Face recognition security and protection system based on big data and application

Abstract

The invention provides a face recognition security system and application based on big data, and the system comprises a real-time data collection module, a biological characteristic data anonymous transaction module, a face recognition module, a security application module, a data auditing module, an emotion intelligent module, a data desensitization and reconstruction module, and a dynamic simulation generation module which work cooperatively. And efficient and accurate face recognition and security application are jointly realized. Through the arranged system, supplement of an existing database is achieved, transaction supplement is conducted on face biological data related to the industry, risk face data can be effectively input into the database in advance, and through comparison of data collected on site, deployment is conducted in advance, and the safety of the site is guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of security, and in particular to a face recognition security system and application based on big data. Background Art

[0002] With the advancement of science and technology and the development of informatization, face recognition technology has gradually become an important technology in the security field. Face recognition security systems and applications based on big data can achieve efficient and accurate identity authentication and security monitoring, and are widely used in various fields such as finance, transportation, education, tourism, etc.

[0003] Traditional security systems usually use video surveillance and manual patrols, which have certain limitations. For example, video surveillance can only be used for post-event evidence collection and cannot provide real-time warnings; while manual patrols are limited by factors such as manpower and time, making it difficult to achieve full coverage.

[0004] The emergence of facial recognition technology has brought new solutions to the security field. Through facial recognition technology, the identity information of the target person can be quickly and accurately identified, improving the efficiency and accuracy of security monitoring. The facial recognition security system based on big data can realize the processing and analysis of massive data, further improving the accuracy and reliability of facial recognition.

[0005] However, existing facial recognition security systems have certain risks in terms of data security and privacy protection. In the big data environment, how to ensure data security and privacy has become an urgent problem to be solved. Facial recognition technology still has a certain misrecognition rate, especially in complex scenes and dynamic environments. The recognition effect needs to be improved.

[0006] To sum up, while improving the efficiency and accuracy of security monitoring, the facial recognition security system and applications based on big data still need to solve problems such as data security and privacy protection. Future development directions include improving the accuracy and reliability of facial recognition, strengthening data security and privacy protection, and expanding application scenarios.

[0007] For example, the "Face Recognition Security System Based on Big Data" disclosed in the Chinese invention patent CN116403316A, its specification discloses: the current TV monitoring system has been organically combined with the anti-theft alarm system to form a more reliable monitoring system. The entrance and exit control system is also called the access control system. Its function is to control the entry and exit of personnel and the activities of personnel in the prevention area. In the prevention area, various cards, passwords or biometrics must be used to be identified and confirmed by the control device before passing; the above patent can prove the defects of the existing technology.

[0008] Therefore, we made improvements to this and proposed a face recognition security system and application based on big data. Summary of the invention

[0009] The purpose of the present invention is to: aim at the existing

[0010] In order to achieve the above-mentioned purpose of the invention, the present invention provides the following face recognition security system and application based on big data to improve the above-mentioned problems.

[0011] The specific application is as follows: The face recognition security system based on big data includes a real-time data collection module, a biometric data anonymous transaction module, a face recognition module, a security application module, a data audit module, an emotional intelligence module, a data desensitization and reconstruction module, and a dynamic simulation generation module. These modules work together to achieve efficient and accurate face recognition and security applications. The real-time data acquisition module is responsible for capturing facial image data. This module uses a high-resolution camera and image processing technology for preprocessing to improve the accuracy of face recognition; The biometric data anonymous transaction module provides biometric data transaction services. This module uses encryption technology and privacy protection algorithms to ensure the security and privacy of biometric data. The face recognition module performs face recognition and improves recognition accuracy by training face image data. This module supports biometric recognition technology and is used in security, access control and alarm prompts. The security application module issues a security alarm based on the identification results. The module can be integrated with the application control system to achieve automatic control and management of the application, and issue an alarm when an unauthorized person enters. The data audit module records the flow and use of biometric data to ensure data security. The module uses distributed storage technology and encryption technology for secure storage and access control, and provides real-time monitoring and recording functions; The emotional intelligence module analyzes people's micro-expressions and voice changes in biological characteristics, combined with artificial intelligence technology, to achieve intelligent recognition and management of user emotions. This module uses deep learning technology and natural language processing technology to analyze the user's emotional state.

[0012] As the preferred technical solution of this application, the biometric data anonymous transaction module ensures data security and privacy protection through encryption and anonymization technology. When uploading data, the AES-256 strong encryption algorithm is used to protect the original information, and it is securely transmitted through the SSL / TLS protocol. The platform implements the k-anonymity model and irreversible hash processing to isolate the association between personal identity and biometrics. In terms of transactions, it integrates a secure payment system and uses blockchain to improve transaction transparency and security. At the same time, it implements audit monitoring and ensures compliance to protect user privacy and maintain market trust.

[0013] As the preferred technical solution of the present application, the core principle of the face recognition module is the model-based method, such as the hidden Markov model (HMM), the active shape model (ASM) and the active appearance model (AAM). These HMMs process time series data and predict the future trend of the observed data by estimating the hidden state. The ASM focuses on locating and describing specific shapes from the image and captures the contours of the object by training shape feature points. The AAM further combines shape and texture information to provide a more comprehensive description of the image appearance for image matching and recognition tasks.

[0014] As the preferred technical solution of the present application, the biometric data desensitization and reconstruction module performs deep desensitization processing on the original biometric data to ensure the privacy and security of the data, prevent sensitive information from being illegally obtained and abused, and fully protect the user's data privacy. At the same time, the availability and value of the data are also retained.

[0015] As the preferred technical solution of this application, the dynamic simulation generation module is used to generate virtual biometric data with a high degree of simulation for training, testing and verifying the biometric recognition system. Through the generative adversarial network (GAN) technology, virtual biometric data is generated with a high degree of simulation, and it also has the functions of perfect optimization and timely adjustment to improve the performance and effect of the system.

[0016] The face recognition security application based on big data includes a base, a viewing box is connected to the top of the base, a reflector is arranged above the base, a security main body device is arranged on the viewing box, a ramp is fixedly connected to the base, a camera combination device is arranged on the base, and an inflator is arranged above the base.

[0017] As a preferred technical solution of the present application, the security main device includes a flip partition hinged on both sides of the inspection box, the end of the flip partition away from the hinged part is fixedly connected to a magnetic sheet, the inflator is fixedly connected to an outer wall of one side of the flip partition, the reflector is fixedly connected to the outer wall of the flip partition, the flip partition is fixedly connected to an airbag, and rotating partitions are hinged on both sides of the inspection box.

[0018] As a preferred technical solution of the present application, the security main body device also includes a rectangular groove opened on the rotating partition, a rotating plate is rotatably connected to the rectangular groove through a bearing and a rotating shaft, a plurality of fixed strips are fixedly connected to the outer wall of one side of the rotating plate, and a plurality of spikes are fixedly connected to the fixed strips.

[0019] As a preferred technical solution of the present application, the camera combination device includes two empty slots opened on the base, a first electric push rod is fixedly connected to the inner wall of each of the empty slots, a vertical pole is fixedly connected to each of the first electric push rods, and a through slot is opened on each of the vertical poles.

[0020] As a preferred technical solution of the present application, the camera combination device also includes a second electric push rod fixedly connected to the outer wall of the vertical pole, and a sliding block is fixedly connected to the second electric push rod. The sliding block is slidably connected in the through groove through a sliding sheet, and the sliding block is rotatably connected to the first arc plate through a bearing.

[0021] As a preferred technical solution of the present application, the camera assembly device also includes a liquid storage tank fixedly connected to the sliding block, and a plurality of cameras are arranged on one side of the first arc plate.

[0022] As a preferred technical solution of the present application, the camera combination device also includes two spring boxes fixedly connected to the sliding block, the first arc plate is rotatably connected to the second arc plate through a bearing, the camera is fixedly connected to the concave surface of the second arc plate, a plurality of second motor boxes are fixedly connected to the inner wall of the second arc plate, the output end of the second motor box is fixedly connected to a winding roller, a wiring harness is wound on the winding roller of the second motor box, the second arc plate is provided with wiring harness grooves corresponding to the number of wiring harnesses, the other end of the wiring harness is fixedly connected to the concave surface of the first arc plate, and a spray tube is fixedly connected to the first arc plate.

[0023] Compared with the prior art, the present invention has the following beneficial effects: In the scheme of this application: 1. In order to solve the problem of incomplete database coverage in the face recognition system in the prior art, this application realizes the supplement of the existing database through the system set up. By trading and supplementing the industry-related facial biometric data, the risky facial data can be effectively entered into the database in advance. By comparing the data collected on site, it is possible to deploy in advance and ensure the safety of the site; 2. In order to solve the problem that the devices combined with face recognition technology in the prior art are difficult to play a greater security role, this application realizes the rational response to most emergencies through the security main device set up; 3. Through the setting of the security main device, in addition to the effect of limit detection of personnel on site, it can also protect the security personnel on site and restrict dangerous persons to maximize the security effect, solving the problem of relatively single effect of security devices in the prior art; 4. Through the setting of the security main device, the position of the security entrance and exit is restricted by the change of the device form, which provides a reasonable solution for other people to collide with the checkpoint, and safely and effectively restricts dangerous people, solving the problem of weak functionality of security equipment in the prior art; 5. By setting up the camera combination device, it is possible to transform the camera component into a quick response component. By changing the camera combination device, it is possible to take measures to restrict passage and personnel movement when non-compliance is found and dangerous behavior is about to be performed after identity authentication of the personnel passing through the card. This solves the problem in the prior art that it is difficult to ensure the safety of dangerous personnel and the people on the scene at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 System block diagram of the face recognition security system based on big data provided for this application; Figure 2 The main view of the big data-based face recognition security application provided by this application; Figure 3 A side view of the big data-based face recognition security application provided for this application; Figure 4 A schematic diagram of the first state structure of the face recognition security application based on big data provided by this application; Figure 5 A schematic diagram of the rotating plate structure for face recognition security applications based on big data provided in this application; Figure 6 A schematic diagram of the first curved plate structure for the face recognition security application based on big data provided in this application; Figure 7 A schematic diagram of the pole structure for the face recognition security application based on big data provided in this application; Figure 8 A schematic diagram of the second state structure of the face recognition security application based on big data provided by this application; Fig. 9 A cross-sectional view of a pole for a facial recognition security application based on big data provided in this application.

[0025] Indicated in the figure: 1. Base; 3. Reflector; 2. Inspection box; 4. Security main device; 401. Flip baffle; 402. Airbag; 403. Rotating baffle; 404. Rectangular groove; 405. Rotating plate; 406. Fixed strip; 407. Spike; 5. Ramp board; 6. Camera assembly; 601. Empty slot; 602. First electric push rod; 603. Vertical pole; 604. Through slot; 605. Second electric push rod; 606. Sliding block; 607. First curved plate; 608. Liquid storage tank; 609. Camera; 610. Coil spring box; 611. Second curved plate; 612. Second motor box; 613. Wire harness; 614. Spray tube; 7. Inflator. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0027] As described in the background art, traditional security systems usually use video surveillance and human patrols, which have certain limitations. For example, video surveillance can only be used for post-event evidence collection and cannot provide real-time warnings.

[0028] In order to solve this technical problem, the present invention provides a face recognition security system and application based on big data, which is used to restrict dangerous persons from passing through security facilities in specific scenarios, while protecting the safety of security detection personnel and the public.

[0029] Specifically, please refer to Figure 1 ,The face recognition security system based on big data includes real-time data acquisition module, biometric data anonymous transaction module, face recognition module, security application module, data audit module, emotional intelligence module, data desensitization and reconstruction module and dynamic simulation generation module. These modules work together to achieve efficient and accurate face recognition and security applications; The real-time data acquisition module is responsible for capturing facial image data. This module uses a high-resolution camera and image processing technology for preprocessing to improve the accuracy of face recognition; The biometric data anonymous transaction module provides biometric data transaction services. This module uses encryption technology and privacy protection algorithms to ensure the security and privacy of biometric data. The face recognition module performs face recognition and improves recognition accuracy by training face image data. This module supports biometric recognition technology and is used in security, access control and alarm prompts. The security application module issues a security alarm based on the identification results. The module can be integrated with the application control system to achieve automatic control and management of the application, and issue an alarm when an unauthorized person enters. The data audit module records the flow and use of biometric data to ensure data security. The module uses distributed storage technology and encryption technology for secure storage and access control, and provides real-time monitoring and recording functions; The emotional intelligence module analyzes people's micro-expressions and voice changes in biological characteristics, combined with artificial intelligence technology, to achieve intelligent recognition and management of user emotions. This module uses deep learning technology and natural language processing technology to analyze the user's emotional state: The biometric data anonymous transaction module ensures data security and privacy protection through encryption and anonymization technology. When uploading data, the AES-256 strong encryption algorithm is used to protect the original information, and it is securely transmitted through the SSL / TLS protocol. The platform implements the k-anonymity model and irreversible hash processing to isolate the association between personal identity and biometrics. In terms of transactions, a secure payment system is integrated and blockchain is used to improve transaction transparency and security. At the same time, audit monitoring is implemented to ensure compliance, protect user privacy and maintain market trust.

[0030] The core principle of the face recognition module is the model-based approach, such as the Hidden Markov Model (HMM), the Active Shape Model (ASM) and the Active Appearance Model (AAM). These HMMs process time series data and predict future trends of observed data by estimating hidden states. ASMs focus on locating and describing specific shapes from images and capture the contours of objects by training shape feature points. AAMs further combine shape and texture information to provide a more comprehensive description of image appearance for image matching and recognition tasks.

[0031] The biometric data desensitization and reconstruction module performs deep desensitization processing on the original biometric data to ensure the privacy and security of the data and prevent sensitive information from being illegally obtained and abused. The user's data privacy is fully protected, and the availability and value of the data are also retained.

[0032] The dynamic simulation generation module is used to generate virtual biometric data with a high degree of simulation for training, testing and verifying the biometric recognition system. Through the generative adversarial network (GAN) technology, virtual biometric data is generated with a high degree of simulation, and it also has the functions of perfect optimization and timely adjustment to improve the performance and effect of the system.

[0033] The face recognition security system based on big data provided by the present invention can cooperate with the face recognition security application based on big data and the data support of the anonymous transaction module of biometric data, and then perform key scanning on people wearing makeup or in disguise through the key features provided, and restrict uncooperative people through the device support in the application.

[0034] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings.

[0035] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features and technical solutions in the embodiments may be combined with each other.

[0036] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0037] Example 1, please refer to Figure 2 , Figure 3 and Figure 4 The face recognition security application based on big data includes a base 1, a viewing box 2 is fixedly connected to the top of the base 1, the viewing box 2 has two exits forming an arch structure, a security main body device 4 is arranged on the viewing box 2, a ramp plate 5 is fixedly connected to the base 1, a camera combination device 6 is arranged on the base 1, and an inflator 7 is arranged above the base 1. It should be added that the inflator 7 is connected to the airbag 402 through an air pipe, and the air pipe is a prior art and is therefore not disclosed.

[0038] Please refer to Figure 3 , Figure 4 and Figure 5 The security main body device 4 includes a flip partition 401 hinged on both sides of the inspection box 2, and a magnetic suction sheet is fixedly connected to one end of the flip partition 401 away from the hinged part. The inflator 7 is fixedly connected to the outer wall of one side of the flip partition 401, and the reflector 3 is fixedly connected to the outer wall of the flip partition 401. An airbag 402 is fixedly connected to the flip partition 401, and the airbag 402 penetrates the flip partition 401, that is, the airbag 402 is located on both sides of the flip partition 401, and a certain amount of powder is filled in the airbag 402. Rotating partitions 403 are hinged on both sides of the inspection box 2, and the flip partition 401 and the rotating partition 403 constitute a double-layer side panel of the inspection box 2.

[0039] The security main device 4 also includes a rectangular groove 404 opened on the rotating partition 403, in which a rotating plate 405 is rotatably connected via a bearing and a rotating shaft, and a plurality of fixing strips 406 are fixedly connected to an outer wall of one side of the rotating plate 405, and a plurality of spikes 407 are fixedly connected to the fixing strips 406.

[0040] The plurality of spikes 407 can protect the device from being damaged by collision with other objects in a normal state, and can also prevent climbing and circumvention.

[0041] Embodiment 2 further optimizes the face recognition security application based on big data provided in Embodiment 1. Specifically, Figure 6 , Figure 7 , Figure 8 and Fig. 9 As shown, the camera assembly device 6 includes two empty slots 601 opened on the base 1, a first electric push rod 602 is fixedly connected to the inner wall of a single empty slot 601, a vertical rod 603 is fixedly connected to the single first electric push rod 602, and a through slot 604 is opened on the single vertical rod 603. There are two groups of camera assembly devices 6, which are symmetrically arranged on both sides of the entrance and exit of the inspection box 2.

[0042] Further, such as Figure 6 , Figure 7 and Figure 8 As shown, the camera combination device 6 also includes a second electric push rod 605 fixedly connected to the outer wall of the vertical pole 603, and a sliding block 606 is fixedly connected to the second electric push rod 605. The sliding block 606 is slidably connected in the through groove 604 through a sliding sheet, and a first arc plate 607 is rotatably connected to the sliding block 606 through a bearing. A motor for driving the spring box 610 to rotate is fixedly connected between the spring box 610 and the sliding block 606. Since the motor is a prior art, it is not disclosed.

[0043] By using the motion components, the camera assembly device 6 can be moved on a plane, thereby changing the positions of the camera 609 and other components to achieve different effects.

[0044] Further, such as Figure 6 , Figure 7 , Figure 8 and Fig. 9 As shown, the camera assembly device 6 also includes a liquid storage tank 608 fixedly connected to the sliding block 606, and a plurality of cameras 609 are arranged on one side of the first arc plate 607. It should be added that the number of the cameras 609 is determined according to actual needs.

[0045] The camera assembly device 6 also includes two coil spring boxes 610 fixedly connected to the sliding block 606, the first arc plate 607 is rotatably connected to the second arc plate 611 through a bearing, the two coil spring boxes 610 are respectively fixedly connected to the first arc plate 607 and the second arc plate 611 through a rotating shaft, the camera 609 is fixedly connected to the concave surface of the second arc plate 611, and a plurality of second motor boxes 612 are fixedly connected to the inner wall of the second arc plate 611. The output end is fixedly connected to a winding roller, a wire harness 613 is wound on the winding roller of the second motor box 612, the second arc plate 611 is provided with wire harness grooves corresponding to the number of wire harnesses 613, the other end of the wire harness 613 is fixedly connected to the concave surface of the first arc plate 607, and a spray pipe 614 is fixedly connected to the first arc plate 607. It should be added that the spray pipe 614 is connected to the liquid storage tank 608 through a water pump and a water pipe. Since the water pump and the water pipe are prior art, they are not disclosed.

[0046] The combination of curved plates forms a structure that blocks people from entering or exiting, but does not cause obstruction during daily use.

[0047] The use process of the face recognition security system and application based on big data provided by the present invention is as follows: 1. When the device is in use, the inspected person enters and exits through the two entrances and exits on the inspection box 2. When the person reaches the ramp 5, the first electric push rod 602 operates, and its output end drives the sliding block 606 to slide up and down. At the same time, the first curved plate 607 moves with it. At this time, the motor on the coil spring box 610 operates to make the coil spring box 610 rotate. At this time, the first curved plate 607 rotates with it and becomes Figure 7 In the structure, the camera 609 on the second curved plate 611 collects the facial data of the person on the ramp plate 5, and at the same time, the water pump in the liquid storage tank 608 operates to spray the disinfectant through the spray pipe 614 to the next person to be inspected; 2. When the detection result is inconsistent, the first electric push rod 602 pulls the vertical rod 603 to approach the inspection box 2. At this time, the motor in the second motor box 612 is running, and the output end of the motor releases the wire harness 613. At the same time, the first curved plate 607 and the second curved plate 611 are unfolded under the action of the coil spring in the coil spring box 610. At this time, a plurality of wire harnesses 613 and the first curved plate 607 and the second curved plate 611 form a mesh structure to prevent people from escaping from the inspection box 2. At the same time, the airbag 402 on the flip partition 401 expands under the operation of the inflator 7 to squeeze the space of the inspected person without harming his personal safety; 3. When the inspected person determines that there is danger, the flip partition 401 rotates and forms the following Figure 8 In this case, the detected person is restricted in the area formed by the unfolding of the flip partition 401 and the first curved plate 607 and the second curved plate 611. Figure 6 In the triangular area formed by the blocking structure shown, the airbag 402 continues to expand and pushes the person toward Figure 6 In the structure shown, the wiring harness 613 cooperates with the airbag 402 to be completely controlled by the inspector; 4. When the security device is impacted by a person, the flip partition 401 rotates through the electric push-pull device. Since the electric push-pull device belongs to the prior art, it is not disclosed. The flip partition 401 moves inward to form a triangle and fits through the magnetic sheet at the end. At the same time, the rotating partition 403 rotates under the same principle and is perpendicular to the inspection box 2, forming the same Figure 8 In the structure shown, the rotating partition 403 and the flip partition 401 form an effective defense line, and the reflector 3 faces the attacker to interfere with him. When the situation is serious, the rotating plate 405 can be rotated to make the side with the spikes 407 face the attacker. When not in use, the reflector 3 is fitted inward. At this time, the airbag 402 is inflated to squeeze the reflector 3 to stabilize the structure by squeezing and fixing, so that the device is more stable when not deployed; 5. Under certain extreme conditions, due to the presence of a certain amount of powder in the airbag 402, the rotating plate 405 can rotate and make the spikes 407 pierce the airbag 402. The powder forms a smoke bomb effect after the airbag 402 explodes. In another case, if dangerous personnel occupy the protection line, the airbag 402 can be pressurized by the inflator 7 to squeeze the personnel out, so that the defense line effect is lost and the occupying personnel lose the advantageous terrain.

[0048] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral one; it can be a mechanical connection, an electrical connection, or communication with each other; it can be a direct connection, or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0049] Obviously, the embodiments described above are only some embodiments of the present invention, rather than all embodiments. The preferred embodiments of the present invention are given in the accompanying drawings, but they do not limit the patent scope of the present invention. The present invention can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present invention more thorough and comprehensive. Although the present invention has been described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific embodiments, or to perform equivalent replacements for some of the technical features therein. Any equivalent structure made using the contents of the specification and drawings of the present invention, directly or indirectly used in other related technical fields, is also within the scope of patent protection of the present invention.

Claims

1. The face recognition security system based on big data is characterized by: It includes real-time data collection module, biometric data anonymous transaction module, face recognition module, security application module, data audit module, emotional intelligence module, data desensitization and reconstruction module and dynamic simulation generation module; The real-time data acquisition module is responsible for capturing facial image data. This module uses a high-resolution camera and image processing technology for preprocessing to improve the accuracy of face recognition; The biometric data anonymous transaction module provides biometric data transaction services. This module uses encryption technology and privacy protection algorithms to ensure the security and privacy of biometric data. The face recognition module performs face recognition and improves recognition accuracy by training face image data. This module supports biometric recognition technology and is used in security, access control and alarm prompts. The security application module issues a security alarm based on the identification results. The module can be integrated with the application control system to achieve automatic control and management of the application, and issue an alarm when an unauthorized person enters. The data audit module records the flow and use of biometric data to ensure data security. The module uses distributed storage technology and encryption technology for secure storage and access control, and provides real-time monitoring and recording functions; The emotional intelligence module analyzes people's micro-expressions and voice changes in biological characteristics, combined with artificial intelligence technology, to achieve intelligent recognition and management of user emotions. This module uses deep learning technology and natural language processing technology to analyze the user's emotional state.

2. The face recognition security system based on big data according to claim 1 is characterized in that: The biometric data anonymous transaction module ensures data security and privacy protection through encryption and anonymization technology. When uploading data, the AES-256 strong encryption algorithm is used to protect the original information, and it is securely transmitted through the SSL / TLS protocol. The platform implements the k-anonymity model and irreversible hash processing to isolate the association between personal identity and biometrics. In terms of transactions, a secure payment system is integrated and blockchain is used to improve transaction transparency and security. At the same time, audit monitoring is implemented to ensure compliance, protect user privacy and maintain market trust.

3. The face recognition security system based on big data according to claim 2 is characterized in that: The core principle of the face recognition module is the model-based approach, Hidden Markov Model (HMM), Active Shape Model (ASM) and Active Appearance Model (AAM). HMM processes time series data and predicts future trends of observed data by estimating hidden states. ASM focuses on locating and describing specific shapes from images and training shape feature points to capture the contours of objects. AAM combines shape and texture information to provide a more comprehensive description of image appearance for image matching and recognition tasks.

4. The face recognition security system based on big data according to claim 3 is characterized in that: The biometric data desensitization and reconstruction module performs deep desensitization processing on the original biometric data to ensure the privacy and security of the data and prevent sensitive information from being illegally obtained and abused. The user's data privacy is fully protected, and the availability and value of the data are also retained.

5. The face recognition security system based on big data according to claim 4 is characterized in that: The dynamic simulation generation module is used to generate virtual biometric data with a high degree of simulation, which is used to train, test and verify the biometric recognition system. Through the generative adversarial network (GAN) technology, virtual biometric data is generated. The data has a high degree of simulation and has perfect optimization and timely adjustment functions, which is used to improve the performance and effect of the system.

6. A face recognition security application based on big data, using the face recognition security system based on big data as claimed in claim 5, characterized in that: The invention comprises a base (1), the top of the base (1) is connected to a viewing box (2), a reflector (3) is arranged above the base (1), a security main body device (4) is arranged on the viewing box (2), a ramp (5) is fixedly connected to the base (1), a camera assembly device (6) is arranged on the base (1), and an inflator (7) is arranged above the base (1).

7. The face recognition security application based on big data according to claim 6 is characterized in that: The security main body device (4) comprises a flip partition (401) hinged on both sides of the inspection box (2), the inflator (7) is fixedly connected to an outer wall of one side of the flip partition (401), the reflector (3) is fixedly connected to the outer wall of the flip partition (401), the flip partition (401) is fixedly connected to an air bag (402), and both sides of the inspection box (2) are hinged with rotating partitions (403).

8. The face recognition security application based on big data according to claim 7 is characterized in that: The security main body device (4) further comprises a rectangular groove (404) formed on the rotating partition plate (403), a rotating plate (405) being rotatably connected to the rectangular groove (404) via a bearing and a rotating shaft, a plurality of fixing bars (406) being fixedly connected to an outer wall on one side of the rotating plate (405), and a plurality of spikes (407) being fixedly connected to the fixing bars (406).

9. The face recognition security application based on big data according to claim 8 is characterized in that: The camera assembly device (6) comprises two empty slots (601) formed on a base (1); a first electric push rod (602) is fixedly connected to the inner wall of each of the empty slots (601); a vertical rod (603) is fixedly connected to each of the first electric push rods (602); and a through slot (604) is formed on each of the vertical rods (603).

10. The face recognition security application based on big data according to claim 5 is characterized in that: The camera assembly device (6) further comprises a second electric push rod (605) fixedly connected to the outer wall of the vertical rod (603); a sliding block (606) is fixedly connected to the second electric push rod (605); the sliding block (606) is slidably connected to the through groove (604) via a sliding sheet; and a first arc-shaped plate (607) is rotatably connected to the sliding block (606) via a bearing.

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