Data dynamic encryption transmission method and system based on remote office platform

Abstract

The invention discloses a data dynamic encryption transmission method and system based on a remote office platform, and relates to the technical field of remote office, and the method comprises the steps: obtaining all remote office terminals connected to the remote office platform; sample working behaviors are collected; extracting behavior characteristic data based on the sample working behavior, and recording the behavior characteristic data as sample working behavior characteristic data; obtaining a normal working behavior characteristic relation database of the remote office terminal; real-time working behaviors of the remote office terminal are obtained in real time; extracting real-time working behavior characteristics of a plurality of remote office terminals; calculating a reasonable index of the real-time working behavior of the remote office terminal; determining an encryption level of data transmission of the remote office terminal; and generating encrypted data by adopting a data scrambling algorithm and transmitting the encrypted data to a remote office terminal. The method has the advantages that analysis and learning are performed based on behaviors of the remote office terminal during normal working of the remote office terminal, data encryption is dynamically adjusted based on working behavior characteristics, and data security of the remote office platform is guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of remote office technology, and in particular to a data dynamic encryption transmission method and system based on a remote office platform. Background Art

[0002] A remote office platform refers to a system or platform that allows employees to collaborate and communicate with each other through the Internet and dedicated software tools when they are geographically dispersed. These platforms usually integrate multiple functions to support the efficient operation of remote teams, including but not limited to file sharing, real-time communication, project management, task assignment, video conferencing, scheduling, online collaborative editing, etc.

[0003] The main purpose of remote working platforms is to break geographical restrictions and enable team members to stay closely connected and collaborate seamlessly no matter where they are. They provide remote workers with the necessary tools and environment to ensure smooth workflow while maintaining the security and confidentiality of information.

[0004] With the continuous development of technologies such as cloud computing, big data, and artificial intelligence, the functions and performance of remote office platforms are also constantly improving. Modern remote office platforms are usually highly scalable, flexible, and easy to use, and can meet the needs of enterprises of different sizes and industries.

[0005] The secure transmission of data on remote office platforms is an important issue for remote office platforms. Existing remote office platforms lack analysis of the working behavior characteristics of remote office terminals. When remote office terminals are hijacked, it is difficult to identify them in a timely manner and the data encryption method cannot be adjusted dynamically, resulting in the risk of data leakage. Summary of the invention

[0006] In order to solve the above-mentioned technical problems, a data dynamic encryption transmission method and system based on a remote office platform are provided. This technical solution solves the problem that the above-mentioned existing remote office platform lacks analysis of the working behavior characteristics of the remote office terminal. When the remote office terminal is hijacked, it is difficult to identify it in time and the data encryption method cannot be dynamically adjusted, resulting in the risk of data leakage.

[0007] In order to achieve the above purpose, the technical solution adopted by the present invention is: A data dynamic encryption transmission method based on a remote office platform, comprising: Obtain all remote office terminals connected to the remote office platform; Collect historical work behaviors of remote office terminals during normal working process and record them as sample work behaviors; Extracting behavior feature data based on the sample work behavior, recorded as sample work behavior feature data, wherein the behavior feature data at least includes access features and time features; Analyze and learn based on sample behavior feature data to obtain a normal working behavior feature relationship database of the remote office terminal; The behavior of the remote office terminal during the working process is obtained in real time, and recorded as the real-time working behavior of the remote office terminal; Extracting several real-time working behavior features of remote office terminals based on the real-time working behavior of remote office terminals; Based on the real-time working behavior characteristics of remote office terminals, a behavioral risk identification algorithm is used to calculate reasonable indicators of real-time working behavior of remote office terminals; Determine the encryption level of data transmission from remote office terminals based on reasonable indicators of real-time working behavior of remote office terminals; According to the encryption level of data transmission of the remote office terminal, a data scrambling algorithm is used to generate encrypted data and transmit it to the remote office terminal.

[0008] Preferably, the analyzing and learning based on the sample behavior feature data to obtain the normal working behavior feature relationship database of the remote office terminal specifically includes: Divide a day into several analysis periods according to the set working hours; Based on the time characteristics of the sample work behavior, determine the analysis period corresponding to the sample work behavior; Count all sample work behaviors corresponding to each analysis period; Based on the access features of the sample work behavior corresponding to each analysis period, the feature correlation algorithm is used to calculate the correlation between the access features corresponding to each analysis period; The correlation between the sample work behavior corresponding to each analysis period and the access feature corresponding to each analysis period is encapsulated into a normal work behavior feature relationship database of the remote office terminal.

[0009] Preferably, the feature correlation algorithm is specifically: The access characteristics of the sample work behavior corresponding to the analysis period are recorded as the access characteristics corresponding to the analysis period; All access features corresponding to the analysis period are combined into an access feature set A, A={a 1 , …, a i , …, a n}, where a i is the i-th access feature corresponding to the analysis period, and n is the total number of access features corresponding to the analysis period; Determine the occurrence of a during the analysis period i A number of sample work behaviors of compose a first sample work behavior set; Determine the occurrence of a during the analysis period j A number of sample work behaviors of compose a second sample work behavior set; Find the intersection of the first sample work behavior set and the second sample work behavior set to obtain a third sample work behavior set; Taking the union of the second sample work behavior set and the second sample work behavior set, to obtain a fourth sample work behavior set; Determining the number of elements in the first sample work behavior set, the number of elements in the second sample work behavior set, the number of elements in the third sample work behavior set, and the number of elements in the fourth sample work behavior set; Calculate a by using the correlation calculation formula i and a j The correlation between The correlation calculation formula is specifically: ; In the formula, for a i and a j The correlation between 0 is the total number of sample work behaviors corresponding to the analysis period, N 1 is the number of elements in the first sample work behavior set, N 2 is the number of elements in the second sample work behavior set, N 1∩2 is the number of elements in the third sample work behavior set, N 1∪2 is the number of elements in the fourth sample work behavior set.

[0010] Preferably, the behavior risk identification algorithm specifically includes: Based on the time characteristics in the real-time work behavior characteristics of the remote office terminal, determine the analysis period corresponding to the real-time work behavior of the remote office terminal, and record it as the real-time analysis period; Retrieve the normal working behavior characteristic relation database corresponding to the real-time analysis period; Combining multiple remote office terminal real-time access features in the remote office terminal real-time work behavior features into a plurality of remote office terminal real-time access feature groups; Retrieve the two remote office terminal real-time access features in each remote office terminal real-time access feature group in the normal working behavior feature relationship database, determine the correlation between the two remote office terminal real-time access features in the remote office terminal real-time access feature group, and use it as the rationality of the remote office terminal real-time access feature group; if the correlation between the two remote office terminal real-time access features in each remote office terminal real-time access feature group cannot be retrieved in the normal working behavior feature relationship database, assign a value of 0 to the rationality of the remote office terminal real-time access feature group; Based on the rationality calculation formula, the rationality of the real-time working behavior of the remote office terminal is calculated; The rationality calculation formula is specifically: ; Where H is the rationality of the real-time working behavior of the remote office terminal, K is the total number of real-time access feature groups of the remote office terminal, and X 1 is the rationality of the real-time access feature group of the lth remote office terminal.

[0011] Preferably, the determining of the encryption level of the remote office terminal data transmission based on the reasonable index of the real-time working behavior of the remote office terminal specifically includes: Determine the maximum level of scrambling encryption set by the remote office platform; Based on the rationality of the real-time working behavior of the remote office terminal and the maximum level of scrambling encryption, the level indicator of the remote office terminal data transmission is determined through a level determination formula; Based on the upward rounding of the level index of the remote office terminal data transmission, the encryption level of the remote office terminal data transmission is obtained; The level determination formula is specifically: ; Where L' is the level index of remote office terminal data transmission, L max The maximum level of encryption for scrambling.

[0012] Preferably, the step of using a data scrambling algorithm to generate encrypted data and transmit it to the remote office terminal according to the encryption level of the data transmitted by the remote office terminal specifically includes: The encryption level of remote office terminal data transmission is L; Convert the remote office terminal data to be transmitted into binary data, and extract L from the binary data in order from front to back. 2 characters, recorded as a characteristic character segment, if the number of remaining characters is less than L 2 , then add 0 to the last remaining character until the number of characters reaches L 2 ; Determine the total number of extracted characteristic character segments, recorded as M, and add a number between 1 and M to each characteristic character segment in sequence according to the order of the characteristic character segments in the binary data; Randomly sort the integers between 1 and M to obtain the initial scrambled key; According to the order of the integers between 1 and M in the initial scrambling key, the corresponding characteristic character segments are sorted in turn to obtain the initial scrambling data; A square scrambling algorithm is used to encrypt each characteristic character segment in the initial scrambled data to obtain encrypted data.

[0013] Preferably, the position scrambling algorithm is specifically: Generate an L×L grid and replace 1-L 2 Randomly fill in the L×L square with positive integers; Numbered according to the sequence of characters in the characteristic character segment, 1-L 2 The characters in the feature character segment are filled in the positions of the positive integers in the L×L square; Characters are extracted from the L×L square in order from left to right and from top to bottom to obtain the positionally encrypted character segment of the characteristic character segment.

[0014] Furthermore, a data dynamic encryption transmission system based on a remote office platform is proposed, which is used to implement the data dynamic encryption transmission method based on the remote office platform as described above, including: A log module, which is used to obtain all remote office terminals connected to the remote office platform and collect historical work behaviors of the remote office terminals during normal work, which are recorded as sample work behaviors; A behavior analysis module, the behavior analysis module is electrically connected to the log module, the behavior analysis module is used to extract behavior feature data based on the sample work behavior, recorded as sample work behavior feature data, the behavior feature data at least includes access features and time features, and analyzes and studies the sample behavior feature data to obtain a normal work behavior feature relationship database of the remote office terminal; A work behavior monitoring module, the work behavior monitoring module is electrically connected to the behavior analysis module, the work behavior monitoring unit is used to obtain the behavior of the remote office terminal in the working process in real time, recorded as the real-time work behavior of the remote office terminal, and extract a number of real-time work behavior characteristics of the remote office terminal based on the real-time work behavior of the remote office terminal, and based on the real-time work behavior characteristics of the remote office terminal, a behavior risk identification algorithm is used to calculate a reasonable index of the real-time work behavior of the remote office terminal; An encryption module is electrically connected to the work behavior monitoring module, and is used to determine the encryption level of data transmission of the remote office terminal based on reasonable indicators of the real-time work behavior of the remote office terminal, and to generate encrypted data and transmit it to the remote office terminal using a data scrambling algorithm according to the encryption level of data transmission of the remote office terminal.

[0015] Compared with the prior art, the present invention has the following beneficial effects: Since remote office terminals correspond one-to-one to office workers and office workers have consistent office habits, this solution analyzes and studies the behavior of remote office terminals during normal working hours to obtain a normal working behavior feature relationship database that conforms to the behavioral habits of remote office terminals. Based on the normal working behavior feature relationship database, behavioral risk identification is performed on the real-time working behavior of remote office terminals during the working process of remote office terminals. When the identified behavior does not conform to the behavioral habits of remote office terminals, it is determined that the remote office terminal is at high risk of being hijacked, so a high-level encryption method is used for data transmission. In this way, even if the data is hijacked and leaked, the high-level encrypted data is difficult to decipher and can effectively resist brute force attacks to ensure the data security of the remote office platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Flowchart of the data dynamic encryption transmission method based on the remote office platform proposed in this solution; Figure 2 A flow chart of the method for obtaining a normal working behavior characteristic relation database of a remote office terminal in this solution; Figure 3 A method flow chart of the behavioral risk identification algorithm in this solution; Figure 4 A flow chart of the method for determining the encryption level of remote office terminal data transmission in this solution; Figure 5 A flow chart of the method for using a data scrambling algorithm to generate encrypted data for transmission to a remote office terminal in this solution; Figure 6 This is a method flow chart of the direction scrambling algorithm in this scheme; Figure 7 This is a schematic diagram of the electronic device in this solution; Figure 8 This is a schematic diagram of the computer-readable storage medium structure in this solution. DETAILED DESCRIPTION

[0017] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0018] Reference Figure 1 As shown, a data dynamic encryption transmission method based on a remote office platform includes: Obtain all remote office terminals connected to the remote office platform; Collect historical work behaviors of remote office terminals during normal working process and record them as sample work behaviors; Extracting behavior feature data based on the sample work behavior, recorded as sample work behavior feature data, the behavior feature data at least including access features and time features; Analyze and learn based on sample behavior feature data to obtain a normal working behavior feature relationship database of the remote office terminal; The behavior of the remote office terminal during the working process is obtained in real time, and recorded as the real-time working behavior of the remote office terminal; Extracting several real-time working behavior features of remote office terminals based on the real-time working behavior of remote office terminals; Based on the real-time working behavior characteristics of remote office terminals, a behavioral risk identification algorithm is used to calculate reasonable indicators of real-time working behavior of remote office terminals; Determine the encryption level of data transmission from remote office terminals based on reasonable indicators of real-time working behavior of remote office terminals; According to the encryption level of data transmission of the remote office terminal, a data scrambling algorithm is used to generate encrypted data and transmit it to the remote office terminal.

[0019] Based on the analysis and learning of the behavior of the remote office terminal during normal working, a normal working behavior feature relationship database that conforms to the behavioral habits of the remote office terminal is obtained. Based on the normal working behavior feature relationship database, behavioral risk identification is performed on the real-time working behavior of the remote office terminal during the working process of the remote office terminal. For the identified behavior that does not conform to the behavioral habits of the remote office terminal, it is determined that the remote office terminal is at high risk of being hijacked, so a high-level encryption method is used for data transmission.

[0020] Reference Figure 2 As shown, based on the analysis and learning of sample behavior feature data, the normal working behavior feature relationship database of the remote office terminal is obtained, which specifically includes: Divide a day into several analysis periods according to the set working hours; Based on the time characteristics of the sample work behavior, determine the analysis period corresponding to the sample work behavior; Count all sample work behaviors corresponding to each analysis period; Based on the access features of the sample work behavior corresponding to each analysis period, the feature correlation algorithm is used to calculate the correlation between the access features corresponding to each analysis period; The correlation between the sample work behavior corresponding to each analysis period and the access feature corresponding to each analysis period is encapsulated into a normal work behavior feature relationship database of the remote office terminal.

[0021] The feature correlation algorithm is as follows: The access characteristics of the sample work behavior corresponding to the analysis period are recorded as the access characteristics corresponding to the analysis period; All access features corresponding to the analysis period are combined into an access feature set A, A={a 1 , …, a i , …, a n}, where a i is the i-th access feature corresponding to the analysis period, and n is the total number of access features corresponding to the analysis period; Determine the occurrence of a during the analysis period i A number of sample work behaviors of compose a first sample work behavior set; Determine the occurrence of a during the analysis period j A number of sample work behaviors of compose a second sample work behavior set; Find the intersection of the first sample work behavior set and the second sample work behavior set to obtain a third sample work behavior set; Taking the union of the second sample work behavior set and the second sample work behavior set, to obtain a fourth sample work behavior set; Determining the number of elements in the first sample work behavior set, the number of elements in the second sample work behavior set, the number of elements in the third sample work behavior set, and the number of elements in the fourth sample work behavior set; Calculate a by using the correlation calculation formula i and a j The correlation between The correlation calculation formula is as follows: ; for a i and a j The correlation between 0 is the total number of sample work behaviors corresponding to the analysis period, N 1 is the number of elements in the first sample work behavior set, N 2 is the number of elements in the second sample work behavior set, N 1∩2 is the number of elements in the third sample work behavior set, N 1∪2 is the number of elements in the fourth sample work behavior set.

[0022] The behavior of workers in the process of normal work is usually cyclical every day. This cyclical behavior habit is determined by the daily work and rest of the workers. In some preferred embodiments, the work and rest is classified into holidays and working days according to the attributes of the date, and the holidays and working days are analyzed and studied separately to obtain a normal work behavior feature relationship database for holidays and a normal work behavior feature relationship database for working days; In this scheme, the calculation formula for correlation consists of two parts, one of which is a i and a jThe proportion of the corresponding usage behavior in the usage behavior in the current period, that is, , which represents the worker's behavior habits, and the other part is a i and a j The rationality of the simultaneous occurrence of This part represents whether the behavior is normal. It is calculated by combining the user's behavior habits and whether the behavior is normal. i and a j The correlation between them is greater, the greater the correlation value is. i and a j The higher the plausibility of the simultaneous occurrence within the current analysis period.

[0023] Reference Figure 3 As shown in Figure 1, the behavioral risk identification algorithm specifically includes: Based on the time characteristics in the real-time work behavior characteristics of the remote office terminal, determine the analysis period corresponding to the real-time work behavior of the remote office terminal, and record it as the real-time analysis period; Retrieve the normal working behavior characteristic relation database corresponding to the real-time analysis period; Combining multiple remote office terminal real-time access features in the remote office terminal real-time work behavior features into a plurality of remote office terminal real-time access feature groups; Retrieve the two remote office terminal real-time access features in each remote office terminal real-time access feature group in the normal working behavior feature relationship database, determine the correlation between the two remote office terminal real-time access features in the remote office terminal real-time access feature group, and use it as the rationality of the remote office terminal real-time access feature group; if the correlation between the two remote office terminal real-time access features in each remote office terminal real-time access feature group cannot be retrieved in the normal working behavior feature relationship database, assign a value of 0 to the rationality of the remote office terminal real-time access feature group; Based on the rationality calculation formula, the rationality of the real-time working behavior of the remote office terminal is calculated; The specific formula for calculating rationality is: ; Where H is the rationality of the real-time working behavior of the remote office terminal, K is the total number of real-time access feature groups of the remote office terminal, and X 1 is the rationality of the real-time access feature group of the lth remote office terminal.

[0024] Reference Figure 4 As shown, based on the reasonable indicators of the real-time working behavior of the remote office terminal, the encryption level of the remote office terminal data transmission is determined specifically including: Determine the maximum level of scrambling encryption set by the remote office platform; Based on the rationality of the real-time working behavior of the remote office terminal and the maximum level of scrambling encryption, the level indicator of the remote office terminal data transmission is determined through a level determination formula; Based on the upward rounding of the level index of the remote office terminal data transmission, the encryption level of the remote office terminal data transmission is obtained; The specific formula for determining the grade is: ; Where L' is the level index of remote office terminal data transmission, L max The maximum level of encryption for scrambling.

[0025] The encryption level is determined based on the reasonable level. The larger the reasonable index is, the more the remote office terminal conforms to the worker's work habits and the lower the risk of being held hostage. Therefore, the encryption level can be appropriately lowered.

[0026] Reference Figure 5 As shown, according to the encryption level of the remote office terminal data transmission, using the data scrambling algorithm to generate encrypted data and transmit it to the remote office terminal specifically includes: The encryption level of remote office terminal data transmission is L; Convert the remote office terminal data to be transmitted into binary data, and extract L from the binary data in order from front to back. 2 characters, recorded as a characteristic character segment, if the number of remaining characters is less than L 2 , then add 0 to the last remaining character until the number of characters reaches L 2 ; Determine the total number of extracted characteristic character segments, recorded as M, and add a number between 1 and M to each characteristic character segment in sequence according to the order of the characteristic character segments in the binary data; Randomly sort the integers between 1 and M to obtain the initial scrambled key; According to the order of the integers between 1 and M in the initial scrambling key, the corresponding characteristic character segments are sorted in turn to obtain the initial scrambling data; A square scrambling algorithm is used to encrypt each characteristic character segment in the initial scrambled data to obtain encrypted data.

[0027] Reference Figure 6 As shown, the specific position scrambling algorithm is: Generate an L×L grid and replace 1-L 2 Randomly fill in the L×L square with positive integers; Numbered according to the sequence of characters in the characteristic character segment, 1-L 2 The characters in the feature character segment are filled in the positions of the positive integers in the L×L square; Characters are extracted from the L×L square in order from left to right and from top to bottom to obtain the positionally encrypted character segment of the characteristic character segment.

[0028] The double-reset random encryption method is used to dynamically adjust the encryption level. Since the initial random data is obtained by the initial random method, and the smaller the encryption level, the lower the encryption level of the random algorithm, but the encryption level of the initial random method designed in this scheme will be higher, thereby effectively ensuring the comprehensive encryption security of the data and ensuring data security at a low encryption level.

[0029] Further, based on the same inventive concept as the above-mentioned data dynamic encryption transmission method based on the remote office platform, this solution proposes a data dynamic encryption transmission system based on the remote office platform, including: Log module: The log module is used to obtain all remote office terminals connected to the remote office platform, and collect historical work behaviors of the remote office terminals during normal work, which are recorded as sample work behaviors; A behavior analysis module, the behavior analysis module is electrically connected to the log module, and the behavior analysis module is used to extract behavior feature data based on the sample work behavior, recorded as sample work behavior feature data, the behavior feature data at least includes access features and time features, and analyzes and learns based on the sample behavior feature data to obtain a normal work behavior feature relationship database of the remote office terminal; A work behavior monitoring module, the work behavior monitoring module is electrically connected to the behavior analysis module, the work behavior monitoring unit is used to obtain the behavior of the remote office terminal in the working process in real time, recorded as the real-time work behavior of the remote office terminal, and extract a number of real-time work behavior characteristics of the remote office terminal based on the real-time work behavior of the remote office terminal, and based on the real-time work behavior characteristics of the remote office terminal, a behavior risk identification algorithm is used to calculate the reasonable indicators of the real-time work behavior of the remote office terminal; The encryption module is electrically connected to the work behavior monitoring module. The encryption module is used to determine the encryption level of the remote office terminal data transmission based on reasonable indicators of the real-time work behavior of the remote office terminal, and according to the encryption level of the remote office terminal data transmission, use a data scrambling algorithm to generate encrypted data and transmit it to the remote office terminal.

[0030] Furthermore, the method according to the embodiment of the present application can also be performed by Figure 7 The electronic device architecture shown in FIG. Figure 7As shown, the electronic device 500 may include a bus 501, one or more CPUs 502, a read-only memory (ROM) 503, a random access memory (RAM) 504, a communication port 505 connected to a network, an input / output component 506, a hard disk 507, etc. The storage device in the electronic device 500, such as the ROM 503 or the hard disk 507, may store a method for dynamically encrypting and transmitting data based on a remote office platform provided in the present application. The electronic device 500 may also include a user interface 508. Of course, Figure 7 The architecture shown is only exemplary and can be omitted according to actual needs when implementing different devices. Figure 7 One or more components of an electronic device are shown.

[0031] Figure 8 Schematic diagram of a computer-readable storage medium structure provided by an embodiment of the present application. Figure 8 As shown, a computer-readable storage medium 600 according to an embodiment of the present application is shown. Computer-readable instructions are stored on the computer-readable storage medium 600. When the computer-readable instructions are executed by the processor, a method for dynamically encrypting and transmitting data based on a remote office platform according to an embodiment of the present application described with reference to the above figures can be executed. The storage medium 600 includes, but is not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory (cache), etc. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0032] In summary, the advantages of the present invention are: analyzing and learning based on the behavior of the remote office terminal when it is working normally, dynamically adjusting data encryption based on work behavior characteristics, and ensuring data security of the remote office platform.

[0033] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A data dynamic encryption transmission method based on a remote office platform, characterized in that: include: Obtain all remote office terminals connected to the remote office platform; Collect historical work behaviors of remote office terminals during normal working process and record them as sample work behaviors; Extracting behavior feature data based on the sample work behavior, recorded as sample work behavior feature data, wherein the behavior feature data at least includes access features and time features; Analyze and learn based on sample behavior feature data to obtain a normal working behavior feature relationship database of the remote office terminal; The behavior of the remote office terminal during the working process is obtained in real time and recorded as the real-time working behavior of the remote office terminal; Extracting several real-time working behavior features of remote office terminals based on the real-time working behavior of remote office terminals; Based on the real-time working behavior characteristics of remote office terminals, a behavioral risk identification algorithm is used to calculate reasonable indicators of real-time working behavior of remote office terminals; Determine the encryption level of data transmission from remote office terminals based on reasonable indicators of real-time working behavior of remote office terminals; According to the encryption level of data transmission of the remote office terminal, a data scrambling algorithm is used to generate encrypted data and transmit it to the remote office terminal.

2. According to claim 1, a method for dynamic data encryption transmission based on a remote office platform is characterized in that: The analysis and learning based on the sample behavior feature data to obtain the normal working behavior feature relationship database of the remote office terminal specifically includes: Divide a day into several analysis periods according to the set working hours; Based on the time characteristics of the sample work behavior, determine the analysis period corresponding to the sample work behavior; Count all sample work behaviors corresponding to each analysis period; Based on the access features of the sample work behavior corresponding to each analysis period, the feature correlation algorithm is used to calculate the correlation between the access features corresponding to each analysis period; The correlation between the sample work behavior corresponding to each analysis period and the access feature corresponding to each analysis period is encapsulated into a normal work behavior feature relationship database of the remote office terminal.

3. According to claim 2, a method for dynamic data encryption transmission based on a remote office platform is characterized in that: The feature correlation algorithm is specifically: The access characteristics of the sample work behavior corresponding to the analysis period are recorded as the access characteristics corresponding to the analysis period; All access features corresponding to the analysis period are combined into an access feature set A, A = {a1, ..., a i , …, a n }, where a i is the i-th access feature corresponding to the analysis period, and n is the total number of access features corresponding to the analysis period; Determine the occurrence of a during the analysis period i A number of sample work behaviors of compose a first sample work behavior set; Determine the occurrence of a during the analysis period j A number of sample work behaviors of compose a second sample work behavior set; Find the intersection of the first sample work behavior set and the second sample work behavior set to obtain a third sample work behavior set; Taking the union of the second sample work behavior set and the second sample work behavior set, to obtain a fourth sample work behavior set; Determining the number of elements in the first sample work behavior set, the number of elements in the second sample work behavior set, the number of elements in the third sample work behavior set, and the number of elements in the fourth sample work behavior set; Calculate a by using the correlation calculation formula i and a j The correlation between The correlation calculation formula is specifically: ； In the formula, for a i and a j The correlation between them, N0 is the total number of sample work behaviors corresponding to the analysis period, N1 is the number of elements in the first sample work behavior set, N2 is the number of elements in the second sample work behavior set, and N 1∩2 is the number of elements in the third sample work behavior set, N 1∪2 is the number of elements in the fourth sample work behavior set.

4. According to claim 3, a method for dynamic data encryption transmission based on a remote office platform is characterized in that: The behavior risk identification algorithm specifically includes: Based on the time characteristics in the real-time work behavior characteristics of the remote office terminal, determine the analysis period corresponding to the real-time work behavior of the remote office terminal, and record it as the real-time analysis period; Retrieve the normal working behavior characteristic relation database corresponding to the real-time analysis period; Combining multiple remote office terminal real-time access features in the remote office terminal real-time work behavior features into a plurality of remote office terminal real-time access feature groups; Retrieve the two remote office terminal real-time access features in each remote office terminal real-time access feature group in the normal working behavior feature relationship database, determine the correlation between the two remote office terminal real-time access features in the remote office terminal real-time access feature group, and use it as the rationality of the remote office terminal real-time access feature group; if the correlation between the two remote office terminal real-time access features in each remote office terminal real-time access feature group cannot be retrieved in the normal working behavior feature relationship database, assign a value of 0 to the rationality of the remote office terminal real-time access feature group; Based on the rationality calculation formula, the rationality of the real-time working behavior of the remote office terminal is calculated; The rationality calculation formula is specifically: ； Where H is the rationality of the real-time working behavior of the remote office terminal, K is the total number of real-time access feature groups of the remote office terminal, and X1 is the rationality of the real-time access feature group of the lth remote office terminal.

5. According to claim 4, a method for dynamic data encryption transmission based on a remote office platform is characterized in that: The determination of the encryption level of the remote office terminal data transmission based on the reasonable indicators of the real-time working behavior of the remote office terminal specifically includes: Determine the maximum level of scrambling encryption set by the remote office platform; Based on the rationality of the real-time working behavior of the remote office terminal and the maximum level of scrambling encryption, the level indicator of the remote office terminal data transmission is determined through a level determination formula; Based on the upward rounding of the level index of the remote office terminal data transmission, the encryption level of the remote office terminal data transmission is obtained; The level determination formula is specifically: ； Where L' is the level index of remote office terminal data transmission, L max The maximum level of encryption for scrambling.

6. A method for dynamic data encryption transmission based on a remote office platform according to claim 5, characterized in that: The step of using a data scrambling algorithm to generate encrypted data and transmit it to the remote office terminal according to the encryption level of the data transmitted by the remote office terminal specifically includes: The encryption level of remote office terminal data transmission is L; Convert the remote office terminal data to be transmitted into binary data, and extract L from the binary data in order from front to back. 2 characters, recorded as a characteristic character segment, if the number of remaining characters is less than L 2 , then add 0 to the last remaining character until the number of characters reaches L 2 ; Determine the total number of extracted characteristic character segments, recorded as M, and add a number between 1 and M to each characteristic character segment in sequence according to the order of the characteristic character segments in the binary data; Randomly sort the integers between 1 and M to obtain the initial scrambled key; According to the order of the integers between 1 and M in the initial scrambling key, the corresponding characteristic character segments are sorted in turn to obtain the initial scrambling data; A square scrambling algorithm is used to encrypt each characteristic character segment in the initial scrambled data to obtain encrypted data.

7. A method for dynamic data encryption transmission based on a remote office platform according to claim 6, characterized in that: The position scrambling algorithm is specifically as follows: Generate an L×L grid and replace 1-L 2 Randomly fill in the L×L square with positive integers; Numbered according to the sequence of characters in the characteristic character segment, 1-L 2 The characters in the feature character segment are filled in the positions of the positive integers in the L×L square; Characters are extracted from the L×L square in order from left to right and from top to bottom to obtain the positionally encrypted character segment of the characteristic character segment.

8. A data dynamic encryption transmission system based on a remote office platform, characterized in that: The method for dynamically encrypting and transmitting data based on a remote office platform according to any one of claims 1 to 7 comprises: A log module, which is used to obtain all remote office terminals connected to the remote office platform and collect historical work behaviors of the remote office terminals during normal work, which are recorded as sample work behaviors; A behavior analysis module, the behavior analysis module is electrically connected to the log module, the behavior analysis module is used to extract behavior feature data based on the sample work behavior, recorded as sample work behavior feature data, the behavior feature data at least includes access features and time features, and analyzes and studies the sample behavior feature data to obtain a normal work behavior feature relationship database of the remote office terminal; A work behavior monitoring module, the work behavior monitoring module is electrically connected to the behavior analysis module, the work behavior monitoring unit is used to obtain the behavior of the remote office terminal in the working process in real time, recorded as the real-time work behavior of the remote office terminal, and extract a number of real-time work behavior characteristics of the remote office terminal based on the real-time work behavior of the remote office terminal, and based on the real-time work behavior characteristics of the remote office terminal, a behavior risk identification algorithm is used to calculate a reasonable index of the real-time work behavior of the remote office terminal; An encryption module is electrically connected to the work behavior monitoring module, and is used to determine the encryption level of data transmission of the remote office terminal based on reasonable indicators of the real-time work behavior of the remote office terminal, and to generate encrypted data and transmit it to the remote office terminal using a data scrambling algorithm according to the encryption level of data transmission of the remote office terminal.

9. An electronic device, characterized in that: include: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a data dynamic encryption transmission method based on a remote office platform as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, a method for dynamic encryption transmission of data based on a remote office platform as described in any one of claims 1 to 7 is implemented.

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