbers: 123, 456, 789 (3 in total);

[0072] (3) Special symbol field:

[0073] Common symbol combinations: @, #, !, @!, #$, &* (6 in total);

[0074] Semantic special symbols: ##, ! ! (emphasis), ￥￥ (currency type) (3 in total).

[0075] In one embodiment, if Figure 1 As shown, the weight processing module 150 is connected to the material decomposition and extraction module 140 and the material library module 110 respectively, and is used to assign weights to each structural expression and each semantic type of field according to the statistical results in the material decomposition and extraction module 140 to obtain a user personal material library; the weight value in the user personal material library is adjusted according to the common material in the material library module 110, and the adjusted user personal material library is integrated with the common material to obtain a final password generation material library.

[0076] It should be noted that after analyzing and processing the password information and non-password information in the user's personal information, the structured expression data set, field data set and corresponding statistical results are obtained, and weights are assigned according to the statistical results. The weight assignment is based on the frequency of occurrence of the structured expression in the statistical results. The structured expression with a high frequency (more times) means that it has a higher priority when generating passwords, so it is assigned a larger weight value. Similar to the structured expression, the weight assignment of the field is also based on its frequency of occurrence in the statistical results. Frequently appearing fields will be assigned higher weights to reflect their importance in password generation.

[0077] For example, the weight values ​​of structure expressions can be divided into 1-32 levels, and the weight values ​​of fields can also be divided into 1-32 levels, where level 32 represents the highest priority and level 1 represents the lowest priority. This classification method helps to quickly identify and use high-priority materials when calculating the weight values ​​of passwords later.

[0078] It should be understood that if the weight is too large, invalid information will be amplified, the comprehensiveness and coverage of the password will be reduced, and the generated password will be too concentrated and easy to be cracked. If the weight is too small, personalized information may not be fully integrated, some possible passwords will be missed, and the personalization and security of the password will be reduced. Therefore, the specific value of the weight assignment should be determined according to the actual situation, and the weight assignment strategy should be flexibly adjusted according to different application scenarios and security requirements to achieve the best password generation effect, which is not limited in the embodiments of the present invention.

[0079] The structural expressions and fields after weight assignment are sorted to obtain the user's personal material library. The materials in the user's personal material library highlight the user's password habits and preferences, so that the passwords generated by the system based on the materials in the user's personal material library are more in line with the user's habits, thereby improving the success rate of decryption.

[0080] Furthermore, the user's personal material library is merged with the general materials in the existing material library. The merged materials can increase the combinations of password generation, making the generated passwords more diverse and increasing the possibility of successful decryption. Before the merger, in order to highlight the particularity of the user's personal material library and make the password generation more targeted, the weight value in the user's personal material library is adjusted based on the weight value of the general material.

[0081] Specifically, the weight value in the user's personal material library is adjusted according to the general material in the material library module 110 in the following manner: the maximum weight value of the structural expression or field in the user's personal material library is slightly higher than the maximum weight value of the corresponding structural expression or field in the general material. For example, the maximum weight value of any structural expression in the user's personal material library is greater than the maximum weight value of the corresponding structural expression in the general material, and the weight value of each semantic type of field in the user's personal material library is greater than the maximum weight value of the corresponding semantic type of field in the general material, so that the material (structural expression or field) in the personal material library is preferentially used when generating a password after merging. Preferably, the maximum weight value of the material in the user's personal material library = the maximum weight value of the corresponding material in the general material + 2. After testing, a good cracking hit rate can be obtained under this assignment mode. The user's personal material library after adjusting the weight value is integrated with the general material to obtain the final password generation material library, that is, the materials of the same weight and type are merged, and the final password generation material library includes an analysis result file and an analysis result index file.

[0082] In one embodiment, if Figure 1 As shown, the password generation module 160 is connected to the weight processing module 150, and is used to generate the weight values ​​of the structural expressions and fields in the material library based on the final password, calculate the weight value of the password according to the weight calculation formula, and generate new passwords in descending order according to the weight values ​​of the passwords to reconstruct the password space; wherein the new passwords are generated in parallel.

[0083] In some examples, the weight calculation formula is:

[0084]

[0085] Among them, Q is the weight value of the password, X is the weight value of the structural expression, N is the sum of the weight values ​​of the semantic types corresponding to each field in the password, and M is the number of fields.

[0086] It should be understood that the weight calculation formula does not constitute a limitation on the protection scope of the present invention. The present invention may also use other formulas to calculate the corresponding weight values. Other calculation formulas that can convert frequency data into corresponding weight values ​​all fall within the protection scope of the present invention.

[0087] In some examples, the process of generating the new password in parallel includes: dividing the password space into several intervals, and assigning a computing unit to each interval for password generation; wherein, taking the starting point of the first interval as a reference, setting a corresponding offset for the starting point of each interval, and each computing unit skips its corresponding offset and then generates the password in the corresponding interval.

[0088] For example, there is a password space sorted by weight, containing 12 passwords: a1#, a1&, a2#, a2&, b1#, b1&, b2#, b2&, c1#, c1&, c2#, c2&. The password space can be divided into 3 intervals, and 4 passwords are generated in each interval:

[0089] Interval 1: a1#, a1&, a2#, a2&.

[0090] Interval 2: b1#, b1&, b2#, b2&.

[0091] Interval 3: c1#, c1&, c2#, c2&.

[0092] Assign different computing units to intervals 1 to 3 for generation. Each computing unit only needs to load the subspace data it is responsible for and does not need to process the entire password space. In addition, multiple computing units can simultaneously process different parts of the password space to speed up the generation. In addition, the offset and password quantity parameters can be used to ensure that the task scope of each subspace is clear and the generated passwords do not overlap or miss.

[0093] Preferably, the weight value of each semantic type of field in the final password generation material library is assigned an analysis result file, and at the same time, the weight values ​​of all semantic types are summarized to generate an analysis result index file, which contains information such as material type, corresponding weight, and material quantity. Compared with dictionary files and material library files (usually at the level of tens of GB), the volume of the analysis result file is much smaller (at the level of several MB). Therefore, the analysis result file can be sent to the password generation module on the computing node through a network interface call, or it can be accessed by the password generation module on the computing node in the form of a shared file through shared storage. The access method is selected according to the actual situation and is not limited in the embodiment of the present application. When generating a password, according to the analysis result index file, the number of passwords specified by the offset parameter can be quickly skipped by simple calculation, and then the specified analysis result file content is read, and the specified number of passwords is quickly generated according to the password quantity parameter.

[0094] In some examples, the password structure analysis module, the material decomposition and extraction module, and the weight processing module are deployed on a management server; and the password generation module is deployed on a decryption platform.

[0095] Combination Figure 1 Description: Each computing node (computing unit) deploys a set of password generator programs, and the analysis result files and analysis result index files are stored in the shared storage area, which can be accessed by the weight processing module in the management server and the password generation module in the computing node at the same time. The password generation module deployment mode is distributed multi-instance deployment, forming a decryption cluster, in which each deployment instance can independently use one or more sets of offset and password quantity parameters, and generate passwords within the parameter specified range. Different deployment instances run independently and concurrently at the same time. The generated password is directly transferred to the decryption program through memory sharing or pipeline, without the need for transfer through the file storage system.

[0096] Furthermore, the operations of configuring the password interval (offset and number of passwords) and calling the password generation module can also be completed autonomously by the third scheduling program, thereby realizing the automation of the entire decryption process. When the computing unit (computing node) completes the calculation of the password in one interval, it can quickly obtain the next interval from the third-party scheduling program for password calculation until the decryption calculation operation is completed in all intervals in the plan. In this way, multiple computing units can be operated concurrently, the computing power resources can be maximized, and the decryption time can be reduced.

[0097] It should be emphasized that when the system in the embodiment of the present application is working, it first initializes the material library (general material) through the manual import mode, and then analyzes the user's personal information through the password structure analysis module and the material decomposition and extraction module, and generates an analysis result file and an analysis result index component in combination with the general material. Finally, a different password interval is assigned to each computing node (computing unit) by configuring the offset and the number of passwords. The password generator in the computing node generates the password of the corresponding interval and sends it to the decryption program for subsequent processing.

[0098] This application analyzes and extracts personalized user personal information, combines the common materials in the existing material library module to quickly generate targeted password spaces in batches, and can effectively improve the success rate of decryption in actual combat environments. At the same time, the password generation module of the present invention can be deployed across multiple nodes in multiple instances, which can achieve high-speed parallel work and improve the overall efficiency of the decryption system.

[0099] In the embodiments of the present application, words such as "first" and "second" are used to distinguish the same or similar items with substantially the same functions and effects, and do not limit their order. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit them to be different.

[0100] It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" represent examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0101] In the embodiments of the present application, "at least one" refers to one or more, and "plurality" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can represent: a, b, c, ab, ac, bc or abc, where a, b, c can be single or multiple.

[0102] Figure 2 is a schematic block diagram of a method for generating a password space based on user personal information provided by an embodiment of the present application. Figure 2 As shown, the method includes:

[0103] Step S21: providing general materials for password generation;

[0104] Step S22: inputting user personal information; the user personal information includes: password information and non-password information;

[0105] Step S23: Analyze the password information to extract structure expressions and fields; the set of each structure expression is a structure expression data set;

[0106] Step S24: extracting and classifying the non-password information in the personal information input module to extract various fields to form a first field data set; classifying the fields in the password structure analysis module into semantic types, and a set of fields of each semantic type is a second field data set; integrating the first field data set and the second field data set into a field data set, and respectively counting the total number of fields of each structural expression and each semantic type in the structural expression data set and the field data set to obtain statistical results;

[0107] Step S25: assigning weights to each structural expression and each semantic type of field according to the statistical results in the material decomposition and extraction module to obtain a user personal material library; adjusting the weight values ​​in the user personal material library according to the general materials in the material library module, and integrating the adjusted user personal material library with the general materials to obtain a final password generation material library;

[0108] Step S26: Based on the structural expressions and field weight values ​​in the final password generation material library, the weight value of the password is calculated according to the weight calculation formula, and new passwords are generated in descending order according to the weight values ​​of the passwords to reconstruct the password space; wherein the new passwords are generated in parallel.

[0109] It should be noted that the password space generation method based on user personal information provided in the present application can be specifically applied to controllers such as ARM (Advanced RISC Machines), FPGA (Field Programmable Gate Array), SoC (System on Chip), DSP (Digital Signal Processing), or MCU (Microcontroller Unit); or can be applied to computers including components such as memory, storage controller, one or more processing units (CPU), peripheral interface, RF circuit, audio circuit, speaker, microphone, input / output (I / O) subsystem, display, other output or control devices, and external ports; the computer includes but is not limited to personal computers such as desktop computers, laptops, tablet computers, smart phones, smart TVs, personal digital assistants (PDA for short); it can also be applied to servers, which can be arranged on one or more physical servers according to various factors such as function and load, or can be composed of distributed or centralized server clusters.

[0110] It should be understood that the specific process of executing the above corresponding steps has been described in detail in the above module embodiments, and for the sake of brevity, it will not be repeated here.

[0111] It should also be understood that the division of modules in the embodiments of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, each functional module in each embodiment of the present application may be integrated into a processor, or may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated modules may be implemented in the form of hardware or in the form of software functional modules.

[0112] Figure 3 is a schematic block diagram of an electronic terminal provided in an embodiment of the present application. Figure 3 As shown, the electronic terminal includes: at least one processor 301, a memory 302, at least one network interface 303 and a user interface 305. The various components in the device are coupled together through a bus system 304. It can be understood that the bus system 304 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 304 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, Figure 3 In the specification, various buses are labeled as bus systems.

[0113] The user interface 305 may include a display, a keyboard, a mouse, a trackball, a click gun, keys, buttons, a touch pad or a touch screen.

[0114] It is understood that the memory 302 can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM). The memory described in the embodiments of the present invention is intended to include but is not limited to these and any other suitable categories of memory.

[0115] The memory 302 in the embodiment of the present invention is used to store various categories of data to support the operation of the electronic terminal 300. Examples of these data include: any executable program used to operate on the electronic terminal 300, such as an operating system 3021 and an application 3022; the operating system 3021 includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., for implementing various basic services and processing hardware-based tasks. The application 3022 can include various applications, such as a media player (Media Player), a browser (Browser), etc., for implementing various application services. The password space generation method based on user personal information provided in the embodiment of the present invention can be included in the application 3022.

[0116] The method disclosed in the above embodiment of the present invention can be applied to the processor 301, or implemented by the processor 301. The processor 301 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit in the processor 301 or the instruction in the form of software. The above processor 301 may be a general processor, a digital signal processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor 301 can implement or execute the methods, steps and logic block diagrams disclosed in the embodiment of the present invention. The general processor 301 can be a microprocessor or any conventional processor, etc. In combination with the steps of the accessory optimization method provided in the embodiment of the present invention, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium, which is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0117] In an exemplary embodiment, the electronic terminal 300 may be implemented by one or more application specific integrated circuits (ASIC), DSP, programmable logic device (PLD), complex programmable logic device (CPLD) to execute the aforementioned method.

[0118] According to the method provided in the embodiments of the present application, the present application also provides a computer program product, which includes: computer program code, when the computer program code is run on a computer, the computer executes the password space generation method based on user personal information of any embodiment of the illustrated embodiments.

[0119] According to the method provided in the embodiments of the present application, the present application also provides a computer-readable storage medium, which stores a program code. When the program code runs on a computer, the computer executes the password space generation method based on user personal information of any embodiment of the illustrated embodiments.

[0120] The terms "component", "module", "system", etc. used in this specification are used to represent computer-related entities, hardware, firmware, a combination of hardware and software, software, or software in execution. For example, a component can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program and / or a computer. By way of illustration, both applications running on a computing device and a computing device can be components. One or more components may reside in a process and / or an execution thread, and a component may be located on a computer and / or distributed between two or more computers. In addition, these components may be executed from various computer-readable media having various data structures stored thereon. Components may, for example, communicate through local and / or remote processes according to signals having one or more data packets (e.g., data from two components interacting with another component between a local system, a distributed system and / or a network, such as the Internet interacting with other systems through signals).

[0121] Those of ordinary skill in the art will appreciate that the various illustrative logical blocks and steps described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or in 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 may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0122] 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.

[0123] 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 units is only a logical function division. There may be other division methods in actual implementation. For example, 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.

[0124] 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.

[0125] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0126] In the above embodiments, the functions of each functional unit can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions (programs). When loading and executing computer program instructions (programs) on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media integrations. Available media may be magnetic media (e.g., floppy disks, hard disks, tapes), optical media (e.g., high-density digital video discs (DVDs), or semiconductor media (e.g., solid state disks (SSDs), etc.).

[0127] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0128] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0129] In summary, the present application provides a password space generation system, method, medium, program product and terminal based on user personal information. The present application analyzes and extracts personalized user personal information, combines the common materials in the existing material library module to quickly generate targeted password spaces in batches, and can effectively improve the success rate of decryption in actual combat environments. At the same time, the password generation module of the present invention can be deployed across multiple nodes, can achieve high-speed parallel work, and improve the overall use efficiency of the decryption system. Therefore, the present application effectively overcomes the various shortcomings in the prior art and has a high industrial utilization value.

[0130] The above embodiments are merely illustrative of the principles and effects of the present application and are not intended to limit the present application. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed in the present application shall still be covered by the claims of the present application.

Claims

1. A password space generation system based on user personal information, characterized in that: include: The material library module is used to provide common materials for password generation; Personal information input module, used to input user personal information; The user personal information includes: password information and non-password information; A password structure analysis module, connected to the personal information input module, is used to analyze the password information to extract structure expressions and fields; the set of each structure expression is a structure expression data set; A material decomposition and extraction module, connected to the personal information input module and the password structure analysis module respectively, for extracting and classifying the non-password information in the personal information input module, so as to extract each field to form a first field data set; performing semantic type classification on the fields in the password structure analysis module, and a set of fields of each semantic type is a second field data set; integrating the first field data set and the second field data set into a field data set, and respectively counting the total number of fields of each structural expression and each semantic type in the structural expression data set and the field data set to obtain statistical results; A weight processing module is connected to the material decomposition and extraction module and the material library module respectively, and is used to assign weights to each structural expression and each semantic type of field according to the statistical results in the material decomposition and extraction module to obtain a user personal material library; the weight value in the user personal material library is adjusted according to the general material in the material library module, and the adjusted user personal material library is integrated with the general material to obtain a final password generation material library; A password generation module is connected to the weight processing module, and is used to generate the weight values ​​of the structural expressions and fields in the material library based on the final password, calculate the weight value of the password according to the weight calculation formula, and generate new passwords in descending order according to the weight values ​​of the passwords to reconstruct the password space; wherein the new passwords are generated in parallel.

2. The password space generation system based on user personal information according to claim 1 is characterized in that: The method of adjusting the weight value in the user's personal material library according to the common material in the material library module is as follows: the maximum weight value of the structural expression or field in the user's personal material library is slightly higher than the maximum weight value of the corresponding structural expression or field in the common material.

3. The password space generation system based on user personal information according to claim 1 is characterized in that: The weight calculation formula is: Among them, Q is the weight value of the password, X is the weight value of the structural expression, N is the sum of the weight values ​​of the semantic types corresponding to each field in the password, and M is the number of fields.

4. The password space generation system based on user personal information according to claim 1, characterized in that: The process of generating the new password in parallel includes: The password space is divided into several intervals, and a computing unit is assigned to each interval for password generation; wherein, taking the starting point of the first interval as a reference, a corresponding offset is set for the starting point of each interval, and each computing unit skips its corresponding offset and then generates a password in the corresponding interval.

5. The password space generation system based on user personal information according to claim 1 is characterized in that: The password structure analysis module, material decomposition and extraction module and weight processing module are deployed on the management server; the password generation module is deployed on the decryption platform.

6. The password space generation system based on user personal information according to claim 1 is characterized in that: The structure expression includes the data type, length and position of the field.

7. A method for generating a password space based on user personal information, characterized in that: Applied to the password space generation system based on user personal information as described in any one of claims 1 to 6, the method comprising: Provide common materials for password generation; Enter user personal information; the user personal information includes: password information and non-password information; Analyze the password information to extract structure expressions and fields; a set of each structure expression is a structure expression data set; Extract and classify the non-password information in the personal information input module to extract various fields to form a first field data set; divide the fields in the password structure analysis module into semantic types, and the set formed by the fields of each semantic type is a second field data set; integrate the first field data set and the second field data set into a field data set, and count the total number of fields of each structural expression and each semantic type in the structural expression data set and the field data set, respectively, to obtain statistical results; According to the statistical results in the material decomposition and extraction module, weights are assigned to each structural expression and each semantic type of field to obtain a user personal material library; according to the general materials in the material library module, the weight values ​​in the user personal material library are adjusted, and the adjusted user personal material library is integrated with the general materials to obtain a final password generation material library; Based on the structural expressions and field weight values ​​in the final password generation material library, the weight value of the password is calculated according to the weight calculation formula, and new passwords are generated in descending order according to the weight values ​​of the passwords to reconstruct the password space; wherein the new passwords are generated in parallel.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for generating a password space based on user personal information as described in claim 7 is implemented.

9. A computer program product, characterized in that The computer program product includes computer program codes, and when the computer program codes are executed on a computer, the computer is enabled to implement the method for generating a password space based on user personal information as claimed in claim 7.

10. An electronic terminal comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the password space generation method based on user personal information as described in claim 7.

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