Communication equipment data transmission security management system and method

Abstract

The present invention discloses a communication equipment data transmission security management system and method, which relates to the technical field of communication equipment data transmission, in order to solve the problem that the communication equipment cannot effectively monitor the transmission data for security when performing data transmission. The present invention can more accurately describe the nature and severity of the abnormality by subdividing the abnormal data into different levels, which helps to more accurately identify potential security risks. Each level of abnormality corresponds to a different warning intensity. The operation time and SIM card status are monitored in real time through the device function management module, so that abnormal behavior can be discovered in time, and the accuracy of security management can be improved. Text data, image data and voice data are classified, and different types of data are separated and extracted to ensure that each data type is properly processed, avoiding the risk of reduced processing efficiency or data damage that may be caused by mixed storage.

Description

Technical Field

[0001] The present invention relates to the technical field of communication equipment data transmission, and in particular to a communication equipment data transmission security management system and method. Background Art

[0002] Communication equipment data transmission refers to the process of transmitting information from one place to another through communication equipment.

[0003] The Chinese patent with publication number CN112312413A discloses a status monitoring system for mobile communication equipment and a working method thereof, which is mainly used to monitor the communication channel between the mobile communication equipment and the base station through a channel status monitoring module; the channel status monitoring module analyzes the on-off status between the mobile communication equipment and the base station by obtaining the first time difference and the second time difference, which helps to quickly locate the cause of the communication failure and improve the work efficiency. Although the above patent solves the problem of abnormal data screening, the following problems still exist in actual operation:

[0004] 1. Abnormal data is not processed more safely and effectively, resulting in invalid abnormal data processing.

[0005] 2. There is no effective real-time monitoring of the functions and finances of the communication equipment itself, which leads to external intrusion into the equipment from the functions and financial expenditures of the equipment itself.

[0006] 3. No specific anomaly monitoring is performed based on the format of the transmitted data, resulting in the inability to detect abnormal data in a timely manner during data transmission. Summary of the invention

[0007] The purpose of the present invention is to provide a communication equipment data transmission security management system and method. By subdividing abnormal data into different levels, the nature and severity of the abnormality can be described more accurately, which helps to identify potential security risks more accurately. Each level of abnormality corresponds to a different warning intensity. The device function management module monitors the operation time and SIM card status in real time, so as to timely discover abnormal behavior, reduce delays and false alarms, and improve the accuracy of security management. Text data, image data and voice data are classified. By separating and extracting different types of data, it can be ensured that each data type is properly processed, avoiding the risk of reduced processing efficiency or data corruption that may be caused by mixed storage, and can solve the problems in the prior art.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] A communication equipment data transmission security management system, comprising:

[0010] Device data transmission unit, used for:

[0011] Receive the data acquired by the communication device, classify the received data according to the data type, and obtain the transmission data to be monitored after the classification is completed;

[0012] The receiving data abnormality monitoring unit is used to:

[0013] Perform abnormal monitoring on the transmission data to be monitored according to the type of data, mark the abnormal transmission data to be monitored that is abnormal, and mark the abnormally marked data as transmission data to be warned;

[0014] Device abnormality management unit, used to:

[0015] The communication equipment body is controlled in real time, and when an abnormality occurs during the control of the communication equipment body, the abnormal data is acquired in real time, and the abnormal data acquired in real time is marked as management data to be warned;

[0016] Abnormal data decision-making and early warning unit, used for:

[0017] The transmission data to be warned and the management data to be warned are processed according to the degree of abnormality respectively, and different intensities of warnings are issued for fundamentally different degrees of abnormality, and alarms are displayed according to the warnings.

[0018] Preferably, the management data to be warned is also used for:

[0019] The data acquired by the communication equipment includes text data, image data and voice data;

[0020] classifying the text data, the image data and the voice data according to the data types of the text data, the image data and the voice data;

[0021] After the text data, image data and voice data are classified, they are uniformly marked as transmission data to be monitored.

[0022] Preferably, the received data abnormality monitoring unit includes:

[0023] Classification data validation module, used to:

[0024] Extracting text data, image data and voice data from the transmission data to be monitored respectively;

[0025] According to the data structures of the text data, the image data and the voice data, the text data, the image data and the voice data are respectively stored;

[0026] Among them, the data format of the text data is the text format; the data format of the image data is the picture format; the data format of the voice data is the WAV format, the VOC format and the AU format.

[0027] Preferably, the received data abnormality monitoring unit further includes:

[0028] Abnormal data confirmation module, used for:

[0029] According to the data structure of text data, image data and voice data, different data formats are respectively subjected to different methods of abnormality detection;

[0030] The text data uses natural speech processing technology to screen for abnormal sensitive words, where sensitive words are retrieved from the database;

[0031] The abnormal words in the text data are compared with the sensitive words in the database through natural speech processing technology, the number of abnormal words in the text data is determined according to the comparison result, and the position of each abnormal word is marked, and finally the first abnormal data is obtained;

[0032] The image data is first subjected to image preprocessing, wherein the image preprocessing is to perform image denoising, image enhancement, and image registration on the image data in sequence, and the image data after image preprocessing is subjected to sensitive image processing through deep learning technology, wherein the image data is first divided into a number of sub-images of the same size, and then each sub-image is compared with a sensitive image, wherein the sensitive image is obtained from a database, and whether the sub-image is an abnormal image is determined according to the overlap rate between the sub-image and the sensitive image, and finally the image data of the abnormal image is marked as the second abnormal data;

[0033] The speech data is converted into text language through speech recognition, the text language is processed in the same way as the text data, abnormal data in the text language is obtained, and finally the third abnormal data is obtained;

[0034] The first abnormal data, the second abnormal data and the third abnormal data are marked as data to be transmitted for warning.

[0035] Preferably, the received data abnormality monitoring unit further includes:

[0036] A first abnormal data volume extraction module, used to extract the data volume corresponding to the first abnormal data;

[0037] A second abnormal data volume extraction module, used to extract the data volume corresponding to the second abnormal data;

[0038] The abnormal data coefficient is obtained by using the data amount corresponding to the first abnormal data and the data amount corresponding to the second abnormal data; wherein the abnormal data coefficient is obtained by the following formula:

[0039]

[0040] Among them, λ represents the abnormal data coefficient; C w and C t Respectively represent the data volume corresponding to the text data and the data volume corresponding to the image data; C wy and C ty C represents the data volume corresponding to the first abnormal data and the data volume corresponding to the second abnormal data respectively; z Indicates the total amount of text data, image data and voice data;

[0041] An abnormal data evaluation parameter acquisition module, used to obtain an abnormal data evaluation parameter by using the abnormal data coefficient in combination with the data amount corresponding to the third abnormal data;

[0042] The data anomaly initial warning module is used to issue an initial data anomaly warning when the abnormal data evaluation parameter exceeds a preset parameter threshold.

[0043] Preferably, the abnormal data evaluation parameter acquisition module includes:

[0044] A third abnormal data volume extraction module, used to extract the data volume corresponding to the third abnormal data;

[0045] An abnormal data coefficient extraction module, used for extracting abnormal data coefficients;

[0046] An abnormal data evaluation parameter calculation module, used to obtain an abnormal data evaluation parameter by using the data volume and abnormal data coefficient corresponding to the third abnormal data;

[0047] The abnormal data evaluation parameter is obtained by the following formula:

[0048]

[0049] Among them, Q represents the abnormal data evaluation parameter; λ represents the abnormal data coefficient; C s Indicates the amount of data corresponding to the voice data; C sy Indicates the data volume corresponding to the third abnormal data.

[0050] Preferably, the device abnormality management unit includes:

[0051] Device function management module, used for:

[0052] When the communication equipment is operated, the operation time and operation area are monitored in real time, and whether the communication equipment is within the normal use time range is determined based on the real-time monitored operation time, and whether the operation area of ​​the communication equipment is within the specified range is determined based on the GPS positioning, and the communication equipment that is not within the normal use range and is not within the operation area is marked as the fourth abnormal data;

[0053] Monitor the SIM card status of the communication device in real time and mark the fifth abnormal data when the SIM card is replaced.

[0054] Preferably, the device abnormality management unit further includes:

[0055] Equipment security management module, used for:

[0056] Monitor each financial data in the communication device in real time, including WeChat finance, QQ finance, and mobile banking finance;

[0057] A threshold value for the amount of financial expenditure is set. When the amount of financial expenditure exceeds the preset threshold value, the financial expenditure data is marked as sixth abnormal data.

[0058] The fourth abnormal data, the fifth abnormal data and the sixth abnormal data are marked as management data to be warned.

[0059] Preferably, the abnormal data decision warning unit is also used for:

[0060] Process the transmission data to be warned and the management data to be warned according to the degree of abnormality respectively;

[0061] Confirming the number of abnormal words in the first abnormal data in the data to be transmitted for early warning, and corresponding the first abnormal data to first-level abnormal words, second-level abnormal words, and third-level abnormal words according to the total number of abnormal words;

[0062] Confirm the percentage of the overlap rate between the sub-image and the sensitive image in the second abnormal data in the transmission data to be warned, and correspond the second abnormal data to the first-level abnormal image, the second-level abnormal image and the third-level abnormal image according to the percentage;

[0063] Confirming the number of abnormal words in the third abnormal data in the data to be transmitted for early warning, and corresponding the third abnormal data to the first-level abnormal voice, the second-level abnormal voice and the third-level abnormal voice according to the total number of abnormal words;

[0064] Confirm the real-time usage duration of the fourth abnormal data in the management data to be warned, and correspond the fourth abnormal data to the first-level abnormal duration, the second-level abnormal duration, and the third-level abnormal duration according to the real-time usage duration;

[0065] Confirming the SIM card replacement status of the fifth abnormal data in the management data to be warned, and corresponding the fifth abnormal data to the first abnormal state, the second abnormal state and the third abnormal state according to the SIM card replacement status;

[0066] Confirm the financial expenditure data of the sixth abnormal data in the management data to be warned, and correspond the sixth abnormal data to the first-level abnormal finance, the second-level abnormal finance and the third-level abnormal finance according to the financial expenditure data;

[0067] Each level of abnormal prompt corresponds to a different warning intensity, among which, level 1 abnormality corresponds to level 1 warning, level 2 abnormality corresponds to level 2 warning, and level 3 abnormality corresponds to level 3 warning;

[0068] Different warning intensities correspond to different processing decisions.

[0069] The present invention provides another technical solution, a method for secure management of data transmission of communication equipment, comprising the following steps:

[0070] Step 1: First, the text data, image data and voice data transmitted by the communication device are obtained respectively through the device data transmission unit;

[0071] Step 2: The received data anomaly monitoring unit performs anomaly processing on the text data, image data and voice data obtained by the communication device, and extracts the abnormal data in each data:

[0072] Step 3: Manage the communication device body securely through the device abnormality management unit and extract the abnormal state of the communication device body;

[0073] Step 4: The abnormal data acquired by the communication equipment and the abnormal state of the communication equipment body are classified into abnormal levels through the abnormal data decision warning unit, and warnings of different degrees and methods are issued according to different levels.

[0074] Compared with the prior art, the present invention has the following beneficial effects:

[0075] 1. Classify text data, image data, and voice data. By separating and extracting different types of data, we can ensure that each data type is properly processed, avoiding the risk of reduced processing efficiency or data corruption that may be caused by mixed storage. Different anomaly detection methods are used according to the specific data structure of each data type. This targeted processing method can more effectively identify anomalies in various types of data, improving the accuracy and efficiency of anomaly detection.

[0076] 2. Real-time monitoring of operation time and SIM card status through the device function management module can timely detect abnormal behavior, reduce delays and false alarms, and improve the accuracy of security management. By monitoring the operation time, it can be identified whether the communication equipment exceeds the normal usage time range, which may mean that the equipment is abused or subjected to unauthorized access. The device security management module monitors sensitive financial data such as WeChat finance, QQ finance, and mobile banking finance in real time to ensure the safety of funds and avoid financial losses. At the same time, setting a threshold for the amount of financial expenditure can trigger an early warning in time when it exceeds the preset limit to reduce potential risks.

[0077] 3. By subdividing abnormal data into different levels, the nature and severity of the abnormality can be described more accurately, which helps to identify potential security risks more accurately. Each level of abnormality corresponds to a different warning intensity. When abnormal data with an abnormal level of level 1 and a warning level of level 1 is detected in the data to be transmitted for warning, it is uploaded to the supervision system in a timely manner. The supervision system is supervised by the emergency contacts stored in the communication device. The emergency contacts can remotely control the deletion of illegal files on the mobile phone, thereby improving the management effect of the communication equipment and enhancing the security of the communication equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 This is a schematic diagram of the principle of the data transmission module of the present invention;

[0079] Figure 2 It is a flow chart of the data transmission method of the present invention. DETAILED DESCRIPTION

[0080] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0081] In order to solve the problem in the prior art that when communication equipment transmits data, it does not perform specific abnormal monitoring according to the format of the transmitted data, resulting in the inability to timely detect abnormal data during data transmission, please refer to Figure 1 and Figure 2 , this embodiment provides the following technical solutions:

[0082] A communication equipment data transmission security management system, comprising:

[0083] Device data transmission unit, used for:

[0084] Receive the data acquired by the communication device, classify the received data according to the data type, and obtain the transmission data to be monitored after the classification is completed;

[0085] The receiving data abnormality monitoring unit is used to:

[0086] Perform abnormal monitoring on the transmission data to be monitored according to the type of data, mark the abnormal transmission data to be monitored that is abnormal, and mark the abnormally marked data as transmission data to be warned;

[0087] Device abnormality management unit, used to:

[0088] The communication equipment body is controlled in real time, and when an abnormality occurs during the control of the communication equipment body, the abnormal data is acquired in real time, and the abnormal data acquired in real time is marked as management data to be warned;

[0089] Abnormal data decision-making and early warning unit, used for:

[0090] The transmission data to be warned and the management data to be warned are processed according to the degree of abnormality respectively, and different intensities of warnings are issued for fundamentally different degrees of abnormality, and alarms are displayed according to the warnings.

[0091] Specifically, by receiving data anomaly monitoring units, it can ensure that each data type is properly processed, avoiding the risk of reduced processing efficiency or data corruption that may be caused by mixed storage. By real-time monitoring of operation time and SIM card status by the device anomaly management unit, abnormal behavior can be discovered in time, delays and false alarms can be reduced, and the accuracy of security management can be improved. Abnormal data can be classified and marked by the abnormal data decision-making and early warning unit. This solution simplifies the exception handling process and improves management efficiency.

[0092] The data for early warning management is also used for:

[0093] The data acquired by the communication equipment includes text data, image data and voice data;

[0094] classifying the text data, the image data and the voice data according to the data types of the text data, the image data and the voice data;

[0095] After the text data, image data and voice data are classified, they are uniformly marked as transmission data to be monitored.

[0096] Specifically, all data are uniformly marked as monitored transmission data to facilitate unified management and monitoring, ensuring that data transmission and processing comply with regulations and safety standards. By classifying and labeling different types of data, data transmission and monitoring can be carried out more effectively, reducing unnecessary data processing and analysis time. Classifying text data, image data and voice data and uniformly labeling them as monitored transmission data will help improve the efficiency, security and flexibility of data transmission and processing.

[0097] The receiving data abnormality monitoring unit includes:

[0098] Classification data validation module, used to:

[0099] Extracting text data, image data and voice data from the transmission data to be monitored respectively;

[0100] According to the data structures of the text data, the image data and the voice data, the text data, the image data and the voice data are respectively stored;

[0101] Among them, the data format of the text data is the text format; the data format of the image data is the picture format; the data format of the voice data is the WAV format, the VOC format and the AU format.

[0102] Abnormal data confirmation module, used for:

[0103] According to the data structure of text data, image data and voice data, different data formats are respectively subjected to different methods of abnormality detection;

[0104] The text data uses natural speech processing technology to screen for abnormal sensitive words, where sensitive words are retrieved from the database;

[0105] The abnormal words in the text data are compared with the sensitive words in the database through natural speech processing technology, the number of abnormal words in the text data is determined according to the comparison result, and the position of each abnormal word is marked, and finally the first abnormal data is obtained;

[0106] The image data is first subjected to image preprocessing, wherein the image preprocessing is to perform image denoising, image enhancement, and image registration on the image data in sequence, and the image data after image preprocessing is subjected to sensitive image processing through deep learning technology, wherein the image data is first divided into a number of sub-images of the same size, and then each sub-image is compared with a sensitive image, wherein the sensitive image is obtained from a database, and whether the sub-image is an abnormal image is determined according to the overlap rate between the sub-image and the sensitive image, and finally the image data of the abnormal image is marked as the second abnormal data;

[0107] The speech data is converted into text language through speech recognition, the text language is processed in the same way as the text data, abnormal data in the text language is obtained, and finally the third abnormal data is obtained;

[0108] The first abnormal data, the second abnormal data and the third abnormal data are marked as data to be transmitted for warning.

[0109] Specifically, the text data, image data and voice data are first classified through the classification data confirmation module. By separating and extracting different types of data, it can be ensured that each data type is properly processed, avoiding the risk of reduced processing efficiency or data damage that may be caused by mixed storage. The storage is performed in a suitable data format, which can more effectively utilize the storage space and avoid unnecessary waste of resources. Then, the classified data is extracted separately through the abnormal data confirmation module. Different abnormality detection methods are used according to the specific data structure of each data type. This targeted processing method can more effectively identify abnormalities in various types of data, improve the accuracy and efficiency of abnormality detection. For text data, natural language processing technology is used to screen sensitive words for abnormalities, which can accurately identify text containing sensitive information and mark and process them in time. In the processing of image data, image preprocessing and deep learning technology are used. Through preprocessing steps such as denoising, enhancement, and registration, the quality of the image can be improved, laying a good foundation for subsequent abnormality detection. The use of deep learning technology can more accurately identify sensitive content in the image, improve the accuracy of abnormality detection, and after converting the voice data into text language, it is processed in the same way as the text data, realizing abnormality detection of voice data.

[0110] Specifically, the received data abnormality monitoring unit further includes:

[0111] A first abnormal data volume extraction module, used to extract the data volume corresponding to the first abnormal data;

[0112] A second abnormal data volume extraction module, used to extract the data volume corresponding to the second abnormal data;

[0113] The abnormal data coefficient is obtained by using the data amount corresponding to the first abnormal data and the data amount corresponding to the second abnormal data; wherein the abnormal data coefficient is obtained by the following formula:

[0114]

[0115] Among them, λ represents the abnormal data coefficient; C w and C t Respectively represent the data volume corresponding to the text data and the data volume corresponding to the image data; C wy and C tyC represents the data volume corresponding to the first abnormal data and the data volume corresponding to the second abnormal data respectively; z Indicates the total amount of text data, image data and voice data;

[0116] An abnormal data evaluation parameter acquisition module, used to obtain an abnormal data evaluation parameter by using the abnormal data coefficient in combination with the data amount corresponding to the third abnormal data;

[0117] The data anomaly initial warning module is used to issue an initial data anomaly warning when the abnormal data evaluation parameter exceeds a preset parameter threshold.

[0118] The technical effect of the above technical solution is: by setting up a first abnormal data volume extraction module and a second abnormal data volume extraction module, the technical solution can extract the data volume corresponding to different types of abnormal data respectively. This refined extraction helps to more accurately identify and analyze data anomalies. Through the calculation of the abnormal data coefficient (λ), the technical solution can dynamically evaluate the severity of abnormal data based on the data volume (Cwy and Cty) of different types of abnormal data, and the sum of the data volume (Cz) of text data, image data and voice data. This evaluation method can more accurately reflect the actual situation of data anomalies. The abnormal data evaluation parameter acquisition module can combine the data volume corresponding to the third abnormal data and use the abnormal data coefficient to obtain a comprehensive abnormal data evaluation parameter. This parameter can comprehensively consider multiple types of abnormal data and provide a more comprehensive basis for subsequent early warning and processing. The data anomaly initial warning module can issue a data anomaly initial warning in time when the abnormal data evaluation parameter exceeds the preset parameter threshold. This timely warning helps to timely discover and handle data anomalies and avoid possible losses. Although the technical solution mainly mentions text data, image data and voice data, the designed framework and algorithm are scalable and can adapt to more types of data and more complex scenarios. At the same time, by adjusting the parameter threshold, the technical solution can also flexibly adapt to different application requirements.

[0119] In summary, this technical solution improves the accuracy and efficiency of data anomaly monitoring through refined anomaly monitoring, dynamic assessment of anomaly degree, comprehensive evaluation of abnormal data, and timely warning, providing effective protection for data security and reliability.

[0120] Specifically, the abnormal data evaluation parameter acquisition module includes:

[0121] A third abnormal data volume extraction module, used to extract the data volume corresponding to the third abnormal data;

[0122] An abnormal data coefficient extraction module, used for extracting abnormal data coefficients;

[0123] An abnormal data evaluation parameter calculation module, used to obtain an abnormal data evaluation parameter by using the data volume and abnormal data coefficient corresponding to the third abnormal data;

[0124] The abnormal data evaluation parameter is obtained by the following formula:

[0125]

[0126] Among them, Q represents the abnormal data evaluation parameter; λ represents the abnormal data coefficient; C s Indicates the amount of data corresponding to the voice data; C sy Indicates the data volume corresponding to the third abnormal data.

[0127] The technical effect of the above technical solution is that the module not only considers the abnormal data volume of text data and image data, but also specially increases the consideration of the abnormal volume of voice data. This design makes the abnormal data evaluation more comprehensive and can cover abnormal situations of multiple data types. The abnormal data coefficient extraction module is used to extract the abnormal data coefficient λ calculated previously, which dynamically evaluates the severity of the abnormal data based on the data volume of different types of abnormal data. The abnormal data evaluation parameter calculation module uses this coefficient, combined with the data volume corresponding to the third abnormal data, to more accurately evaluate the comprehensive impact of the current abnormal data. Through the calculation formula of the abnormal data evaluation parameter Q, the module can quantify the impact of the current abnormal data. The higher the Q value, the greater the impact of the abnormal data, which has important guiding significance for the subsequent early warning and processing strategy formulation. The design of the entire module is flexible and can be extended to abnormal evaluation of other data types according to actual needs. In addition, by adjusting the calculation method of the abnormal data coefficient and the calculation formula of the abnormal data evaluation parameter, it can adapt to the abnormal data evaluation requirements in different application scenarios. The abnormal data evaluation parameter can be used as an important basis for subsequent decision-making. For example, when the Q value exceeds the preset threshold, a data abnormality warning can be triggered or corresponding processing measures can be taken to ensure the accuracy of the data and the normal operation of the system.

[0128] In summary, this technical solution improves the accuracy and effectiveness of abnormal data evaluation by comprehensively considering the types of abnormal data, effectively utilizing abnormal data coefficients, quantifying the impact of abnormal data, and providing decision support, providing a strong guarantee for the security and reliability of data.

[0129] In order to solve the problem in the prior art that the functions and finances of the communication equipment are not effectively monitored in real time, which leads to external intrusion into the equipment from the functions and financial expenditures of the equipment, please refer to Figure 1 and Figure 2 , this embodiment provides the following technical solutions:

[0130] Device abnormality management unit, including:

[0131] Device function management module, used for:

[0132] When the communication equipment is operated, the operation time and operation area are monitored in real time, and whether the communication equipment is within the normal use time range is determined based on the real-time monitored operation time, and whether the operation area of ​​the communication equipment is within the specified range is determined based on the GPS positioning, and the communication equipment that is not within the normal use range and is not within the operation area is marked as the fourth abnormal data;

[0133] Monitor the SIM card status of the communication device in real time and mark the fifth abnormal data when the SIM card is replaced.

[0134] Equipment security management module, used for:

[0135] Monitor each financial data in the communication device in real time, including WeChat finance, QQ finance, and mobile banking finance;

[0136] A threshold value for the amount of financial expenditure is set. When the amount of financial expenditure exceeds the preset threshold value, the financial expenditure data is marked as sixth abnormal data.

[0137] The fourth abnormal data, the fifth abnormal data and the sixth abnormal data are marked as management data to be warned.

[0138] Specifically, by monitoring the operation time and SIM card status in real time through the device function management module, abnormal behavior can be discovered in time, delays and false alarms can be reduced, and the accuracy of security management can be improved. By monitoring the operation time, it can be identified whether the communication equipment exceeds the normal usage time range, which may mean that the equipment is abused or subjected to unauthorized access. Real-time monitoring of the SIM card status can detect the replacement of the SIM card in time, which is essential to prevent the communication equipment from being illegally taken over or used for fraudulent activities. In addition, the software is bound to the mobile phone, and each mobile phone has a unique serial number. Through the device security management module, sensitive financial data such as WeChat finance, QQ finance, and mobile banking finance can be monitored in real time to ensure the safety of funds and avoid financial losses. At the same time, setting a threshold for the amount of financial expenditure can trigger an early warning in time when it exceeds the preset limit to reduce potential risks. Through real-time monitoring and abnormal annotation, the solution can help organizations adopt preventive security strategies, identify potential security risks in advance, and take corresponding measures to prevent and respond.

[0139] In order to solve the problem in the prior art that when abnormal data is detected in the communication device, the abnormal data is not processed more safely and effectively, resulting in invalid abnormal data processing, please refer to Figure 1 and Figure 2, this embodiment provides the following technical solutions:

[0140] The abnormal data decision-making and early warning unit is also used to:

[0141] Process the transmission data to be warned and the management data to be warned according to the degree of abnormality respectively;

[0142] Confirming the number of abnormal words in the first abnormal data in the data to be transmitted for early warning, and corresponding the first abnormal data to first-level abnormal words, second-level abnormal words, and third-level abnormal words according to the total number of abnormal words;

[0143] Confirm the percentage of the overlap rate between the sub-image and the sensitive image in the second abnormal data in the transmission data to be warned, and correspond the second abnormal data to the first-level abnormal image, the second-level abnormal image and the third-level abnormal image according to the percentage;

[0144] Confirming the number of abnormal words in the third abnormal data in the data to be transmitted for early warning, and corresponding the third abnormal data to the first-level abnormal voice, the second-level abnormal voice and the third-level abnormal voice according to the total number of abnormal words;

[0145] Confirm the real-time usage duration of the fourth abnormal data in the management data to be warned, and correspond the fourth abnormal data to the first-level abnormal duration, the second-level abnormal duration, and the third-level abnormal duration according to the real-time usage duration;

[0146] Confirming the SIM card replacement status of the fifth abnormal data in the management data to be warned, and corresponding the fifth abnormal data to the first abnormal state, the second abnormal state and the third abnormal state according to the SIM card replacement status;

[0147] Confirm the financial expenditure data of the sixth abnormal data in the management data to be warned, and correspond the sixth abnormal data to the first-level abnormal finance, the second-level abnormal finance and the third-level abnormal finance according to the financial expenditure data;

[0148] Each level of abnormal prompt corresponds to a different warning intensity, among which, level 1 abnormality corresponds to level 1 warning, level 2 abnormality corresponds to level 2 warning, and level 3 abnormality corresponds to level 3 warning;

[0149] Different warning intensities correspond to different processing decisions.

[0150] Specifically, by subdividing abnormal data into different levels, the nature and severity of the abnormality can be described more accurately, which helps to identify potential security risks more accurately. Each level of abnormality corresponds to a different warning intensity. This differentiated warning mechanism enables organizations to take corresponding measures according to different security risk levels, thereby improving the pertinence and effectiveness of the warning. By classifying and marking abnormal data, the solution simplifies the exception handling process and improves management efficiency. This helps organizations respond to and handle security issues more quickly and reduce potential security risks. Among them, level one anomalies and level one warnings are the highest level of anomalies and warnings, followed by level two anomalies and level two warnings, and level three anomalies and level three levels are the lowest level of anomalies and warnings. When the usage time and operation area of ​​the communication device are not within the specified range, the alarm notification will be sent directly to the communication device body. If the usage time and operation area are not within the specified range at level one, the alarm notification will be sent directly to the emergency contact stored in the communication device. When the SIM card is replaced, the communication device’s own security verification will be performed, and the abnormality level will be determined based on the number of errors in the verification. When the abnormality level is the highest, the replaced SIM card will be automatically blocked from any operation. When abnormal data with a level one anomaly and a level one warning degree is detected in the transmission data to be warned, it will be uploaded to the supervision system in a timely manner. The supervision system is supervised by the emergency contacts stored in the communication device. The emergency contacts can remotely control and delete illegal files on the mobile phone, thereby improving the management effect of the communication equipment and enhancing the security of the communication equipment.

[0151] A method for secure management of data transmission of communication equipment comprises the following steps:

[0152] Step 1: First, the text data, image data and voice data transmitted by the communication device are obtained respectively through the device data transmission unit;

[0153] Among them, classifying and labeling different types of data can make data transmission and monitoring more efficient and reduce unnecessary data processing and analysis time;

[0154] Step 2: The received data abnormality monitoring unit performs abnormal processing on the text data, image data and voice data obtained by the communication device, and extracts the abnormal data in each data;

[0155] Among them, text data, image data and voice data are classified, and by separating and extracting different types of data, it can be ensured that each data type is properly processed;

[0156] Step 3: Manage the communication device body securely through the device abnormality management unit and extract the abnormal state of the communication device body;

[0157] Among them, real-time monitoring of operation time and SIM card status can promptly detect abnormal behavior, reduce delays and false alarms, and improve the accuracy of security management;

[0158] Step 4: The abnormal data acquired by the communication device and the abnormal state of the communication device are classified into abnormal levels through the abnormal data decision warning unit, and different degrees and different methods of warning are issued according to different levels;

[0159] Among them, subdividing abnormal data into different levels can more accurately describe the nature and severity of the abnormalities, and help to more accurately identify potential security risks.

[0160] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0161] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A communication equipment data transmission security management system, characterized in that: include: Device data transmission unit, used for: Receive the data acquired by the communication device, classify the received data according to the data type, and obtain the transmission data to be monitored after the classification is completed; The receiving data abnormality monitoring unit is used to: Perform abnormal monitoring on the transmission data to be monitored according to the type of data, mark the abnormal transmission data to be monitored that is abnormal, and mark the abnormally marked data as transmission data to be warned; Device abnormality management unit, used to: The communication equipment body is controlled in real time, and when an abnormality occurs during the control of the communication equipment body, the abnormal data is acquired in real time, and the abnormal data acquired in real time is marked as management data to be warned; Abnormal data decision-making and early warning unit, used for: The transmission data to be warned and the management data to be warned are processed according to the abnormality degree respectively, and different abnormality degrees are used to give different intensity warnings, and alarms are displayed according to the warnings; The received data abnormality monitoring unit comprises: Classification data validation module, used to: Extracting text data, image data and voice data from the transmission data to be monitored respectively; According to the data structures of the text data, the image data and the voice data, the text data, the image data and the voice data are respectively stored; Among them, the data format of the text data is text format; the data format of the image data is picture format; the data format of the voice data is WAV format, VOC format and AU format; The received data abnormality monitoring unit further includes: Abnormal data confirmation module, used for: According to the data structure of text data, image data and voice data, different data formats are respectively subjected to different methods of abnormality detection; The text data uses natural speech processing technology to screen for abnormal sensitive words, where sensitive words are retrieved from the database; The abnormal words in the text data are compared with the sensitive words in the database through natural speech processing technology, the number of abnormal words in the text data is determined according to the comparison result, and the position of each abnormal word is marked, and finally the first abnormal data is obtained; The image data is first subjected to image preprocessing, wherein the image preprocessing is to perform image denoising, image enhancement, and image registration on the image data in sequence, and the image data after image preprocessing is subjected to sensitive image processing through deep learning technology, wherein the image data is first divided into a number of sub-images of the same size, and then each sub-image is compared with a sensitive image, wherein the sensitive image is obtained from a database, and whether the sub-image is an abnormal image is determined according to the overlap rate between the sub-image and the sensitive image, and finally the image data of the abnormal image is marked as the second abnormal data; The speech data is converted into text language through speech recognition, the text language is processed in the same way as the text data, abnormal data in the text language is obtained, and finally the third abnormal data is obtained; and marking the first abnormal data, the second abnormal data and the third abnormal data as data to be transmitted for early warning; The device abnormality management unit includes: Device function management module, used for: When the communication equipment is operated, the operation time and operation area are monitored in real time, and whether the communication equipment is within the normal use time range is determined based on the real-time monitored operation time, and whether the operation area of ​​the communication equipment is within the specified range is determined based on the GPS positioning, and the communication equipment that is not within the normal use range and is not within the operation area is marked as the fourth abnormal data; Monitor the SIM card status of the communication device in real time and mark the abnormal data when the SIM card is replaced; The device abnormality management unit further includes: Equipment security management module, used for: Monitor each financial data in the communication device in real time, including WeChat finance, QQ finance, and mobile banking finance; A threshold value for the amount of financial expenditure is set. When the amount of financial expenditure exceeds the preset threshold value, the financial expenditure data is marked as sixth abnormal data. and marking the fourth abnormal data, the fifth abnormal data and the sixth abnormal data as data to be managed for early warning; The abnormal data decision warning unit is also used for: Process the transmission data to be warned and the management data to be warned according to the degree of abnormality respectively; Confirming the number of abnormal words in the first abnormal data in the data to be transmitted for early warning, and corresponding the first abnormal data to first-level abnormal words, second-level abnormal words, and third-level abnormal words according to the total number of abnormal words; Confirm the percentage of the overlap rate between the sub-image and the sensitive image in the second abnormal data in the transmission data to be warned, and correspond the second abnormal data to the first-level abnormal image, the second-level abnormal image and the third-level abnormal image according to the percentage; Confirming the number of abnormal words in the third abnormal data in the data to be transmitted for early warning, and corresponding the third abnormal data to the first-level abnormal voice, the second-level abnormal voice and the third-level abnormal voice according to the total number of abnormal words; Confirm the real-time usage duration of the fourth abnormal data in the management data to be warned, and correspond the fourth abnormal data to the first-level abnormal duration, the second-level abnormal duration, and the third-level abnormal duration according to the real-time usage duration; Confirming the SIM card replacement status of the fifth abnormal data in the management data to be warned, and corresponding the fifth abnormal data to the first abnormal state, the second abnormal state and the third abnormal state according to the SIM card replacement status; Confirm the financial expenditure data of the sixth abnormal data in the management data to be warned, and correspond the sixth abnormal data to the first-level abnormal finance, the second-level abnormal finance and the third-level abnormal finance according to the financial expenditure data; Each level of abnormal prompt corresponds to a different warning intensity, among which, level 1 abnormality corresponds to level 1 warning, level 2 abnormality corresponds to level 2 warning, and level 3 abnormality corresponds to level 3 warning; Different warning intensities correspond to different processing decisions.

2. A communication equipment data transmission security management system according to claim 1, characterized in that: The management data to be warned is also used for: The data acquired by the communication equipment includes text data, image data and voice data; classifying the text data, the image data and the voice data according to the data types of the text data, the image data and the voice data; After the text data, image data and voice data are classified, they are uniformly marked as transmission data to be monitored.

3. A communication equipment data transmission security management system according to claim 1, characterized in that: The received data abnormality monitoring unit further includes: A first abnormal data volume extraction module, used to extract the data volume corresponding to the first abnormal data; A second abnormal data volume extraction module, used to extract the data volume corresponding to the second abnormal data; The abnormal data coefficient is obtained by using the data amount corresponding to the first abnormal data and the data amount corresponding to the second abnormal data; wherein the abnormal data coefficient is obtained by the following formula: Among them, λ represents the abnormal data coefficient; C w and C t Respectively represent the data volume corresponding to the text data and the data volume corresponding to the image data; C wy and C ty C represents the data volume corresponding to the first abnormal data and the data volume corresponding to the second abnormal data respectively; z Indicates the total amount of text data, image data and voice data; An abnormal data evaluation parameter acquisition module, used to obtain an abnormal data evaluation parameter by using the abnormal data coefficient in combination with the data amount corresponding to the third abnormal data; The data anomaly initial warning module is used to issue an initial data anomaly warning when the abnormal data evaluation parameter exceeds a preset parameter threshold.

4. A communication equipment data transmission security management system according to claim 3, characterized in that: The abnormal data evaluation parameter acquisition module includes: A third abnormal data volume extraction module, used to extract the data volume corresponding to the third abnormal data; An abnormal data coefficient extraction module, used for extracting abnormal data coefficients; An abnormal data evaluation parameter calculation module, used to obtain an abnormal data evaluation parameter by using the data volume and abnormal data coefficient corresponding to the third abnormal data; The abnormal data evaluation parameter is obtained by the following formula: Among them, Q represents the abnormal data evaluation parameter; λ represents the abnormal data coefficient; C s Indicates the amount of data corresponding to the voice data; C sy Indicates the data volume corresponding to the third abnormal data.

5. A management method for a communication equipment data transmission security management system as claimed in claim 4, characterized in that: The following steps are involved: Step 1: First, the text data, image data and voice data transmitted by the communication device are obtained respectively through the device data transmission unit; Step 2: The received data anomaly monitoring unit performs anomaly processing on the text data, image data and voice data obtained by the communication device, and extracts the abnormal data in each data: Step 3: Manage the communication device body securely through the device abnormality management unit and extract the abnormal state of the communication device body; Step 4: The abnormal data acquired by the communication equipment and the abnormal state of the communication equipment body are classified into abnormal levels through the abnormal data decision warning unit, and warnings of different degrees and methods are issued according to different levels.

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