Security protection control method and system for multi-dimensional data

Abstract

The invention relates to the technical field of automatic safety control, and provides a safety protection control method and system for multi-dimensional data. The method comprises the steps that an identity authentication unit is connected, identity information recognition is carried out by collecting multi-dimensional data, and access opening and closing control of an access system is carried out according to an identity recognition result; if the access opening and closing control is passed, determining an access opening result, and generating a search channel for receiving a search index; generating an access suggestion based on the multi-dimensional data, and performing open control on search data extracted by identifying the search index according to the access suggestion; and the open control result is connected with an alarm system for dark alarm control. The technical problems that a traditional identity authentication mode is insufficient in safety and access control lacks dynamic adaptive capacity are solved, and the technical effects that the identity recognition accuracy and safety are improved through multi-dimensional data fusion, the access permission is dynamically adjusted, and a hidden alarm mechanism is triggered under the stress condition are achieved.

Description

Technical Field

[0001] The present application relates to the field of automated security control technology, and in particular to a security protection control method and system for multi-dimensional data. Background Art

[0002] In the field of modern security protection, traditional unlocking technologies include password unlocking, fingerprint unlocking, face recognition unlocking, and iris recognition unlocking. These technologies are used to ensure the accuracy of the unlocking process. However, traditional unlocking methods face many challenges and limitations, such as: passwords are easy to be cracked or forgotten, fingerprints and irises are vulnerable to copying or forgery, and face recognition is also vulnerable to photo or video deception. These problems make the security of unlocking devices insufficient, especially in complex environments or potential coercion scenarios, traditional methods lack the ability to respond and protect. Existing solutions still have shortcomings, fail to comprehensively utilize multiple information to enhance security, and usually do not have the ability to adapt to changes in complex environments, and cannot respond in time when emergencies occur. With the continuous development of attack technology, traditional unlocking methods have gradually exposed security risks. In order to solve these problems, the present invention proposes a security protection control method for multidimensional data, which aims to improve the accuracy and security of identity authentication by combining multiple biometrics and environmental information, and can dynamically adapt to and defend against potential coercion situations. Summary of the invention

[0003] This application provides a security protection control method and system for multi-dimensional data, aiming to solve the technical problems of insufficient security of traditional identity authentication methods and lack of dynamic adaptability of access control.

[0004] In view of the above problems, the present application provides a security protection control method and system for multi-dimensional data.

[0005] The first aspect disclosed in the present application provides a security protection control method for multi-dimensional data, the method comprising: connecting an identity authentication unit, identifying identity information by collecting multi-dimensional data, and performing access opening and closing control on an access system based on the identity identification result; if the access opening and closing control is passed, an access opening result is determined, and a search channel is generated for receiving a search index; an access suggestion is generated based on the multi-dimensional data, and according to the access suggestion, an opening control is performed on the search data extracted by identifying the search index; and an alarm system is connected with the opening control result to perform covert alarm control.

[0006] Another aspect disclosed in the present application provides a security protection control system for multi-dimensional data, the system comprising: an access opening and closing control module: connected to an identity authentication unit, identifying identity information by collecting multi-dimensional data, and performing access opening and closing control on the access system based on the identity identification result; a search index receiving module: if the access opening and closing control is passed, an access opening result is determined, and a search channel is generated for receiving the search index; an opening control module: generating an access suggestion based on the multi-dimensional data, and performing opening control on the search data extracted by identifying the search index according to the access suggestion; a secret alarm control module: connecting to the alarm system with the opening control result to perform secret alarm control.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0008] The above-mentioned security protection control method for multi-dimensional data connects to the identity authentication unit, uses multi-dimensional data for identity recognition, and controls the access rights of the system according to the recognition results; when it is determined that the access rights are open, a specific search channel is generated to receive the search index; based on these multi-dimensional data, access suggestions are generated, and the opening of the search data is controlled according to the suggestions; finally, the result of the open control is connected to the alarm system, and the hidden alarm mechanism is automatically triggered when an abnormality is detected to ensure security.

[0009] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0011] Figure 1 The figure is a flowchart of a security protection control method for multi-dimensional data in one embodiment.

[0012] Figure 2 The present invention is an architecture diagram of a security protection control system for multi-dimensional data in one embodiment.

[0013] Explanation of the reference numerals: access opening and closing control module 11 , search index receiving module 12 , opening control module 13 , dark alarm control module 14 . DETAILED DESCRIPTION

[0014] The embodiments of the present application provide a security protection control method and system for multi-dimensional data to solve the technical problems of insufficient security of traditional identity authentication methods and lack of dynamic adaptability of access control.

[0015] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0016] It should be noted that the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or inherent to these processes, methods, products or devices.

[0017] Embodiment 1, as Figure 1 As shown, the present application provides a security protection control method for multi-dimensional data, the method comprising:

[0018] Connect to the identity authentication unit, collect multi-dimensional data to identify the identity information, and use the identity identification results to control the access to the system.

[0019] In an embodiment of the present application, the identity authentication process is started by connecting an identity authentication unit, and the identity authentication unit includes multiple sensors and data acquisition devices, such as a handprint sensor, a facial recognition camera, an iris scanner, a sound recognition device, etc., which are used to collect the user's biometric information and the surrounding environmental information; then, multi-dimensional data is collected simultaneously through multiple sensors and data acquisition devices, including but not limited to the user's identity information and physiological information (such as fingerprints, irises, sounds, etc.), as well as environmental information (such as portraits, sounds, etc.), to ensure that the identity recognition process is comprehensive and accurate; then, the identity information in the multi-dimensional data is compared with the known user information stored in the database, and the user information stored in the database includes previously registered standard biometric data, such as fingerprint templates, iris images, sound features, etc. During the comparison process, the identity information and standard biometric data are input into the authentication convolutional network, which is constructed based on a convolutional neural network. During the construction process, the sample identity information, the sample standard biometric data, and the sample matching degree are input into the initialized convolutional neural network for forward propagation, and are transmitted layer by layer through the input layer, convolution layer, pooling layer, fully connected layer, output layer, etc., Calculate the prediction result including the matching degree, then use the mean square error loss function to calculate the loss value between the prediction result and the sample matching degree, and calculate the gradient of the loss to the weight of each layer layer by layer through back propagation, and then use the Adam optimizer to optimize the network parameters and adjust the weights to minimize the value of the loss function; repeat the above process until the maximum number of iterations is reached; after the training is completed, use the verification data (the sample identity information, sample standard biometric data, and sample matching degree used for training) to test the network performance and evaluate the accuracy of the network in the matching degree calculation task. If the accuracy meets the preset accuracy, the current convolutional neural network is output as the final authentication convolutional network. Otherwise, adjust the learning rate, the number of training batches and other hyperparameters to further improve the computing power of the convolutional neural network; according to the calculation of the authentication convolutional network, the matching degree of the identity information and the standard biometric data can be obtained. If the matching degree reaches the predetermined standard, it is considered that the identity authentication is passed, and the user's identification result is confirmed to be the legitimacy of the identity. If the matching degree is lower than the standard, it is determined that the identification result is illegal and access is denied; once the identity identification is completed, the access switch control system is dynamically controlled according to the identification result to implement access rights management. Through this process, access rights will be controlled based on identity identification results, ensuring that only verified users can obtain corresponding access rights, thereby flexibly controlling access rights and enhancing security.

[0020] Furthermore, the present application provides the acquisition of multi-dimensional data, including:

[0021] Collect the eye information of the target visitor, perform iris matching to generate the first identity information, and perform eye tracking to generate the first physiological information; collect the audio information of the target visitor, perform audio matching to generate the second identity information, and perform audio pressure recognition to generate the second physiological information; collect the hand skin information of the target visitor, perform hand skin texture matching to generate the third identity information, and perform hand skin electrical response recognition to generate the third physiological information; collect background information to perform environmental anomaly detection to generate environmental information; merge the first identity information, the second identity information and the third identity information as identity information, merge the first physiological information, the second physiological information and the third physiological information as physiological information, and merge the identity information, the physiological information and the environmental information as the multi-dimensional data.

[0022] Preferably, when collecting eye information, an iris scanner or camera is used to collect eye images of the target visitor to form eye information, and then the iris convolution network in the feature convolution channel is used to match the eye information, and the iris feature information of the eye (such as iris texture, pupil position, pupil boundary, iris color, iris shape) is extracted to form the first identity information, wherein the feature convolution channel is composed of three convolution networks, namely, an iris convolution network, a voiceprint convolution network, and a handprint convolution network. The construction method of these convolution networks is the same as the construction method of the aforementioned authentication convolution network, and they are all trained through forward propagation, loss calculation, back propagation, parameter optimization and other steps. In addition, based on the collected eye information, the movement trajectory of the target visitor's eyes is tracked, and the eye movement data, such as gaze point, gaze duration, eye movement speed, etc., are analyzed, and these data are merged into a data set to form the first physiological information; when collecting audio information, a microphone is used to collect the target visitor's eyes. The target visitor's voice is recorded by a wind or other audio collection device to form audio information, and the audio information is converted into a spectrogram using short-time Fourier transform (STFT) through framing, windowing, Fourier transform, spectrogram generation and other steps. The obtained spectrogram is then matched using the voiceprint convolution network in the feature convolution channel to extract voiceprint feature information (such as tone, pitch, resonance peak, timbre, speech speed, short-time energy) to form the second identity information. In addition, the pressure change in the target visitor's voiceprint feature information is analyzed through a pressure recognition model to identify emotional fluctuations such as pressure and anxiety, and quantify a pressure value, which is stored as the second physiological information. The pressure recognition model used in this process can be constructed based on a deep neural network, or based on support vector regression, long short-term memory network, etc. When a deep neural network is used for construction, the training method is the same as the above, the difference lies in the model structure (input layer, hidden layer, output layer) and training data;When collecting hand skin information, the texture image of the target person's hand skin is collected through a handprint sensor or a high-definition camera to form the hand skin information. The handprint convolution network in the feature convolution channel is then used to match the hand skin information, and the hand skin texture feature information (such as texture direction, skin roughness, texture scale, fingerprint ridge density, skin color distribution, color difference) is extracted to form the third identity information. In addition, the electrical response of the target person's hand skin is measured through the galvanic skin response sensor (GSR). The galvanic skin response can reflect the user's physiological response. The conductivity of the skin is closely related to the humidity of the skin. Increased skin humidity usually increases the skin's humidity. Related to emotional fluctuations (such as anxiety, tension, etc.), the collected GSR signal is denoised and filtered (such as using a low-pass filter to remove high-frequency noise), and then the baseline conductivity is determined by identifying the static level of the signal (for example, a period of quietness without stimulation). The baseline conductivity is the average or median of the signal over a period of time. Subsequently, the change value from the baseline to the highest point in the signal is identified as the skin electrical response amplitude, and the moment when the skin conductivity reaches the maximum value is used as the timing zero point. The change in skin conductivity is tracked until it returns to a position close to the baseline conductivity, and this period of time is recorded as the recovery time. After that, , merge the baseline conductivity, skin galvanic response amplitude, and recovery time into a data set to form the third physiological information; when collecting environmental information, collect the image and audio information of the target visitor in the space through the camera and microphone or other audio collection equipment, and merge the two kinds of information into a set as environmental information; then, merge the first identity information generated by iris matching, the second identity information generated by audio matching, and the third identity information generated by hand skin texture matching into a complete identity information. Each type of identity information represents a unique biometric feature of the target visitor. After merging, a multi-dimensional identity authentication information is obtained. Then, the first physiological information generated by eye tracking, the second physiological information generated by audio pressure recognition, and the third physiological information generated by hand skin galvanic response are merged into a complete physiological information to judge the emotional state of the target visitor; finally, the collected environmental information is combined with the identity information and physiological information to generate the final multi-dimensional data. This data includes not only the identity characteristics and physiological state of the target visitor, but also the real-time information of the environment in which it is located, providing richer context information for subsequent access control and security monitoring, and is used for operations such as identity authentication, access control, and security alarm triggering to ensure the security and flexibility of the system. ;

[0023] Furthermore, the present application provides the method of generating first physiological information by performing eye tracking, including:

[0024] Based on the eye information, count the gaze points, determine whether there are repeated gaze points in the gaze point statistics, and obtain the gaze point analysis results; use the eye information to count the gaze duration, determine whether there is excessive gaze duration in the gaze duration statistics, and obtain the gaze duration analysis results; combine the gaze point analysis results and the gaze duration analysis results to calculate the eye movement trajectory and eye movement speed, and obtain the eye movement change results; identify pupil dilation and pupil contraction according to the eye information, and obtain the pupil reaction results; calculate the blinking frequency in combination with the eye information, and obtain the blinking frequency results; combine the eye movement change results, the pupil reaction results, and the blinking frequency results as the first physiological information.

[0025] Optionally, after obtaining the eye information, the eye gaze positions in each time window will be counted to identify the gaze points (i.e., the points where the eyes focus at a certain moment). These gaze points usually correspond to an object or area in the image or scene. During the statistical process, if a gaze point is gazed at multiple times within a certain period of time (i.e., more than a set number of times), it is considered to be a repeated gaze point. Repeated gaze points usually reflect the user's strong attention or emotional response. After the eye information analysis is completed, the obtained repeated gaze points will be summarized to form a gaze point analysis result. This gaze point analysis result shows the focus of the target visitor; in this process, the length of time each gaze point is gazed at will also be calculated, i.e., The time that the eyes stay on the point, the gaze duration is an important indicator of attention concentration and psychological activity. If the dwell time on a certain gaze point exceeds the set duration, it is considered that the point is over-gaze. Excessive gaze usually indicates visual fatigue, tension or abnormal behavior of concentration. The gaze points marked with excessive gaze are summarized to form the gaze duration analysis results; then, according to the time sequence of the eye information, all the gaze points are sorted in chronological order. The sorted gaze point sequence represents the path of eye movement. Starting from the first gaze point, the eye movement path between each gaze point is calculated, that is, the distance between each two adjacent gaze points. This distance can be calculated based on the Euclidean distance, and then according to the calculated The distance connects the sequence of fixations to obtain the eye movement trajectory. At the same time, the distance between each two adjacent fixations and the moving time of the two adjacent fixations (i.e. the time from the first to the second) are used to calculate the ratio to obtain the eye movement velocity. The obtained eye movement trajectory and eye movement velocity are then combined to obtain the eye movement change result. After that, the maximum dilation amplitude (the difference between the maximum diameter and the normal diameter) and contraction amplitude (the difference between the normal diameter and the minimum diameter) of the pupil are calculated, as well as its recovery time (the time to recover from the maximum diameter or the minimum diameter to the normal diameter). As a result of the pupil reaction, the size of the pupil will change with emotional fluctuations. Usually, the pupil will dilate when anxious, stressed or emotional, and will contract when relaxed. By calculating these pupil response results, the stress level and tension of the target visitor can be understood; then, the number of blinks per unit time (per second) is counted as the blink frequency result. Blinking is usually an automatic physiological reaction. High-frequency blinking is usually related to emotional stress or heavy psychological burden, while low-frequency blinking may indicate a relaxed state; finally, the gaze point analysis results, gaze duration analysis results, eye movement change results, pupil response results and blink frequency results are merged, that is, added to a set to form a comprehensive first physiological information. This physiological information not only includes the characteristics of visual attention and emotional fluctuations, but also reflects the individual's stress level, emotional response and other physiological states, providing an important basis for safety protection.

[0026] Furthermore, the present application provides the method of collecting background information for environmental anomaly detection and generating environmental information, including:

[0027] Collect spatial image information to perform portrait recognition other than the target visitor and generate image monitoring results; collect spatial audio information to perform voiceprint collection other than the target visitor and generate audio monitoring results; combine the image monitoring results and the audio monitoring results as the environmental information.

[0028] Optionally, spatial image information is collected through a camera, and face recognition technology (such as HOG features, LBPH algorithm, etc.) is used to detect faces in the spatial image, analyze the characters in the image, and identify whether there are other people besides the target visitor. If so, the features of these faces (such as facial key points, facial contours, etc.) are recorded. In this way, it is possible to confirm whether there are unauthorized people appearing in the monitoring area, thereby generating image monitoring results; subsequently, spatial audio information is collected through a microphone or other audio collection equipment, and voiceprints are collected for sounds other than the target visitor. The collection method is the same as the aforementioned acquisition of the second identity information, and the collected voiceprint features are then compared with the voiceprint features of the target visitor, thereby excluding the audio signal of the target visitor and retaining only other sound signals except the target visitor, thereby obtaining audio monitoring results; finally, the image monitoring results and the audio monitoring results are combined to generate complete environmental information, providing comprehensive data on the current environmental status for subsequent analysis.

[0029] If the access opening and closing control is used to determine the access opening result, a search channel is generated for receiving the search index.

[0030] In one embodiment, access control is to determine whether to allow users to access system resources through identity authentication, ensuring that only authorized users can access search resources. If the access control authentication is passed, it means that the identity of the target access person is legal. At this time, the generated access opening result is access opening, allowing the user to access the search resources. Otherwise, it means that the identity of the target access person is illegal. At this time, the generated access opening result is access denial, and an error prompt or access denial will be returned; when the access opening result is access opening, a search channel will be generated. The search channel refers to an interface or module for performing search operations. It will determine whether the user can query specific data or information based on the access control results. The channel can be a data query interface, API, database search path, etc., which is used to receive and process search requests to indicate how the system should respond to the user's search query; the search channel will also receive search indexes, which are used to retrieve data or keywords for specific information to help the search channel efficiently locate related content. The search index is usually dynamically generated according to the user's query needs and can be built based on database fields, keywords or tags to help speed up the data retrieval process. Simply put, access control determines whether access can continue. Once access is confirmed, a dedicated channel will be set up for subsequent data queries and operations to obtain relevant information, thereby providing users with flexible and secure search functions while ensuring the security and access control of data in the system.

[0031] An access suggestion is generated based on the multi-dimensional data, and open control is performed on the search data extracted by identifying the search index according to the access suggestion.

[0032] In one embodiment, generating access suggestions based on multidimensional data and controlling the opening of search data is achieved by comprehensively considering the user's identity information, environmental information, physiological information and other relevant data. First, the access status is verified based on the user's identity and physiological status to ensure that the user's authority matches the current access conditions. This process not only evaluates whether the user's identity is legal, but also checks the dynamic changes of environmental changes and physiological status to ensure that the user accesses data in the correct context; then, based on the verification results, specific access suggestions are generated. These suggestions include different processing methods, such as directly outputting the original text, extracting and replacing key information from the data, or replacing the original data with virtual data simulation. ; Afterwards, the search data is controlled accordingly based on these suggestions. For example, in the case of unprocessed suggestions, the data will be output as is, while for key replacement suggestions, the key parts of the data will be extracted and modified to ensure that sensitive information is not leaked. Among them, the process of obtaining search data is to compare the query information entered by the user with the search index, and match an index that best meets the user's current needs (that is, the one with the highest frequency of indexed keywords in the query information), and based on this index, use the search channel to query the corresponding data from the database and output feedback; In summary, this method ensures the security and flexibility of data access through a flexible control mechanism, while minimizing the potential risk of privacy leakage.

[0033] Furthermore, the present application provides the method of generating access suggestions based on the multidimensional data, and performing open control on identifying the search data extracted by the search index according to the access suggestions, including:

[0034] The access status of the identity information and the physiological information is corrected through the environmental information to complete the judgment of the access status of the target visitor, and access suggestions are generated based on the access status and stored, wherein the access suggestions include unprocessed suggestions, key replacement suggestions, and virtual simulation suggestions; the search data is output in original text with the unprocessed suggestions; the key content of the search data is extracted and changed according to the key replacement suggestions, and the changed search data is output; the search data is replaced with virtual data through the virtual simulation suggestions, and the replaced search data is output.

[0035] Optionally, when performing corrective verification, the identity information is first verified twice. The secondary verification process is the same as the aforementioned access control of the access system based on the identity recognition result. This process is to avoid the contingency that occurs during the first verification. If the secondary verification is also passed, the physiological information and environmental information will be quantified at this time. For each data in the physiological information, such as baseline conductivity, the baseline conductivity and the median of the baseline conductivity range will be used as the difference, and then the difference will be calculated by ratio with the median of the baseline conductivity range to obtain the baseline conductivity score. For example, for the skin electrical response amplitude, the skin electrical response amplitude will be calculated by ratio with the historical maximum response amplitude. , get the skin electrical response score, such as conductivity recovery time, the conductivity recovery time will be calculated by ratio to the maximum conductivity recovery time to get the conductivity recovery time score, such as pressure value, the pressure value will be calculated by ratio to the maximum pressure value to get the pressure score, such as repeated fixation point, the number of fixations of each repeated fixation point will be calculated by ratio to the maximum number of fixations, and then the ratios of all calculated repeated fixation points will be averaged to get the fixation point score, such as excessive fixation duration, the excessive fixation duration of each excessive fixation point will be calculated by ratio to the maximum fixation duration, and then the ratios of all calculated excessive fixation points will be averaged to get the fixation duration. For long scores, such as eye movement tracks, the ratio of the track length to the maximum track length is calculated to obtain the eye movement track score. Similarly, all the scores obtained are weighted to obtain a comprehensive physiological score. Similarly, for each data in the environmental information, such as image monitoring results, the number of faces in the image monitoring results is input into the character score mapping table to obtain the image score of the image monitoring results. For audio monitoring results, the noise intensity is input into the noise intensity score mapping table to obtain the audio score of the audio monitoring results. The image score and the audio score are then weighted to obtain a comprehensive environmental score. Subsequently, the comprehensive physiological score, the comprehensive environmental score and multiple The risk access state thresholds (including no risk threshold, low risk threshold, high risk threshold, each threshold includes physiological score threshold and environmental score threshold) are compared to determine whether the current risk access state is a no risk access state, a low risk access state, or a high risk access state; then, based on the access state judgment result, corresponding access suggestions are generated, and the access suggestions can be of different types, such as unprocessed suggestions, key replacement suggestions, and virtual simulation suggestions; if the access state verification passes and the generated access suggestion is an unprocessed suggestion, the original text of the matched search data will be directly output to the user, and at this time, the user will be able to access the complete and unmodified data;If the access suggestion is a key replacement suggestion, the sensitive parts of the search data, such as personal identity information, financial information, etc., will be modified according to the preset template. For example, the name will be replaced with user A, and the address or phone number will be encrypted or desensitized to ensure that useful data can be provided to users without leaking sensitive information. The changed search data will be presented to users in a new form to ensure privacy and security. If the generated suggestion is a virtual simulation suggestion, the search data will be replaced with virtual data. These virtual data are usually randomly generated and look similar to real data in content, but they do not actually contain any real information. The replaced search data will also be presented to users, and users will not be exposed to real information during operation, thus ensuring the security of information. ;

[0036] Furthermore, the present application provides the method of generating an access suggestion based on the access status, including:

[0037] A risk-free access state, a low-risk access state and a high-risk access state are obtained according to the access state; if the access state is a risk-free access state, the unprocessed suggestion is generated; if the access state is a low-risk access state, the key replacement suggestion is generated; if the access state is a high-risk access state, the virtual simulation suggestion is generated; based on the search data sensitivity obtained by performing sensitivity identification on the search data, the key replacement suggestion when the access state is the low-risk access state is subjected to change control on the virtual simulation suggestion.

[0038] Optionally, the access status is judged according to the comprehensive physiological score and comprehensive environmental score of the target visitor, and the corresponding access status of the target visitor is obtained, such as risk-free access status, low-risk access status and high-risk access status; if the access status is risk-free access status, an unprocessed suggestion will be generated, that is, the user can access the data according to the original content without making any modification to the data; if the access status is low-risk access status, a key replacement suggestion will be generated, that is, the key content of the sensitive data will be extracted and replaced; if the access status is high-risk access status, a virtual simulation suggestion will be generated, that is, the search data will be completely replaced, and the real data will be replaced with simulated data; after the suggestion is generated, further control will be performed according to the sensitivity of the search data. If the target visitor is in a low-risk access status, at this time, the sensitivity of the obtained search data will be identified, that is, the proportion of sensitive data in the search data will be judged. If the proportion of sensitive data is greater than or equal to the sensitive warning value, it means that the sensitivity of the search data is high, and the key replacement suggestion will be adjusted to a virtual simulation suggestion to further increase the control over the search data and ensure the security of the system data.

[0039] Use open control results to connect the alarm system for covert alarm control.

[0040] In one embodiment, after the access control result is determined, further measures will be taken according to the access status of the target visitor (such as low risk or high risk) to ensure the security of the data. Specifically, the integrity of the changed or replaced data will be monitored to ensure that it has not been tampered with or modified without authorization. This monitoring process will continue. If an abnormality is found (such as data tampering or inconsistency), the alarm mechanism will be automatically triggered to notify the administrator or security personnel. The alarm information will be sent secretly through the alarm system without being noticed by the target visitor, ensuring that potential risks are responded to without interfering with their operations. This method ensures that when facing potential risks, monitoring and data protection can be carried out quietly in the background to ensure that data security is not threatened.

[0041] Furthermore, the present application provides the method of connecting the alarm system with the open control result to perform covert alarm control, including:

[0042] The search data in the low-risk access state or the high-risk access state is backed up and stored, and the modified search data or the replaced search data is integrity monitored; if the integrity monitoring obtains an abnormal integrity result, the alarm system is connected to issue a risk tampering alarm.

[0043] Optionally, when the system detects a low-risk or high-risk access status, the relevant search data will be backed up and stored to ensure that the original state of the data can be restored when a problem occurs later to avoid data loss or malicious tampering. At the same time, the integrity of the changed or replaced search data will be monitored. In this process, any modification to the data content (such as replacement of sensitive information or adjustment of data format) will be recorded and tracked to ensure that these data changes are authorized and reviewed. If data integrity anomalies are detected during the monitoring process (such as unauthorized modification or tampering of data), the alarm mechanism will be triggered, and the alarm will automatically connect to the alarm system to report the anomaly to the administrator or relevant security personnel. In this way, timely monitoring and intervention can be ensured when the data is potentially threatened to prevent data tampering, and relevant personnel will be notified quickly to handle the risk when it is discovered.

[0044] In summary, the embodiments of the present application have at least the following technical effects:

[0045] The embodiment of the present application is connected to the identity authentication unit, and performs identity information identification by collecting multi-dimensional data, and performs access opening and closing control on the access system based on the identity identification result; if the access opening result is determined by the access opening and closing control, a search channel is generated for receiving the search index; access suggestions are generated based on the multi-dimensional data, and the search data extracted by identifying the search index is openly controlled according to the access suggestions; the alarm system is connected with the open control result to perform covert alarm control. These technical effects jointly solve the technical problems of insufficient security of traditional identity authentication methods and lack of dynamic adaptability of access control, and achieve the technical effects of improving the accuracy and security of identity identification through multi-dimensional data fusion, dynamically adjusting access rights, and triggering a hidden alarm mechanism under duress.

[0046] Embodiment 2 is based on the same inventive concept as the security protection control method for multi-dimensional data in the above embodiment. Figure 2 As shown, the present application provides a security protection control system for multi-dimensional data, and the system includes: an access opening and closing control module 11: connected to the identity authentication unit, identifying identity information by collecting multi-dimensional data, and performing access opening and closing control on the access system based on the identity identification result; a search index receiving module 12: if the access opening and closing control is passed, the access opening result is determined, and a search channel is generated for receiving the search index; an opening control module 13: generating an access suggestion based on the multi-dimensional data, and performing opening control on the search data extracted by identifying the search index according to the access suggestion; a secret alarm control module 14: connecting the alarm system with the opening control result to perform secret alarm control.

[0047] Furthermore, the access opening and closing control module 11 is also used to execute the following method:

[0048] Collect the eye information of the target visitor, perform iris matching to generate the first identity information, and perform eye tracking to generate the first physiological information; collect the audio information of the target visitor, perform audio matching to generate the second identity information, and perform audio pressure recognition to generate the second physiological information; collect the hand skin information of the target visitor, perform hand skin texture matching to generate the third identity information, and perform hand skin electrical response recognition to generate the third physiological information; collect background information to perform environmental anomaly detection to generate environmental information; merge the first identity information, the second identity information and the third identity information as identity information, merge the first physiological information, the second physiological information and the third physiological information as physiological information, and merge the identity information, the physiological information and the environmental information as the multi-dimensional data.

[0049] Furthermore, the access opening and closing control module 11 is also used to execute the following method:

[0050] Based on the eye information, count the gaze points, determine whether there are repeated gaze points in the gaze point statistics, and obtain the gaze point analysis results; use the eye information to count the gaze duration, determine whether there is excessive gaze duration in the gaze duration statistics, and obtain the gaze duration analysis results; combine the gaze point analysis results and the gaze duration analysis results to calculate the eye movement trajectory and eye movement speed, and obtain the eye movement change results; identify pupil dilation and pupil contraction according to the eye information, and obtain the pupil reaction results; calculate the blinking frequency in combination with the eye information, and obtain the blinking frequency results; combine the eye movement change results, the pupil reaction results, and the blinking frequency results as the first physiological information.

[0051] Furthermore, the access opening and closing control module 11 is also used to execute the following method:

[0052] Collect spatial image information to perform portrait recognition other than the target visitor and generate image monitoring results; collect spatial audio information to perform voiceprint collection other than the target visitor and generate audio monitoring results; combine the image monitoring results and the audio monitoring results as the environmental information.

[0053] Furthermore, the open control module 13 is also used to execute the following method:

[0054] The access status of the identity information and the physiological information is corrected through the environmental information to complete the judgment of the access status of the target visitor, and access suggestions are generated based on the access status and stored, wherein the access suggestions include unprocessed suggestions, key replacement suggestions, and virtual simulation suggestions; the search data is output in original text with the unprocessed suggestions; the key content of the search data is extracted and changed according to the key replacement suggestions, and the changed search data is output; the search data is replaced with virtual data through the virtual simulation suggestions, and the replaced search data is output.

[0055] Furthermore, the open control module 13 is also used to execute the following method:

[0056] A risk-free access state, a low-risk access state and a high-risk access state are obtained according to the access state; if the access state is a risk-free access state, the unprocessed suggestion is generated; if the access state is a low-risk access state, the key replacement suggestion is generated; if the access state is a high-risk access state, the virtual simulation suggestion is generated; based on the search data sensitivity obtained by performing sensitivity identification on the search data, the key replacement suggestion when the access state is the low-risk access state is subjected to change control on the virtual simulation suggestion.

[0057] Furthermore, the dark alarm control module 14 is also used to execute the following method:

[0058] The search data in the low-risk access state or the high-risk access state is backed up and stored, and the modified search data or the replaced search data is integrity monitored; if the integrity monitoring obtains an abnormal integrity result, the alarm system is connected to issue a risk tampering alarm.

[0059] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0060] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0061] This specification and the drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A security protection control method for multi-dimensional data, characterized in that: include: Connect to the identity authentication unit, collect multi-dimensional data to identify identity information, and use the identity identification results to control the access to the system; If the access opening and closing control is used to determine the access opening result, a search channel is generated for receiving the search index; generating access suggestions based on the multidimensional data, and performing open control on search data extracted by identifying the search index according to the access suggestions; Use open control results to connect the alarm system for covert alarm control.

2. The multi-dimensional data security protection control method according to claim 1, characterized in that: The collecting of multi-dimensional data includes: Collecting eye information of the target visitor, performing iris matching to generate first identity information, and performing eye tracking to generate first physiological information; Collecting audio information of the target visitor, performing audio matching to generate second identity information, and performing audio pressure recognition to generate second physiological information; Collecting the hand skin information of the target visitor, performing hand skin texture matching to generate third identity information, and performing hand skin electrical response recognition to generate third physiological information; Collect background information to detect environmental anomalies and generate environmental information; The first identity information, the second identity information and the third identity information are combined as identity information, the first physiological information, the second physiological information and the third physiological information are combined as physiological information, and the identity information, the physiological information and the environmental information are combined as the multidimensional data.

3. The multi-dimensional data security protection control method according to claim 2, characterized in that: The step of performing eye tracking to generate first physiological information includes: Counting the fixation points based on the eye information, determining whether there are repeated fixation points in the fixation point statistics, and obtaining a fixation point analysis result; Counting the fixation duration using the eye information, determining whether there is excessive fixation duration in the fixation duration statistics, and obtaining a fixation duration analysis result; Calculate the eye movement trajectory and eye movement speed by combining the gaze point analysis result and the gaze duration analysis result to obtain the eye movement change result; identifying pupil dilation and pupil contraction according to the eye information to obtain a pupil response result; Calculating the blink frequency based on the eye information to obtain a blink frequency result; The eye movement change result, the pupil reaction result and the blink frequency result are combined as the first physiological information.

4. The multi-dimensional data security protection control method according to claim 2, characterized in that: The collecting of background information to detect environmental anomalies and generate environmental information includes: Collecting spatial image information to perform portrait recognition on people other than the target visitor, and generating image monitoring results; Collect spatial audio information to collect voiceprints other than the target visitor, and generate audio monitoring results; The image monitoring result and the audio monitoring result are combined as the environmental information.

5. The multi-dimensional data security protection control method according to claim 2, characterized in that: The generating of the access suggestion based on the multi-dimensional data and performing open control on the search data extracted by identifying the search index according to the access suggestion includes: Performing a corrective verification of the access status of the identity information and the physiological information through the environmental information, completing the determination of the access status of the target visitor, generating access suggestions based on the access status, and storing the access suggestions, wherein the access suggestions include unprocessed suggestions, key replacement suggestions, and virtual simulation suggestions; Outputting the search data in original text with the unprocessed suggestions; Extracting and modifying key content of the search data according to the key replacement suggestion, and outputting the modified search data; The virtual simulation suggestion performs virtual data replacement on the search data, and outputs the replaced search data.

6. The multi-dimensional data security protection control method according to claim 5, characterized in that: The generating the access suggestion based on the access status includes: Obtaining a no-risk access status, a low-risk access status, and a high-risk access status according to the access status; If the access status is a risk-free access status, generating the unprocessed suggestion; If the access status is a low-risk access status, generating the key replacement suggestion; If the access status is a high-risk access status, generating the virtual simulation suggestion; According to the search data sensitivity obtained by performing sensitivity identification on the search data, the key replacement suggestions when the access state is the low-risk access state are controlled to change the virtual simulation suggestions.

7. The multi-dimensional data security protection control method according to claim 6, characterized in that: The method of connecting the alarm system with the open control result to perform covert alarm control includes: Backing up and storing the search data in the low-risk access state or the high-risk access state, and monitoring the integrity of the modified search data or the replaced search data; If the integrity monitoring obtains an abnormal integrity result, the alarm system is connected to issue a risky tampering alarm.

8. A multi-dimensional data-oriented security protection control system, characterized in that: The steps for implementing the multi-dimensional data security protection control method according to any one of claims 1 to 7 include: Access opening and closing control module: connected to the identity authentication unit, it collects multi-dimensional data to identify identity information, and uses the identity identification results to control the access opening and closing of the access system; Search index receiving module: if the access opening and closing control is passed and the access opening result is determined, a search channel is generated for receiving the search index; An open control module: generating access suggestions based on the multidimensional data, and performing open control on the search data extracted by identifying the search index according to the access suggestions; Hidden alarm control module: connect the alarm system with open control results to perform hidden alarm control.

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