A control method, system, device and medium for mobile phone security and confidentiality device

Abstract

The present application relates to a control method, system, equipment and medium for a mobile phone security and confidentiality device, and belongs to the field of confidentiality and safety technology. Among them, the mobile phone security and confidentiality device includes a security box for sealing and placing the mobile phone, and the security box is also provided with an incoming call status detection module and an incoming call prompt module, and the incoming call status detection module is used to detect the incoming call status of the mobile phone and output an incoming call status detection signal; the control method includes: receiving the incoming call status detection signal sent by the incoming call status detection module; obtaining the incoming call request information of the mobile phone in response to the incoming call status detection signal; traversing the preset contact database, and determining the caller information based on the incoming call request information; based on the machine learning algorithm, predicting the importance priority of the incoming call request information according to the caller information; determining the corresponding incoming call prompt mode according to the importance priority of the incoming call request information; and controlling the incoming call prompt module to perform the incoming call prompt according to the incoming call prompt mode. The present application has the effect of improving the user experience.

Description

Technical Field

[0001] The present application relates to the field of confidentiality and security technology, and in particular to a control method, system, equipment and medium for a mobile phone security and confidentiality device. Background Art

[0002] In the current information age, smartphones have become an indispensable part of people's daily lives and work. However, as smartphones become increasingly powerful, their security risks are becoming increasingly prominent, especially in special confidential industries. For example, in highly sensitive fields such as military, government, and finance, how to ensure the security of information during meetings and prevent the leakage of sensitive information has become an urgent problem to be solved.

[0003] At present, in special confidentiality-related industries, facing confidentiality meetings or confidentiality-related workplaces in fixed locations, mobile phones are usually required to be centrally stored and managed, and fixed mobile phone safes are used to seal and isolate mobile phones to cut off signals and prevent illegal transmission and eavesdropping of information. However, when using mobile phone safes to seal mobile phones, users often worry about missing urgent or important calls, so they need to frequently open the safe to check their phones, resulting in a poor user experience. Summary of the invention

[0004] In order to improve user experience, the present application provides a control method, system, device and medium for a mobile phone security and confidentiality device.

[0005] In a first aspect, the present application provides a control method for a mobile phone security and confidentiality device, which adopts the following technical solution:

[0006] A control method for a mobile phone security and confidentiality device, the mobile phone security and confidentiality device comprising a security box for sealing and placing a mobile phone, the security box also being provided with an incoming call status detection module and an incoming call prompt module, the incoming call status detection module being used to detect the incoming call status of the mobile phone and output an incoming call status detection signal; the control method comprising:

[0007] Receiving an incoming call status detection signal sent by the incoming call status detection module;

[0008] acquiring incoming call request information of the mobile phone in response to the incoming call status detection signal;

[0009] Traversing a preset contact database, and determining caller information based on the incoming call request information;

[0010] Based on a machine learning algorithm, predict the importance priority of the incoming call request information according to the caller information;

[0011] Determine a corresponding incoming call prompt mode according to the importance priority of the incoming call request information;

[0012] The incoming call prompt module is controlled to perform an incoming call prompt according to the incoming call prompt mode.

[0013] By adopting the above technical solution, when the mobile phone is sealed and placed using the mobile phone security and confidentiality device, the priority of incoming calls can be intelligently judged. In specific environments (confidential meetings or confidential workplaces, etc.), users can intuitively perceive the importance of incoming calls through different prompt modes, reasonably arrange answering time, and improve work or life efficiency, so there is no need to frequently open the safe to check the incoming call status of the mobile phone, thereby improving the user experience.

[0014] Optionally, based on a machine learning algorithm, the step of determining the importance priority of the incoming call request information according to the caller information includes:

[0015] The caller information is input into a pre-trained priority prediction model to predict the importance priority of the incoming call request information; wherein the priority prediction model is pre-trained based on historical incoming call data and pre-marked important priority tags.

[0016] By adopting the above technical solution, a prediction model is trained that can accurately predict important priorities based on caller information. As the model continues to learn, the judgment of call priority will become more and more in line with the user's personal preferences and actual needs, thereby obtaining a more personalized service experience.

[0017] Optionally, the method further includes a step of training the priority prediction model, the step comprising:

[0018] Acquire a sample data set; wherein the sample data set includes the historical incoming call data and pre-marked important priority tags;

[0019] Performing data preprocessing on the sample data set and dividing it into a training set and a test set;

[0020] Inputting the historical incoming call data in the training set into a pre-built neural network model to obtain a first label result;

[0021] Comparing the first label result with the pre-labeled important priority label in the training set to obtain a first comparison result;

[0022] The neural network model is iterated according to the first comparison result, the model parameters are corrected, and the trained priority prediction model is obtained.

[0023] By adopting the above technical solution, the preprocessed training set data is input into the pre-built neural network model. The neural network automatically adjusts the internal weight parameters of the network by learning the relationship between the input data (call information) and the output data (important priority label) so that the model can capture complex nonlinear relationships and achieve the purpose of predicting call priority.

[0024] Optionally, after obtaining the trained priority prediction model, the method further includes:

[0025] Obtaining the historical incoming call data and pre-labeled important priority labels in the test set;

[0026] Inputting the historical incoming call data in the test set into the trained priority prediction model to obtain a second label result;

[0027] Comparing the second label result with the pre-labeled important priority label in the test set, obtaining a second comparison result;

[0028] According to the second comparison result, the performance index of the trained priority prediction model is evaluated and iterated until a preset number of iterations or a performance index threshold is reached to obtain the priority prediction model.

[0029] By adopting the above technical solution, an independent test set can be used to more accurately evaluate the performance of the model on unknown data, ensuring that the model can predict call priority with high accuracy in practical applications; by performing rigorous test set evaluation and iterative optimization on the trained model, the high performance and reliability of the priority prediction model in practical applications can be ensured, thereby improving user efficiency and satisfaction with call processing.

[0030] Optionally, after the step of determining a corresponding incoming call prompt mode according to the importance priority of the incoming call request information, the method further includes:

[0031] Determine whether the important priority is higher than a preset priority threshold, and if so, obtain the identity information of the current user in real time;

[0032] Perform security verification on the identity information based on a preset identity database and determine whether the verification is successful;

[0033] If the verification is successful, the incoming call prompt mode is maintained and the process proceeds to the next step; if the verification fails, the incoming call prompt mode is modified to a silent mode and the process proceeds to the next step.

[0034] By adopting the above technical solution, when there is an important or urgent call, the call reminder function is activated only when the user who has passed the identity verification is present, otherwise it remains silent to prevent unauthorized personnel from noticing the call information, thereby ensuring that only users who have passed the identity security verification can receive the call reminder, avoiding unauthorized personnel from accidentally contacting sensitive calls, and enhancing the protection of user privacy and security.

[0035] Optionally, after the step of controlling the incoming call prompt module to perform the incoming call prompt according to the incoming call prompt mode, the method further includes:

[0036] Determine whether there is any incoming call request information higher than a preset priority threshold that has not been processed after a preset time period;

[0037] If so, emergency handling information is generated according to the incoming call request information and sent to a preset emergency contact.

[0038] By adopting the above technical solution, unprocessed high-priority call requests are automatically converted into emergency processing information and sent to the preset emergency contact. This is suitable for situations where the user cannot answer the call but the call is very urgent, ensuring that the emergency information can be processed in time, thereby improving the efficiency and security of call management.

[0039] In a second aspect, the present application provides a control system for a mobile phone security and confidentiality device, which adopts the following technical solution:

[0040] A control system for a mobile phone security and confidentiality device, the mobile phone security and confidentiality device comprising a security box for sealing and placing a mobile phone, the security box also being provided with an incoming call status detection module and an incoming call prompt module, the incoming call status detection module being used to detect the incoming call status of the mobile phone and output an incoming call status detection signal; the control system comprising:

[0041] A receiving module, used for receiving an incoming call status detection signal sent by the incoming call status detection module;

[0042] An acquisition module, configured to acquire the incoming call request information of the mobile phone in response to the incoming call status detection signal;

[0043] A caller information determination module, used to traverse a preset contact database and determine the caller information based on the call request information;

[0044] An important priority prediction module, used for predicting the important priority of the incoming call request information according to the caller information based on a machine learning algorithm;

[0045] An incoming call prompt mode determination module, used to determine a corresponding incoming call prompt mode according to the importance priority of the incoming call request information;

[0046] The incoming call prompt control module controls the incoming call prompt module to perform incoming call prompt according to the incoming call prompt mode.

[0047] Optionally, the control system further includes:

[0048] A judgment module, used to judge whether the important priority is higher than a preset priority threshold, and if so, output a first judgment result;

[0049] An acquisition module, used for acquiring the identity information of the current user in real time in response to the first judgment result;

[0050] A security verification module is used to perform security verification on the identity information based on a preset identity database and determine whether the verification is successful; if so, output a verification success result; if not, output a verification failure result;

[0051] An incoming call prompt mode processing module, configured to maintain the incoming call prompt mode in response to the verification passing result;

[0052] The incoming call prompt mode processing module is also used to modify the incoming call prompt mode to a silent mode in response to the verification failure result.

[0053] In a third aspect, the present application provides a computer device, which adopts the following technical solution:

[0054] A computer device comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method as described in the first aspect.

[0055] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0056] A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any one of the methods in the first aspect.

[0057] To summarize, the present application includes at least one of the following beneficial technical effects: when using a mobile phone security and confidentiality device to seal and place a mobile phone, by intelligently judging the priority of incoming calls, in specific environments (confidential meetings or confidential workplaces, etc.), users can intuitively perceive the importance of incoming calls through different prompt modes, reasonably arrange answering time, and improve work or life efficiency, thereby eliminating the need to frequently open the safe to check the incoming call status of the mobile phone, thereby improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a side cross-sectional view of a mobile phone security and privacy device according to one embodiment of the present application.

[0059] Figure 2It is a top view of a mobile phone security and privacy device according to one embodiment of the present application.

[0060] Figure 3 It is a first flow chart of a control method of a mobile phone security and privacy device according to one embodiment of the present application.

[0061] Figure 4 It is a second flow chart of the control method of one of the embodiments of the present application.

[0062] Figure 5 It is a third flow chart of the control method of one of the embodiments of the present application.

[0063] Figure 6 It is a fourth flow chart of a control method according to one embodiment of the present application.

[0064] Figure 7 It is a fifth flow chart of the control method of one of the embodiments of the present application. DETAILED DESCRIPTION

[0065] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-7 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0066] Reference Figure 1 , Figure 2 First, the mobile phone security and confidentiality device in the embodiment of the present application is introduced. The mobile phone security and confidentiality device disclosed in the embodiment of the present application includes a security box 1 and a storage box 2 for sealing and placing mobile phones. The security box 1 is hollow inside and one side is opened. The storage box 2 is integrally formed and arranged on the side of the security box 1 away from the opening. The security box 1 is filled with a sound-absorbing layer 3, and a mobile phone placement slot 11 for placing a mobile phone is formed on the surface of the sound-absorbing layer 3 in the security box 1, and a soundproof cover 12 is provided at the opening of the security box 1; a noise generator 13 is also installed in the security box 1, and the noise generator 13 is fixedly installed on the inner side wall of the mobile phone placement slot 11, and is used to shield the effective audio signal collected by the mobile phone microphone, that is, when the mobile phone is placed in the mobile phone placement slot 11, the noise generator 13 is directly opposite to the microphone of the mobile phone.

[0067] As an implementation mode of the noise generator 13, the noise generator 13 can be a medium-high audio frequency noise generator 13; after closing the sound insulation cover 12, the medium-high audio frequency noise generator 13 can be controlled to work through an external switch, and the noise generator 13 generates noise of a specific frequency in the security box 1. These noises can interfere with and shield the effective audio signals that may be captured by the mobile phone microphone, so as to achieve the functions of preventing eavesdropping and recording.

[0068] In addition, the noise generator 13 is specially designed to cover the human voice frequency band or other sensitive audio signals, making any attempt to eavesdrop through the mobile phone microphone invalid, ensuring that even if the mobile phone is activated and attempts to record, only invalid audio covered by the noise can be recorded, thereby significantly improving the confidentiality of meetings or conversations and effectively preventing the leakage of sensitive information.

[0069] In the above embodiment, after placing the mobile phone in the security box 1 and closing the soundproof cover 12, the sound-absorbing layer 3 in the security box 1 can absorb and reduce the reflection of sound waves and reduce the propagation of sound due to its special material and structure, and the noise generator 13 can generate noise of a specific frequency in the security box 1 to interfere with and shield the effective audio signal that may be captured by the mobile phone microphone, thereby greatly improving the privacy of confidential meetings or personal conversations and preventing sensitive information from being illegally monitored or recorded; and the design of the device takes portability into consideration, so that it can not only be used in fixed places, but also be suitable for being portable and moved to any temporary or mobile occasions. Therefore, while improving security, it can meet the confidentiality requirements of temporary or mobile occasions.

[0070] Reference Figure 1 , Figure 2 The mobile phone security and confidentiality device also includes a noise detection module 14, a noise display module 15 and a control board 4. The control board 4 is installed in the storage box 2. The control board 4 is respectively connected to the noise detection module 14 and the noise display module 15. The noise detection module 14 is used to detect the noise generated by the noise generator 13 and output a noise detection signal. The control board 4 is used to respond to the noise detection signal and control the noise display module 15 to display the noise intensity.

[0071] Reference Figure 1 , Figure 2 , the security box 1 is also provided with an incoming call status detection module and an incoming call prompt module, the control board 4 is respectively connected to the incoming call status detection module and the incoming call prompt module, the incoming call status detection module is used to detect the incoming call status of the mobile phone and output an incoming call status detection signal, and the control board 4 is used to respond to the incoming call status detection signal and control the incoming call prompt module to perform an incoming call prompt;

[0072] As an implementation of the incoming call status detection module, the incoming call status detection module may include an incoming call vibration sensor 16, which is fixedly installed in the mobile phone placement slot 11 and is located on the surface of the sound absorbing layer 3. The incoming call vibration sensor 16 is used to sense the vibration generated by the mobile phone when a call is coming in and output an incoming call status detection signal; in order to improve the detection effect, the incoming call status detection module may be arranged in close contact with the mobile phone when the mobile phone is placed in the mobile phone placement slot 11.

[0073] As another implementation of the incoming call status detection module, the incoming call status detection module can also include an incoming call ringtone pickup 17, which is fixedly mounted on the inner wall of the mobile phone placement slot 11. The incoming call ringtone pickup 17 is used to collect the ringtone generated by the mobile phone in the incoming call state and output an incoming call status detection signal, that is, when the mobile phone is placed in the mobile phone placement slot 11, the incoming call ringtone pickup 17 is directly opposite to the speaker of the mobile phone.

[0074] It is understandable that the speakers and microphones of most mobile phones on the market are located at the top and bottom of the mobile phone respectively. Therefore, in the embodiment of the present application, the noise generator 13 and the incoming call ringtone pickup 17 are respectively installed on the opposite side walls of the mobile phone placement slot 11.

[0075] It should be noted that, in some embodiments, the incoming call status detection module may select the incoming call vibration sensor 16 and / or the incoming call ringtone pickup 17, that is, the present application can detect the incoming call status of the mobile phone through vibration and / or ringtone.

[0076] As an implementation of the incoming call prompt module, the incoming call prompt module includes an incoming call prompt light 18 and a vibration prompter 19. The incoming call prompt light 18 is fixedly arranged on the surface of the security box 1, and can prompt the user of the incoming call by flashing the light. The vibration prompter 19 is arranged outside the security box 1, and can prompt the user by vibrating the entire mobile phone security and confidentiality device to avoid missing messages. In addition, the incoming call prompt module can also be set as an incoming call prompt display screen, which can prompt by displaying the incoming call words such as "You have a new call".

[0077] In the above implementation mode, through the intelligent incoming call detection and prompt mechanism, the confidentiality device can not only protect the privacy and security of the user, but also intelligently manage incoming calls without interfering with meetings or confidential occasions. Users can keep the meeting or conversation confidential while promptly knowing and responding to important calls, effectively reducing the risk of missing important calls; and users do not need to frequently check their phones or worry about missing urgent or important calls in a confidential environment, which improves the user experience and demonstrates a high level of technological integration and innovation.

[0078] Reference Figure 1 , Figure 2 As a further embodiment of the mobile phone security and confidentiality device, it also includes a mobile phone charging module 5 and a power supply 6. The mobile phone charging module 5 is used to charge the mobile phone in the mobile phone placement slot 11 by wired / wireless means. The power supply 6 and the control board 4 are installed in the storage box 2. The power supply 6 is used to power the mobile phone security and confidentiality device and the mobile phone charging module 5. A backup battery box 7 is also provided in the storage box 2. The backup battery box 7 is used to install backup batteries. The control board 4 is also used to control the backup batteries in the backup battery box 7 to power the mobile phone security and confidentiality device.

[0079] The embodiment of the present application discloses a control method for a mobile phone security and privacy device.

[0080] Reference Figure 3 , a control method for a mobile phone security and confidentiality device, the control method comprising:

[0081] Step S101, receiving an incoming call status detection signal sent by an incoming call status detection module;

[0082] Among them, the incoming call status detection module is responsible for real-time monitoring of the incoming call status of the mobile phone. When there is an incoming call request, the module detects the change in the incoming call status and generates a call status detection signal, ensuring that the mobile phone security and confidentiality device can respond to all incoming call requests in a timely manner.

[0083] It should be noted that, in addition to the physical detection methods such as the above-mentioned incoming call vibration sensor and the incoming call ringtone pickup, the incoming call status detection module in the embodiment of the present application can also be directly connected to the mobile phone. When the mobile phone receives an incoming call, the incoming call status detection module can receive the incoming call notification through a wired or wireless connection and output a corresponding incoming call status detection signal;

[0084] Step S102, acquiring incoming call request information of the mobile phone in response to the incoming call status detection signal;

[0085] Among them, after receiving the incoming call status detection signal, the relevant information of the incoming call request, such as the incoming call number, the incoming call time, etc., is immediately obtained from the mobile phone, thereby providing the necessary input information for the subsequent processing flow, which is the basis for realizing intelligent incoming call processing;

[0086] Step S103, traversing the preset contact database, and determining the caller information based on the call request information;

[0087] Among them, by comparing the incoming call number with the preset contact database, the identity information of the caller is determined, which may include, for example, name, company, position, etc., and may also include identity categories, such as customer, family, leader, etc. By identifying the identity information of the caller, a basis is provided for judging the importance of the call.

[0088] Step S104, predicting the importance priority of the incoming call request information according to the caller information based on a machine learning algorithm;

[0089] Specifically, a machine learning model can be used to analyze caller information and predict the priority of the call request. When training the model, factors such as the caller's identity, historical call frequency, and time are taken into consideration. The importance of the call is intelligently judged to ensure that the user does not miss any important calls, while avoiding being disturbed by unimportant calls at inappropriate times.

[0090] Step S105, determining a corresponding incoming call prompt mode according to the importance priority of the incoming call request information;

[0091] Among them, different incoming call prompt modes can be matched and determined according to the importance priority of the incoming call. For example, important calls may choose light flashing + vibration prompts, generally important calls may choose light flashing prompts or incoming call text display prompts, and unimportant calls may only have simple visual prompts or no prompts.

[0092] It should be noted that users can adjust the contact database and call prompt mode according to personal preferences and actual needs to make call processing more personalized and efficient.

[0093] Step S106, controlling the incoming call prompt module to perform incoming call prompt according to the incoming call prompt mode.

[0094] Among them, the incoming call reminder module performs corresponding reminder actions, such as vibration or flashing lights, according to the received incoming call reminder mode, thereby realizing effective reminders to users and ensuring that users can decide whether to answer the call in time according to their own circumstances.

[0095] In the above implementation mode, when the mobile phone is sealed and placed using the mobile phone security and confidentiality device, by intelligently judging the priority of incoming calls, in specific environments (confidential meetings or confidential workplaces, etc.), users can intuitively perceive the importance of incoming calls through different prompt modes, reasonably arrange answering time, and improve work or life efficiency, thereby eliminating the need to frequently open the safe to check the incoming call status of the mobile phone, thereby improving the user experience.

[0096] As an implementation of step S104, based on a machine learning algorithm, the step of predicting the importance priority of the incoming call request information includes:

[0097] The caller information is input into a pre-trained priority prediction model to predict the importance priority of the call request information; wherein the priority prediction model is pre-trained based on historical call data and pre-labeled important priority tags.

[0098] Specifically, historical call data includes but is not limited to the caller's phone number, call time, caller identity information (such as individual or company), historical call records, etc., and each call data can be pre-labeled to determine the corresponding importance priority label; these labels can be pre-labeled manually based on certain standards or rules. For example, urgent family affairs or calls from important customers may be labeled as "high priority", while advertising or sales calls may be labeled as "low priority".

[0099] It should be noted that the labeling process needs to be carried out according to certain standards or rules. These standards may include: the relationship between the identity of the caller and the user, the time of the call (working hours or non-working hours), and the user's historical response behavior to the call.

[0100] In the above implementation, a prediction model is trained that can accurately predict important priorities based on caller information. As the model continues to learn, the judgment of call priority will become more and more in line with the user's personal preferences and actual needs, thereby obtaining a more personalized service experience.

[0101] Reference Figure 4 As an implementation of the training step of the priority prediction model, the training step includes:

[0102] Step S201, obtaining a sample data set; wherein the sample data set includes historical incoming call data and pre-marked important priority tags;

[0103] Among them, historical call data refers to the data set of all call records received in the past period of time, including but not limited to the caller's phone number, identity information (such as individual, company), call time, historical call records, user's response to the call (such as answering, ignoring, hanging up, etc.), etc. The pre-marked important priority tags can be divided into multiple levels, such as high priority, medium priority, low priority, etc.

[0104] Step S202, preprocessing the sample data set and dividing it into a training set and a test set;

[0105] Specifically, data is preprocessed, including data cleaning (removing missing or outliers), feature encoding (converting categorical data into numerical data), and data normalization (ensuring that the numerical ranges of different features are consistent) to improve the efficiency and accuracy of model training.

[0106] After that, the preprocessed sample data set is randomly divided into two parts: training set and test set. The training set is used to train the model, while the test set is used to evaluate the performance of the model. This step ensures the independence of model training and evaluation, which helps to detect and avoid overfitting.

[0107] Step S203, inputting the historical incoming call data in the training set into the pre-built neural network model to obtain a first label result;

[0108] In some embodiments, the pre-built neural network model may use a multi-layer perceptron (MLP) model. MLP is a feed-forward neural network suitable for processing classification problems and making predictions by learning the feature representation of input data. In the scenario of the present application, MLP can learn the feature representation of caller information and predict its corresponding importance priority.

[0109] Specifically, an MLP model including an input layer, several hidden layers, and an output layer can be pre-built. The number of nodes in the input layer matches the number of features of the caller information, the number of nodes in the output layer matches the number of categories of important priority, and the design of the hidden layer (such as the number of layers and the number of nodes in each layer) is adjusted according to the complexity of the model and the size of the data set. In addition, activation functions (such as ReLU) can be used to increase nonlinearity so that the model can learn complex feature representations.

[0110] Step S204, comparing the pre-annotated important priority labels in the training set with the first label result to obtain a first comparison result;

[0111] The first comparison result is used to correct and adjust the pre-configured model parameters to optimize the model prediction accuracy.

[0112] Step S205, iterating the neural network model according to the first comparison result, correcting the model parameters, and obtaining a trained priority prediction model.

[0113] Specifically, by comparing the model's prediction results (first label results) with the actual important priority labels (pre-labeled important priority labels in the training set), the error is calculated, and backpropagation is performed based on the error to adjust the parameters within the model. This process will be iterated multiple times until the model's prediction error drops to an acceptable level or reaches the preset number of iterations.

[0114] In the above implementation, the preprocessed training set data is input into a pre-built neural network model. The neural network automatically adjusts the internal weight parameters of the network by learning the relationship between the input data (call information) and the output data (important priority label) so that the model can capture complex nonlinear relationships and achieve the purpose of predicting the priority of incoming calls.

[0115] Reference Figure 5 As a further implementation, after obtaining the trained priority prediction model in step S205, the following steps are further included:

[0116] Step S301, obtaining historical incoming call data and pre-annotated important priority labels in a test set;

[0117] It is understandable that after the model training is completed, the performance of the model needs to be evaluated. Therefore, in this step, the historical call data that did not participate in the training and the corresponding pre-labeled important priority labels are obtained from the pre-divided test set to ensure the validity and objectivity of the evaluation results.

[0118] Step S302, inputting the historical incoming call data in the test set into the trained priority prediction model to obtain a second label result;

[0119] The second label result is the model's prediction of the importance priority of these incoming call request information in the test set;

[0120] Step S303, comparing the pre-annotated important priority labels in the test set with the second label result to obtain a second comparison result;

[0121] Among them, the second comparison result can quantitatively evaluate the performance of the model, including the model's ability to recognize labels of different priorities and the overall prediction accuracy.

[0122] Step S304, based on the second comparison result, the performance index of the trained priority prediction model is evaluated and iterated until a preset number of iterations or a performance index threshold is reached to obtain a priority prediction model.

[0123] Among them, the second label result predicted by the model is compared with the pre-labeled important priority labels in the test set to evaluate the performance of the trained model, using indicators such as accuracy, recall rate and F1 score to measure, and adjust the model structure (such as adding or reducing hidden layers, adjusting the number of nodes) or training parameters (such as learning rate, batch size) according to the evaluation results, and retrain until the preset number of iterations or satisfactory performance is reached.

[0124] In the above implementation, the use of an independent test set can more accurately evaluate the performance of the model on unknown data, ensuring that the model can predict the priority of incoming calls with high accuracy in practical applications; by performing rigorous test set evaluation and iterative optimization on the trained model, the high performance and reliability of the priority prediction model in practical applications can be ensured, thereby improving the efficiency and satisfaction of users with call processing.

[0125] Reference Figure 6 As a further implementation of the control method, after the step of determining the corresponding incoming call prompt mode according to the importance priority of the incoming call request information in step S105, it also includes:

[0126] Step S401, determine whether the important priority is higher than the preset priority threshold, if so, jump to step S402; if not, do not perform any operation;

[0127] Step S402, obtaining the identity information of the current user in real time;

[0128] Among them, by comparing the importance priority of the incoming call request information with the priority threshold preset by the system, it is determined whether the incoming call needs to be specially handled. This preset priority is set based on user preferences or system security requirements.

[0129] Step S403, perform security verification on the identity information based on the preset identity database and determine whether the verification is successful; if the verification is successful, jump to step S404; if the verification fails, jump to step S405;

[0130] Specifically, the system matches and verifies the acquired identity information with the information in the preset identity database to determine whether the user identity is legitimate, thereby ensuring whether the current operating user has the authority to receive and process high-priority incoming call prompts.

[0131] In some embodiments, when the priority of the incoming call request is higher than the preset priority, the system will obtain the identity information of the current user in real time. The identity information can be facial recognition information, and the mobile phone security device can be integrated with biometric technology to achieve identity security verification function;

[0132] It is understandable that by collecting identity information and pre-configuring the identity database, a basis can be provided for subsequent security verification, thereby ensuring the security of subsequent processing steps.

[0133] Step S404, keep the incoming call reminder mode and jump to step S106;

[0134] Step S405, modify the incoming call prompt mode to the silent mode and jump to step S106.

[0135] Among them, if the user identity authentication passes, the system maintains the originally set incoming call prompt mode, allowing the user to make an appropriate response based on the importance of the call; if the user identity authentication fails, the system changes the incoming call prompt mode to silent mode to prevent unauthorized users from accessing incoming call prompts that may contain sensitive information.

[0136] In the above implementation, when there is an important or urgent call, the call reminder function is activated only when a user who has passed the identity verification is present, otherwise it remains silent to prevent unauthorized personnel from noticing the call information, thereby ensuring that only users who have passed the identity security verification can receive the call reminder, avoiding unauthorized personnel from accidentally contacting sensitive calls, and enhancing the protection of user privacy and security.

[0137] Reference Figure 7As a further implementation of the control method, after controlling the incoming call prompt module to perform the incoming call prompt according to the incoming call prompt mode in step S106, the method further includes:

[0138] Step S501, determining whether there is any incoming call request information higher than a preset priority threshold that has not been processed after a preset time period;

[0139] It is understandable that the system can generate a call request log to record the reception time, priority and processing status of each call request information. By comparing with the current time, it can be determined which call request information has not been processed within the preset time.

[0140] If yes, jump to step S502; if no, do not perform any operation;

[0141] Step S502: Generate emergency handling information according to the incoming call request information and send it to a preset emergency contact.

[0142] Specifically, for high-priority calls that are judged to be unhandled, the system will automatically generate emergency handling information based on the call request information (such as the identity of the caller, the time of the call, etc.), which may include the basic information of the caller, the time of the call, and an emergency prompt indicating that this is an unhandled important call. The system will send this information to the user's preset emergency contacts through SMS, email or instant messaging applications, ensuring that even if the user cannot respond in time, the emergency information can still be paid attention to and handled.

[0143] In the above implementation, unprocessed high-priority call requests are automatically converted into emergency processing information and sent to the preset emergency contact. This is suitable for situations where the user cannot answer the call but the call is very urgent, ensuring that the emergency information can be processed in a timely manner, thereby improving the efficiency and security of call management.

[0144] In addition, the present application can also integrate environmental perception technology, such as the mobile phone security and confidentiality device also includes a noise detection sensor and a light detection sensor, so that the incoming call prompt module can automatically adjust the prompt mode according to the noise level and light intensity of the current environment. For example, the vibration intensity is automatically increased in a noisy environment, and the brightness or flashing frequency of the LED light is increased in a dim environment, which ensures the effectiveness of the incoming call prompt in various environments, improves the user experience, and avoids the problem of the prompt being too harsh or difficult to detect in a specific environment.

[0145] The embodiment of the present application also discloses a control system for a mobile phone security and confidentiality device.

[0146] A control system for a mobile phone security and confidentiality device, the control system comprising:

[0147] A receiving module, used for receiving an incoming call status detection signal sent by an incoming call status detection module;

[0148] An acquisition module, used for acquiring incoming call request information of a mobile phone in response to an incoming call status detection signal;

[0149] A caller information determination module, used to traverse a preset contact database and determine the caller information based on the call request information;

[0150] An important priority prediction module, used to predict the important priority of incoming call request information according to caller information based on a machine learning algorithm;

[0151] An incoming call prompt mode determination module, used to determine a corresponding incoming call prompt mode according to the importance priority of the incoming call request information;

[0152] The incoming call prompt control module controls the incoming call prompt module to perform incoming call prompt according to the incoming call prompt mode.

[0153] In the above implementation mode, when the mobile phone is sealed and placed using the mobile phone security and confidentiality device, by intelligently judging the priority of incoming calls, in specific environments (confidential meetings or confidential workplaces, etc.), users can intuitively perceive the importance of incoming calls through different prompt modes, reasonably arrange answering time, and improve work or life efficiency, thereby eliminating the need to frequently open the safe to check the incoming call status of the mobile phone, thereby improving the user experience.

[0154] As a further implementation of the control system, it also includes:

[0155] A judgment module, used to judge whether the important priority is higher than a preset priority threshold, and if so, output a first judgment result;

[0156] An acquisition module, used to acquire the identity information of the current user in real time in response to the first judgment result;

[0157] The security verification module is used to perform security verification on the identity information based on the preset identity database and determine whether the verification is successful; if so, output a verification success result; if not, output a verification failure result;

[0158] An incoming call prompt mode processing module, used for maintaining the incoming call prompt mode in response to the verification passing result;

[0159] The incoming call prompt mode processing module is also used to modify the incoming call prompt mode to a silent mode in response to a verification failure result.

[0160] In the above implementation, when there is an important or urgent call, the call reminder function is activated only when a user who has passed the identity verification is present, otherwise it remains silent to prevent unauthorized personnel from noticing the call information, thereby ensuring that only users who have passed the identity security verification can receive the call reminder, avoiding unauthorized personnel from accidentally contacting sensitive calls, and enhancing the protection of user privacy and security.

[0161] The control system of the embodiment of the present application can implement any one of the above control methods, and the specific working process of each module in the control system can refer to the corresponding process in the above method embodiment.

[0162] In the several embodiments provided in this application, it should be understood that the provided methods and systems can be implemented in other ways. For example, the system embodiments described above are only illustrative; for example, the division of a certain module is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed.

[0163] The embodiment of the present application also discloses a computer device.

[0164] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the control method described above is implemented.

[0165] The embodiment of the present application also discloses a computer-readable storage medium.

[0166] A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any one of the control methods described above.

[0167] Among them, computer-readable storage media can be any tangible medium that contains or stores a program, which can be used by or in conjunction with an instruction execution system, apparatus or device; the program code contained on the computer-readable medium can be transmitted using any appropriate medium, including but not limited to wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0168] It should be noted that in the above embodiments, the description of each embodiment has different emphases, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0169] The above are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Any feature disclosed in this specification (including the abstract and drawings), unless otherwise stated, can be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

Claims

1. A control method for a mobile phone security device, characterized in that: The mobile phone security and confidentiality device comprises a security box for sealing and placing the mobile phone, and the security box is also provided with an incoming call status detection module and an incoming call prompt module, and the incoming call status detection module is used to detect the incoming call status of the mobile phone and output an incoming call status detection signal; the control method comprises: Receiving an incoming call status detection signal sent by the incoming call status detection module; Acquiring incoming call request information of the mobile phone in response to the incoming call status detection signal; wherein the incoming call request information includes the incoming call number and the incoming call time; Traversing a preset contact database, and determining caller information based on the incoming call request information; Based on a machine learning algorithm, predict the importance priority of the incoming call request information according to the caller information; Determine a corresponding incoming call prompt mode according to the importance priority of the incoming call request information; The steps of controlling the incoming call prompt module to perform incoming call prompt according to the incoming call prompt mode; and determining the importance priority of the incoming call request information according to the caller information based on a machine learning algorithm include: The caller information is input into a pre-trained priority prediction model to predict the important priority of the call request information; wherein the priority prediction model is pre-trained based on historical call data and pre-labeled important priority tags, and the historical call data includes the caller's phone number, call time, identity information and historical call records; the method also includes a training step for the priority prediction model, which includes: Acquire a sample data set; wherein the sample data set includes the historical incoming call data and pre-marked important priority tags; Performing data preprocessing on the sample data set and dividing it into a training set and a test set; Inputting the historical call data in the training set into a pre-built neural network model to obtain a first label result; wherein the pre-built neural network model is an MLP model including an input layer, a hidden layer, and an output layer, the number of input layer nodes matches the number of features of the caller information, and the number of output layer nodes matches the number of important priority categories; Comparing the first label result with the pre-labeled important priority label in the training set to obtain a first comparison result; The neural network model is iterated according to the first comparison result, the model parameters are corrected, and the trained priority prediction model is obtained.

2. A control method for a mobile phone security device according to claim 1, characterized in that: After obtaining the trained priority prediction model, the method further includes: Obtaining the historical incoming call data and pre-labeled important priority labels in the test set; Inputting the historical incoming call data in the test set into the trained priority prediction model to obtain a second label result; Comparing the second label result with the pre-labeled important priority label in the test set, obtaining a second comparison result; According to the second comparison result, the performance index of the trained priority prediction model is evaluated and iterated until a preset number of iterations or a performance index threshold is reached to obtain the priority prediction model.

3. A control method for a mobile phone security device according to any one of claims 1 to 2, characterized in that: After the step of determining the corresponding incoming call prompt mode according to the importance priority of the incoming call request information, the method further includes: Determine whether the important priority is higher than a preset priority threshold, and if so, obtain the identity information of the current user in real time; Perform security verification on the identity information based on a preset identity database and determine whether the verification is successful; If the verification is successful, the incoming call prompt mode is maintained and the process proceeds to the next step; if the verification fails, the incoming call prompt mode is modified to a silent mode and the process proceeds to the next step.

4. The control method of a mobile phone security and confidentiality device according to claim 3, characterized in that: After the step of controlling the incoming call prompt module to perform the incoming call prompt according to the incoming call prompt mode, the method further includes: Determine whether there is any incoming call request information higher than a preset priority threshold that has not been processed after a preset time period; If so, emergency handling information is generated according to the incoming call request information and sent to a preset emergency contact.

5. A control system for a mobile phone security device, characterized in that: The mobile phone security and confidentiality device comprises a security box for sealing and placing the mobile phone, and the security box is also provided with an incoming call status detection module and an incoming call prompt module, wherein the incoming call status detection module is used to detect the incoming call status of the mobile phone and output an incoming call status detection signal; The control system is used to execute a control method for a mobile phone security and confidentiality device according to any one of claims 1 to 4, and the control system comprises: A receiving module, used for receiving an incoming call status detection signal sent by the incoming call status detection module; An acquisition module, configured to acquire the incoming call request information of the mobile phone in response to the incoming call status detection signal; A caller information determination module, used to traverse a preset contact database and determine the caller information based on the call request information; An important priority prediction module, used for predicting the important priority of the incoming call request information according to the caller information based on a machine learning algorithm; An incoming call prompt mode determination module, used to determine a corresponding incoming call prompt mode according to the importance priority of the incoming call request information; The incoming call prompt control module controls the incoming call prompt module to perform incoming call prompt according to the incoming call prompt mode.

6. The control system of a mobile phone security and confidentiality device according to claim 5, characterized in that: The control system further comprises: A judgment module, used to judge whether the important priority is higher than a preset priority threshold, and if so, output a first judgment result; An acquisition module, used for acquiring the identity information of the current user in real time in response to the first judgment result; A security verification module is used to perform security verification on the identity identification information based on a preset identity database and determine whether the verification is successful; if so, output a verification success result; if not, output a verification failure result; An incoming call prompt mode processing module, configured to maintain the incoming call prompt mode in response to the verification passing result; The incoming call prompt mode processing module is also used to modify the incoming call prompt mode to a silent mode in response to the verification failure result.

7. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the method according to any one of claims 1 to 4 is implemented when the processor executes the program.

8. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and executes the method according to any one of claims 1 to 4.

Images