Security defense method and system for video conference, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a security defense method and system for a video conference, and the method is applied to a computing power system, and the method comprises the steps: obtaining a biological feature image from a terminal, and obtaining a biological feature extraction instruction; performing artificial intelligence enhancement processing on the biological feature image according to the biological feature extraction instruction, and extracting biological feature information from the biological feature image after the artificial intelligence enhancement processing; and transmitting the biological characteristic information to a server, so that the server compares the biological characteristic information with biological characteristic sample information to obtain a comparison result, and performs security defense on the video conference according to the comparison result. According to the embodiment of the invention, the biological characteristic information is processed in a centralized manner, so that the requirement on terminal equipment is reduced, the security, authenticity and security defense flexibility of the video conference are enhanced, and large-scale application of a biological characteristic identification technology in a remote conference is facilitated.

Description

Technical Field

[0001] The present invention relates to the field of video conferencing technology, and in particular to a security defense method for video conferencing, a security defense system for video conferencing, a computing system, an electronic device, and a computer-readable storage medium. Background Art

[0002] With the rapid development of Internet technology and information and communication technology, video conferencing has become an important tool for remote communication and collaboration for modern enterprises, educational institutions, government departments and other organizations. However, with the popularization of video conferencing applications, how to ensure the security, authenticity and reliability of video conferencing has become a key issue that needs to be solved urgently. In video conferencing, especially those involving confidential information, how to ensure the authenticity of the speaker's identity and prevent third parties from maliciously tampering with or impersonating the speaker has become a severe challenge.

[0003] To address this problem, biometric technology has been gradually introduced into identity authentication for video conferencing. Biometric technology can verify an individual's identity by extracting and comparing their unique biological features. Common biological features include fingerprints, faces, voiceprints, irises, etc. Among them, iris recognition technology is considered to be one of the most reliable biometric means at present due to its high accuracy, low false recognition rate and difficulty in forging.

[0004] However, iris recognition technology usually requires high-resolution camera equipment to collect iris images, which makes it difficult to miniaturize the size of the equipment, limiting its portability and flexible deployment capabilities. Compared with fingerprint recognition or facial recognition equipment, iris collection equipment is more expensive, especially high-precision iris recognition cameras, which are expensive, affecting its promotion in the mass market.

[0005] In summary, under the need to ensure the authenticity of the speaker's identity in a video conference, iris recognition technology, as a biometric identification method in video conferences, has great application prospects due to its high security and difficult-to-copy characteristics. However, in view of the high cost of iris recognition equipment and the difficulty of image acquisition, further technological innovation and improvement are still needed to promote the large-scale application of iris recognition technology in video conferencing and other scenarios. Summary of the invention

[0006] In view of the above problems, embodiments of the present invention are proposed to provide a video conferencing security defense method, a video conferencing security defense system, a computing system, an electronic device, and a computer-readable storage medium that overcome the above problems or at least partially solve the above problems.

[0007] In order to solve the above problems, an embodiment of the present invention discloses a security defense method for video conferencing, which is applied to a computing system. The method includes: obtaining a biometric image from a terminal and obtaining a biometric extraction instruction; performing artificial intelligence enhancement processing on the biometric image according to the biometric extraction instruction, and extracting biometric information from the biometric image after the artificial intelligence enhancement processing; transmitting the biometric information to a server so that the server compares the biometric information with biometric sample information to obtain a comparison result, and performing security defense on the video conference according to the comparison result.

[0008] Optionally, performing artificial intelligence enhancement processing on the biometric image according to the biometric extraction instruction, and extracting biometric information from the biometric image after the artificial intelligence enhancement processing, includes: using an artificial intelligence model to perform one or more of the following artificial intelligence enhancement processing on the biometric image: denoising, super-resolution reconstruction, contrast enhancement, edge enhancement, artifact removal and geometric correction; graying the biometric image after artificial intelligence enhancement processing according to the biometric extraction instruction to obtain a grayscale image; performing threshold segmentation processing on the grayscale image based on binarization technology to determine a target area; optimizing the target area based on image morphological operations; extracting biometric information from the optimized target area using a region growing algorithm, and encoding the biometric information to obtain a biometric code.

[0009] An embodiment of the present invention also discloses a security defense method for video conferencing, which is applied to a server. The method includes: generating and transmitting a video stream acquisition instruction to a terminal so that the terminal collects a biometric image and transmits the biometric image to a computing system; generating and transmitting a biometric extraction instruction to the computing system so that the computing system performs artificial intelligence enhancement processing on the biometric image according to the biometric extraction instruction, and extracts biometric information from the biometric image after the artificial intelligence enhancement processing; acquiring the biometric information from the computing system, comparing the biometric information with the biometric sample information to obtain a comparison result; and performing security defense on the video conference according to the comparison result.

[0010] Optionally, before generating and transmitting the video stream acquisition instruction to the terminal, the method also includes: when the terminal registers with the server, or when the terminal does not log in to the server for the first time, obtaining a biometric sample image from the terminal, and forwarding the biometric sample image to the computing system; obtaining from the computing system the biometric sample information extracted by the computing system from the biometric sample image; and pairing and storing the terminal identification information of the terminal with the biometric sample information.

[0011] Optionally, the security defense of the video conference according to the comparison result includes: if the comparison result indicates that the biometric information is consistent with the biometric sample information, maintaining the normal operation state of the terminal in the video conference; if the comparison result indicates that the biometric information is inconsistent with the biometric sample information, interrupting the video conference and issuing a warning message.

[0012] Optionally, after interrupting the video conference and issuing a warning message, the method further includes: recording session data of the video conference, and initiating an access control mechanism and security monitoring measures for the video conference.

[0013] The embodiment of the present invention also discloses a computing system, which includes: an image and instruction acquisition module, which is used to acquire a biometric image from a terminal and acquire a biometric extraction instruction; a biometric extraction module, which is used to perform artificial intelligence enhancement processing on the biometric image according to the biometric extraction instruction, and extract biometric information from the biometric image after artificial intelligence enhancement processing; a biometric transmission module, which is used to transmit the biometric information to a server, so that the server compares the biometric information with the biometric sample information to obtain a comparison result, and performs security defense on the video conference according to the comparison result.

[0014] Optionally, the biometric extraction module includes: an artificial intelligence enhancement processing module, which is used to use an artificial intelligence model to perform one or more of the following artificial intelligence enhancement processing on the biometric image: denoising, super-resolution reconstruction, contrast enhancement, edge enhancement, artifact removal and geometric correction; a grayscale processing module, which is used to grayscale the biometric image after artificial intelligence enhancement processing according to the biometric extraction instruction to obtain a grayscale image; a binarization processing module, which is used to perform threshold segmentation processing on the grayscale image based on binarization technology to determine the target area; a morphological processing module, which is used to optimize the target area based on image morphological operations; a feature encoding module, which is used to extract biometric information from the optimized target area using a region growing algorithm, and encode the biometric information to obtain a biometric code.

[0015] An embodiment of the present invention also discloses a security defense system for video conferencing, which is applied to a server. The security defense system includes: an acquisition instruction generation and transmission module, which is used to generate and transmit video stream acquisition instructions to a terminal, so that the terminal collects a biometric image and transmits the biometric image to a computing system; an extraction instruction generation and transmission module, which is used to generate and transmit a biometric extraction instruction to the computing system, so that the computing system performs artificial intelligence enhancement processing on the biometric image according to the biometric extraction instruction, and extracts biometric information from the biometric image after the artificial intelligence enhancement processing; a biometric information comparison module, which is used to obtain the biometric information from the computing system, compare the biometric information with the biometric sample information to obtain a comparison result; and a video conferencing security defense module, which is used to perform security defense on the video conference according to the comparison result.

[0016] Optionally, the security defense system also includes: a sample image acquisition and forwarding module, which is used to register the terminal with the server before the acquisition instruction generation and transmission module generates and transmits the video stream acquisition instruction to the terminal, or when the terminal is not logging into the server for the first time, obtain a biometric sample image from the terminal and forward the biometric sample image to the computing power system; a biometric sample information acquisition module, which is used to obtain from the computing power system the biometric sample information extracted by the computing power system from the biometric sample image; and a sample and identification pairing storage module, which is used to pair and store the terminal identification information of the terminal with the biometric sample information.

[0017] Optionally, the video conference security defense module includes: a normal operation module, used to maintain the normal operation state of the terminal in the video conference if the comparison result indicates that the biometric information is consistent with the biometric sample information; an interruption warning module, used to interrupt the video conference and issue a warning message if the comparison result indicates that the biometric information is inconsistent with the biometric sample information.

[0018] Optionally, the security defense system further includes: a security control module, which is used to record the session data of the video conference and activate the access control mechanism and security monitoring measures of the video conference after the interruption warning module interrupts the video conference and issues a warning message.

[0019] An embodiment of the present invention also discloses an electronic device, comprising: one or more processors; and one or more machine-readable media having instructions stored thereon, which, when executed by the one or more processors, enables the electronic device to execute the security defense method for video conferencing as described above.

[0020] The embodiment of the present invention further discloses a computer-readable storage medium, which stores a computer program that enables a processor to execute the security defense method for video conferencing as described above.

[0021] The embodiments of the present invention include the following advantages:

[0022] The security defense solution for video conferencing provided by an embodiment of the present invention is applied to a computing system. The computing system obtains a biometric image from a terminal and obtains a biometric extraction instruction. Then, the biometric image is enhanced by artificial intelligence (AI) according to the biometric extraction instruction, and biometric information is extracted from the biometric image after the AI ​​enhancement processing. Next, the biometric information is transmitted to a server so that the server compares the biometric information with the biometric sample information to obtain a comparison result, and performs security defense on the video conference according to the comparison result.

[0023] By introducing biometric technology, the embodiment of the present invention can continuously authenticate the identity of the speaker during the conference, ensure that the speaker is a real authorized user, prevent malicious tampering or impersonation by a third party, and effectively improve the security and authenticity of the video conference. The computing system automatically obtains the biometric image from the terminal, and performs AI enhancement processing on the biometric image based on the server instruction and extracts the biometric information, so that real-time identity authentication can be automatically performed during the video conference. This not only improves the efficiency of identity authentication, but also ensures the continuous confirmation of the speaker's identity, effectively preventing illegal users from taking over the video stream in the middle of the meeting. The video conference is automatically defended against security based on the comparison results of the biometric verification, and the automated process reduces the need for manual intervention, and improves the flexibility and security response speed of the conference security defense. The background technology mentions that iris recognition equipment is relatively complex and has high maintenance costs. The embodiment of the present invention reduces the demand for terminal equipment complexity by processing biometric images through the computing system, concentrates the processing of biometric recognition on the computing system, and reduces the demand for high-end equipment on the terminal. It helps to reduce the overall deployment cost and equipment complexity, solves the technical defects of high cost and difficult promotion of iris acquisition equipment in the background technology, and helps to promote the large-scale application of iris recognition technology in video conferencing. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is a flowchart of the steps of a security defense method for a video conference according to an embodiment of the present invention;

[0025] Figure 2 is a flowchart of another method for protecting the security of a video conference according to an embodiment of the present invention;

[0026] Figure 3It is a schematic diagram of the principle of a video conferencing anti-hacker attack solution based on a computing power server according to an embodiment of the present invention;

[0027] Figure 4 It is a schematic diagram of a process of extracting iris feature information based on a computing power server according to an embodiment of the present invention;

[0028] Figure 5 is a structural block diagram of a computing system according to an embodiment of the present invention;

[0029] Figure 6 It is a structural block diagram of a security defense system for video conferencing according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0031] The video conference security defense solution proposed in the embodiment of the present invention introduces biometric recognition technology (such as iris recognition technology) and uses a computing system to automatically and in real time verify the identity of the speaker to ensure that the speaker in the meeting is always an authorized real user. The specific operation includes: first, obtaining a biometric image from a terminal device and transmitting it to a computing system; then, the computing system performs AI enhancement on the biometric image and extracts biometric information (such as iris features) according to the instructions issued by the server, and compares it with the sample information stored in the server. According to the comparison results, the process of the video conference is automatically defended to ensure that the meeting proceeds normally when the identity match is successful, and the meeting is interrupted and a warning is issued if the match fails. At the same time, the biometric comparison information is saved to facilitate subsequent audits and security defense. By centrally processing biometric information, this solution reduces the requirements for terminal devices, enhances the security, authenticity and security defense flexibility of video conferences, and contributes to the large-scale application of biometric recognition technology in remote conferences.

[0032] Reference Figure 1 , shows a flowchart of the steps of a security defense method for video conferencing according to an embodiment of the present invention. The security defense method for video conferencing is applied to a computing system, and the security defense method for video conferencing may specifically include the following steps:

[0033] Step 101, obtaining a biometric image from a terminal and obtaining a biometric extraction instruction.

[0034] In the embodiment of the present invention, during the video conference security defense process, obtaining the biometric image of the participant from the terminal and receiving the biometric extraction instruction from the server not only involves the collection of image data, but also the specific operation of how to initiate the biometric extraction. The biometric image generally refers to the visual data of the iris image, facial image or other biometrics, and in this embodiment, iris recognition is the main biometric identification method used.

[0035] Specifically, the terminal equipment of the video conference, such as a computer, a smart phone, or a dedicated iris recognition camera, will be responsible for collecting biometric images of the participants. Generally, iris collection requires images with higher resolution, so the terminal equipment must have the corresponding hardware capabilities. In order to ensure image quality, participants may be required to cooperate in adjusting the viewing angle, lighting conditions, etc. until an image that meets the recognition requirements is collected. For example, when an employee participates in a company video conference using a laptop with a high-resolution camera, the system will prompt him to look directly at the camera to collect his iris image. However, the embodiments of the present invention do not have special hardware parameter requirements for the terminal equipment, and it is not necessary to use a terminal equipment dedicated to collecting iris images. The requirements for the terminal equipment of the video conference are relatively low.

[0036] At the same time, the server will generate a biometric extraction instruction based on the security policy of the video conference and send the biometric extraction instruction to the computing system. This instruction contains specific biometric extraction task requirements, such as specifying the extraction of iris features and verifying the identity of a specific terminal user. The instruction may be customized according to the needs of different video conferences. For example, in a high-security conference, the server may require higher image resolution and more accurate biometric extraction algorithms.

[0037] The key to this process is to ensure the accuracy of the biometric image and the stability of the system communication. The server needs to have real-time processing capabilities, be able to efficiently issue biometric feature extraction instructions, and ensure the security of data transmission between systems to prevent data tampering or leakage during transmission. During the image acquisition stage, if image acquisition fails due to network problems or terminal equipment failure, the system will prompt the user to re-operate to ensure that subsequent biometric extraction is accurate.

[0038] Step 102, performing artificial intelligence enhancement processing on the biometric image according to the biometric extraction instruction, and extracting biometric information from the biometric image after the artificial intelligence enhancement processing.

[0039] In an embodiment of the present invention, the computing system performs AI enhancement processing on the previously collected biometric image according to the biometric extraction instruction sent by the server, and extracts specific biometric information from it. For iris recognition technology, biometric information mainly refers to the unique texture information of the iris, which can be used for identity verification after a series of processing.

[0040] The computing system receives the biometric image from the terminal and then performs preprocessing operations according to the extraction instructions. Preprocessing usually includes grayscale, denoising (such as using a Gaussian filter), and binary segmentation of the image. These steps are designed to enhance the contrast and clarity of the image, making the subsequent iris feature extraction more accurate. For example, after the iris image of a company's employee is grayscaled, its texture contrast is improved, making the subtle iris texture more obvious.

[0041] After image preprocessing, the computing system performs morphological operations to identify the iris area and distinguish the iris from surrounding eye structures (such as the pupil and the white of the eye) through a region growing algorithm. The region growing algorithm can start from an initial point in the image and gradually expand to the entire iris area based on the similarity of pixels, thereby effectively extracting the outline of the iris.

[0042] Next, the computing system will use a series of feature extraction algorithms to obtain the unique texture information of the iris from the iris image. The texture of the iris is very complex and difficult to replicate, which makes the extraction of iris features the core of recognition. Commonly used extraction algorithms include Gabor filters, fast Fourier transforms, etc., which can convert complex iris texture information into a unique feature vector that can be used for identity authentication.

[0043] In order to ensure the high accuracy of the extracted features, the computing system will also detect image distortion, noise interference and other issues through algorithms and make corresponding corrections. For example, if there is slight uneven lighting or camera distortion in the image, the computing system can repair it through the image distortion correction algorithm to ensure that the extracted iris feature information is accurate.

[0044] Finally, the computing system generates a set of biometric data (such as iris feature vectors) that represent the unique identity information of the participants. This data will be sent back to the server as the basis for subsequent identity verification. Through this process, the computing system successfully transforms complex image processing and feature extraction into a set of accurate biometric information, providing a solid technical foundation for the security of video conferencing.

[0045] Step 103, transmitting the biometric information to the server, so that the server compares the biometric information with the biometric sample information to obtain a comparison result, and performs security defense on the video conference according to the comparison result.

[0046] In the embodiment of the present invention, the computing system has extracted biometric information such as iris, and it is necessary to transmit this information back to the server for comparison and final authentication results. This process is crucial to the entire video conference security defense, because the server is not only responsible for processing the comparison operation, but also takes corresponding security defense measures based on the comparison results, such as allowing the meeting to continue or interrupting the meeting.

[0047] In actual application, the computing system transmits the extracted biometric information (such as iris feature vectors) to the server in a secure and encrypted manner. This transmission process needs to ensure the integrity and confidentiality of the data, and usually uses encryption protocols such as Transport Layer Security (TLS) to prevent the data from being stolen or tampered with during transmission. After receiving the biometric information, the server compares it with the biometric sample information pre-stored in the database. Biometric sample information is usually collected and stored when the user registers. The information is strictly protected and encrypted to ensure that it is not illegally accessed.

[0048] The matching process usually uses a similarity calculation algorithm, such as the Hamming distance algorithm, to measure the similarity between the extracted iris features and the sample information. The server will set a similarity threshold, and only when the similarity reaches a certain level will the matching be considered successful, and then the user's identity will be confirmed. For example, if the similarity between an employee's iris features and the pre-stored sample information reaches more than 95%, the matching result will be considered successful. On the contrary, if the similarity is low, the identity verification will be considered failed.

[0049] The result of the comparison will directly affect the security defense measures of the video conference. If the comparison result shows that the identity matches successfully, the server will allow the participant to continue to participate in the meeting and the video stream will not be interrupted. However, if the comparison fails, the server will take a series of security measures. First, the server may interrupt the participant's video stream and notify the conference security defender or security team. In addition, the server can also automatically generate an alarm notification to remind relevant personnel to review the security of the meeting and take appropriate remedial measures, such as re-verifying the user's identity or initiating an emergency response mechanism.

[0050] This process not only ensures the security of identity authentication in video conferencing, but also has high real-time and automation characteristics, allowing the server to respond quickly when identity authentication is abnormal, preventing the content of the meeting from being maliciously tampered with or leaked. For example, in a high-level meeting of a company, if a participant's iris verification fails, the server will immediately interrupt the participant's speaking rights and issue a warning to protect the meeting progress of other legitimate participants. Through this security defense mechanism, the overall security of video conferencing is effectively guaranteed.

[0051] The security defense solution for video conferencing provided by an embodiment of the present invention is applied to a computing system. The computing system obtains a biometric image from a terminal and obtains a biometric extraction instruction. Then, the biometric image is subjected to artificial intelligence enhancement processing according to the biometric extraction instruction, and biometric information is extracted from the biometric image after artificial intelligence enhancement processing. Next, the biometric information is transmitted to a server so that the server compares the biometric information with the biometric sample information to obtain a comparison result, and performs security defense on the video conference according to the comparison result.

[0052] By introducing biometric technology, the embodiment of the present invention can continuously authenticate the identity of the speaker during the conference, ensure that the speaker is a real authorized user, prevent malicious tampering or impersonation by a third party, and effectively improve the security and authenticity of the video conference. The computing system automatically obtains the biometric image from the terminal, and performs AI enhancement processing on the biometric image based on the server instruction and extracts the biometric information, so that real-time identity authentication can be automatically performed during the video conference. This not only improves the efficiency of identity authentication, but also ensures the continuous confirmation of the speaker's identity, effectively preventing illegal users from taking over the video stream in the middle of the meeting. The video conference is automatically defended against security based on the comparison results of the biometric verification, and the automated process reduces the need for manual intervention, and improves the flexibility and security response speed of the conference security defense. The background technology mentions that iris recognition equipment is relatively complex and has high maintenance costs. The embodiment of the present invention reduces the demand for terminal equipment complexity by processing biometric images through the computing system, concentrates the processing of biometric recognition on the computing system, and reduces the demand for high-end equipment on the terminal. It helps to reduce the overall deployment cost and equipment complexity, solves the technical defects of high cost and difficult promotion of iris acquisition equipment in the background technology, and helps to promote the large-scale application of iris recognition technology in video conferencing.

[0053] In an exemplary embodiment of the present invention, an implementation method of performing artificial intelligence enhancement processing on a biometric image according to a biometric extraction instruction and extracting biometric information from the biometric image after artificial intelligence enhancement processing is to use an artificial intelligence model to perform one or more of the following artificial intelligence enhancement processing on the biometric image: denoising, super-resolution reconstruction, contrast enhancement, edge enhancement, artifact removal and geometric correction; graying the biometric image after artificial intelligence enhancement processing according to the biometric extraction instruction to obtain a grayscale image; performing threshold segmentation processing on the grayscale image based on binarization technology to determine the target area; optimizing the target area based on image morphological operations; extracting biometric information from the optimized target area using a region growing algorithm, and encoding the biometric information to obtain a biometric code.

[0054] In actual application, the computing system uses deep learning models to remove noise from images to ensure that biometric information is not interfered with by noise. For example, a convolutional neural network (CNN) or a generative adversarial network (GAN) is used to automatically filter noise. When the image resolution is low, AI technology is used to improve the clarity and details of the image. For example, the details of the biometric image are magnified through the residual network (ResNet) to ensure that the subtle iris texture or fingerprint pattern can be clearly captured. The contrast in the image is automatically optimized through the AI ​​algorithm, so that the difference between the biometric part (such as the iris or pupil) and the background is more obvious, which is helpful for subsequent feature extraction. AI technology, such as edge detection, is combined with a deep learning model to strengthen the edges of the biometric area, making the boundaries of feature extraction clearer. De-artifacting algorithms, such as generative adversarial networks, are used to remove image artifacts caused by transmission or compression to ensure the authenticity of the image. Correcting geometric distortion caused by camera angle or lens distortion allows the biometric area in the image to be restored to its true form.

[0055] The computing system grayscales the AI-enhanced biometric image based on the received biometric extraction instructions. Grayscale is an important step in image preprocessing, which aims to convert color images into grayscale images to reduce the complexity and processing burden of the image. Color images usually contain multiple channels (such as RGB: red, green and blue channels), while grayscale images only retain one intensity channel, representing the brightness of the pixel. For iris images, grayscale processing can highlight the texture features of the iris and eliminate the interference of color information on subsequent image processing steps. For example, in the iris images of company employees, after grayscale, the unique texture of the iris will be clearer and more significant, which is conducive to the subsequent feature extraction.

[0056] Next, the computing system uses a threshold segmentation method based on binarization technology to process the grayscale image to determine the target area. Binarization is to divide the pixels in the grayscale image into two categories: foreground (target) and background. By setting a threshold, pixels above the threshold are regarded as foreground, and pixels below the threshold are regarded as background. For iris recognition, the foreground is usually the iris area, while the background is the pupil and the white of the eye. The choice of threshold is very critical, which directly determines the accuracy of the iris area. For example, during an employee's video conference, the computing system may dynamically adjust the threshold according to the collected lighting conditions to ensure the correct separation of the iris area. Through this threshold segmentation method, the target area in the image, that is, the accurate outline of the iris, can be efficiently identified.

[0057] After the target area is determined, the computing system will optimize the target area based on image morphological operations. Image morphological operations are a technology that analyzes and modifies the shape of an image. Common operations include dilation, erosion, opening operations, and closing operations. These operations can eliminate noise in the image, fill in small gaps at the edge of the iris, and further improve the accuracy of feature extraction. For example, if there are some small noise points in the iris image, morphological operations can remove these points, thereby optimizing the boundaries of the entire iris area. This processing step effectively improves the integrity and quality of the target area and ensures the accuracy of subsequent feature extraction.

[0058] After the target area is optimized, the computing system will use the region growing algorithm to extract biometric information from the optimized target area. The region growing algorithm is an image segmentation method based on pixel connectivity. It usually starts from a seed point and gradually expands the area according to the similarity of pixels until the entire iris area is covered. This algorithm can accurately identify the boundaries and internal textures of the iris, thereby extracting biometric information that represents the uniqueness of the iris. For example, in a video conference, after an employee's iris image is extracted through the region growing algorithm, the computing system can obtain its unique iris texture structure, thereby ensuring high accuracy of iris recognition.

[0059] Finally, the computing system encodes the extracted biometric information to generate a biometric code. This process is similar to compressing complex biometric information into a unique set of codes for subsequent comparison and storage. The biometric code is a digital expression of feature information, usually consisting of a set of binary digits or other compact data formats, which is used to compare with the biometric sample information stored in the server. For example, after an employee's iris feature is encoded, a unique iris feature code is generated, and the system can determine the employee's identity by comparing this feature code.

[0060] The AI ​​enhanced processing of the embodiment of the present invention effectively solves the problems of image noise, low resolution, blur and so on caused by camera quality or environmental conditions, making the extraction of biometric features more accurate. Through grayscale processing and threshold segmentation, the image information can be effectively simplified, important biometric features can be highlighted, and processing efficiency can be improved. The optimization processing based on image morphology ensures the removal of image noise and the optimization of boundaries, thereby improving the accuracy of biometric extraction. In addition, the application of the region growing algorithm ensures the complete extraction of biometric information, especially in iris recognition, it can accurately segment the iris area and extract key features. The encoding processing enables the biometric information to be efficiently stored and quickly compared, improving the real-time response capability.

[0061] Reference Figure 2 , shows a flowchart of another video conference security defense method according to an embodiment of the present invention. The video conference security defense method is applied to a server, and the video conference security defense method may specifically include the following steps:

[0062] Step 201, generate and transmit a video stream acquisition instruction to a terminal, so that the terminal collects a biometric image and transmits the biometric image to a computing system.

[0063] In an embodiment of the present invention, the server generates and transmits a video stream acquisition instruction to the terminal. This process ensures that each device participating in the conference can collect the user's biometric image, such as an iris image, a facial image, etc. The generation of the video stream acquisition instruction is based on the real-time needs of the video conference. In particular, in situations involving security and speaker identity authentication, the server must ensure that the terminal device acquires the biometric image in a timely and accurate manner.

[0064] Specifically, when a video conference starts, the server sends a request to each participant's terminal to start capturing the participant's biometrics. For example, in a high-level corporate meeting, the server can generate instructions to require the terminal to capture the iris image of each participant. This iris image will be used for subsequent identity verification to ensure that no unauthorized speakers can insert or tamper with the content of the meeting.

[0065] After the video stream acquisition instruction is transmitted to the terminal, the terminal device will execute the instruction and start collecting the user's biometric image. Here, the device may continuously capture through the camera and ensure that the quality of the collected image is clear enough for subsequent biometric extraction and comparison. During the execution process, the terminal device also needs to transmit these collected biometric images back to the computing system in real time.

[0066] For example, when a company holds a shareholders' meeting, through this step, the server will require the devices of the shareholders' meeting participants to collect their iris images and transmit them to the backend computing system. In this way, the identity of each shareholder can be reliably verified throughout the meeting, preventing a third party from maliciously impersonating or replacing the shareholder.

[0067] Step 202, generate and transmit a biometric extraction instruction to the computing system, so that the computing system performs artificial intelligence enhancement processing on the biometric image according to the biometric extraction instruction, and extracts biometric information from the biometric image after artificial intelligence enhancement processing.

[0068] In an embodiment of the present invention, after completing the collection and transmission of the biometric image, the server generates and transmits a biometric extraction instruction to the computing system. The main purpose of this step is to process the biometric image through the computing system and extract biometric information that can represent the identity of an individual.

[0069] After receiving the biometric extraction instruction from the server, the computing system will start processing the collected biometric images. First, the biometric image will go through a series of preprocessing steps, including AI enhancement processing, grayscale processing, noise filtering, and image enhancement, to ensure that the effective information in the image can be retained to the maximum extent. Next, the computing system will apply the biometric extraction algorithm to identify and extract the key feature points in the biometric image. For example, in iris recognition, the computing system will focus on extracting the texture features of the iris, because the complexity and uniqueness of the iris texture makes it one of the most difficult biometric features to forge.

[0070] Taking a practical application as an example, in a security defense meeting of a large enterprise, the server will transmit extraction instructions to the computing system, requesting feature extraction of the iris image of the shareholder. The computing system will use image processing algorithms to extract unique iris textures from the iris image, which will be converted into biometric information and prepared for subsequent identity verification.

[0071] This step ensures that the identity of each participant can be verified through the uniqueness of biometrics, preventing any form of identity theft or impersonation. In addition, the computing system is efficient in processing biometrics, ensuring real-time and smoothness during the meeting.

[0072] Step 203, obtaining biometric information from the computing system, and comparing the biometric information with the biometric sample information to obtain a comparison result.

[0073] In the embodiment of the present invention, after the computing system extracts the biometric information, the server will obtain the biometric information from the computing system and compare it with the biometric sample information stored in the server in advance. This process is the core link of identity authentication. The comparison result determines the subsequent measures of video conference security defense and is the key to ensuring the security of the meeting and the authenticity of the speaker.

[0074] The biometric sample information in the server is usually collected and stored when the user registers. Taking iris recognition as an example, when a user uses the video conferencing system for the first time, the server will ask the user to provide an iris image sample. The sample will be stored in the server database in an encoded form for subsequent comparison. During the meeting, when the server obtains the newly extracted biometric information, it will call the biometric comparison algorithm to compare one by one. If the feature information matches, it means that the user's identity is authentic and the meeting can continue; if it does not match, the system will issue a warning and take corresponding measures.

[0075] For example, in a telemedicine conference, the doctor's iris sample information has been stored in the server in advance. When the doctor logs in and participates in the conference, the server obtains his current iris feature information from the computing system and performs a real-time comparison. If the comparison results show that the identity is consistent, the doctor can continue to communicate with the patient remotely and provide diagnosis and treatment.

[0076] This step ensures that the identities of meeting participants are authentic and valid through biometric comparison, preventing malicious tampering or unauthorized persons from inserting themselves into the meeting.

[0077] Step 204: Perform security defense on the video conference according to the comparison result.

[0078] In an embodiment of the present invention, the server takes corresponding security measures for the video conference based on the comparison results. This step determines the further direction of the video conference and ensures the security and smooth progress of the conference. If the comparison results are consistent, indicating that the identities of the participants are correct, the server will allow the video conference to continue without taking any additional actions. If the comparison results are inconsistent, it means that there may be security risks such as identity fraud and tampering. The server will immediately interrupt the meeting and issue a security warning.

[0079] For example, in a corporate strategic meeting, if the iris information of a participant does not match the sample information stored in the server, the server will immediately suspend the meeting to prevent the participant from continuing to participate. The server will then send an alert to the meeting organizer to inform them of possible identity theft and provide further processing measures.

[0080] In addition, the server may also record detailed information about the failed match, including the reason for the match failure, time, and detailed information about the relevant equipment, for subsequent audits and investigations. In some high-level meetings, the server may also trigger further security measures, such as restricting access rights to suspicious terminals or even contacting the security team for emergency processing.

[0081] Through this security defense measure, the server can effectively prevent security issues such as identity fraud, ensuring the information security and authenticity of the participants' identities during the meeting.

[0082] In an exemplary embodiment of the present invention, an implementation method before generating and transmitting a video stream acquisition instruction to a terminal is to obtain a biometric sample image from the terminal and forward the biometric sample image to a computing system when the terminal registers with the server or when the terminal does not log in to the server for the first time; obtain the biometric sample information extracted from the biometric sample image by the computing system from the computing system; and pair and store the terminal identification information of the terminal with the biometric sample information. This implementation method describes an important preparation stage before generating and transmitting a video stream acquisition instruction, namely, the registration of the device and the collection and storage of biometric samples. This stage not only provides an accurate identity authentication basis for subsequent video conferences, but also effectively improves the security of the conference and the authenticity of the identities of the participants.

[0083] In actual application, when a terminal device connects to the server for the first time, the server will ask the terminal to register. This registration process usually involves the collection of the user's basic identity information and biometrics, such as the user's iris image, fingerprint, or facial image. In order to ensure the accuracy of biometric collection, the server may prompt the user to adjust the posture multiple times or collect images from different angles. Taking iris recognition as an example, the user needs to aim at the terminal's camera and collect a high-resolution iris image, so that the details of the iris texture can be captured, ensuring that the computing system can extract high-precision biometric sample information.

[0084] After the collection is completed, the terminal sends these biometric images to the server. After the server receives the biometric image, it will forward it to the computing system in the background. The main function of the computing system is to process and analyze the biometric image through complex algorithms. The computing system will first pre-process the biometric image, including grayscale, denoising, edge detection and other steps, and then extract the biometric information through the feature extraction algorithm. For example, in iris recognition, the computing system will extract the unique iris texture information from the iris image and encode it into biometric sample information. This information is usually stored in a digital form to facilitate subsequent comparison and verification.

[0085] Next, the server will obtain the extracted biometric sample information from the computing system and store it in pairs with the unique identification information of the terminal. The terminal identification information is usually the unique identifier of the device, such as MAC address, device serial number, etc. The purpose of storing the terminal identification information in pairs with its corresponding biometric sample information is to be able to quickly and effectively identify the legitimate user identity of each terminal in future video conferences. For example, in a subsequent meeting, when a terminal connects to the server again, the server can immediately determine whether the user of the device is a legitimate conference participant by comparing the real-time collected biometrics of the device with the stored sample information.

[0086] Let's take an example to illustrate: In a multinational company executive meeting, when each terminal device participating in the meeting first accesses the server, the server requires each executive to collect his or her iris image and extract his or her iris features through the computing system. The server pairs these iris feature information with their respective terminal devices and stores them. When these executives attend the meeting again in the future, there is no need to collect iris images again. The server can determine the authenticity of the identity by comparing the real-time collected iris image with the stored sample information. This greatly improves the efficiency of the meeting while ensuring that the identities of the meeting participants are authentic and reliable.

[0087] By pre-collecting and storing biometric sample information, the embodiment of the present invention allows the server to quickly perform identity authentication in subsequent video conferences, reducing the delay and inconvenience caused by identity authentication during the conference. By storing the terminal's identification information in pairs with the biometric information, the server can effectively prevent the terminal from being used by unauthorized users. This means that even if a hacker gains control of a device, he or she cannot pretend to be a legitimate user of the device to attend a meeting because the server will verify the user's identity through biometric comparison. In addition, the high security of the storage of biometric samples and the subsequent comparison process ensures the accuracy and uniqueness of user identity authentication and reduces the risk of identity fraud and tampering.

[0088] In an exemplary embodiment of the present invention, one implementation method of performing security defense on a video conference according to the comparison result is that if the comparison result indicates that the biometric information is consistent with the biometric sample information, the normal operation of the terminal in the video conference is maintained; if the comparison result indicates that the biometric information is inconsistent with the biometric sample information, the video conference is interrupted and a warning message is issued. The implementation method of performing security defense on a conference according to the comparison result includes two scenarios: comparison success and comparison failure. The server takes corresponding measures according to the comparison result to ensure the smooth progress and security of the conference.

[0089] The first scenario is that the comparison result shows that the biometric information is consistent with the biometric sample information. In this case, the server will consider the current participant to be a legitimate user, and therefore keep the terminal in normal operation in the video conference. For example, in iris recognition, if the iris information collected in real time matches the iris sample information stored in the server, the server will allow the terminal to continue to maintain the connection, and the user can speak normally, watch the meeting content, and participate in the discussion. This process is automated, and users are usually not aware of the background identity authentication process. Through this continuous biometric comparison, the server ensures the continuity of the participant's identity and prevents identity tampering or replacement.

[0090] For example, in a video conference of a large company's board of directors, the iris features of each director have been pre-entered into the server. At the beginning of the meeting, the server will continuously collect their iris images and compare them to ensure that they are legitimate participants. Assuming that a director's iris matches the sample, the server will allow him to continue speaking, and the entire meeting process will not be affected. This mechanism ensures that the participants of the meeting are always their true identities, thereby preventing information leakage or threats to the security of the meeting.

[0091] The second scenario is that the comparison result shows that the biometric information is inconsistent with the biometric sample information. In this case, the server will consider that there is an abnormality in the identity of the current terminal user, and it may be that an unauthorized user is trying to impersonate a legitimate participant. In order to ensure the security of the meeting, the server will immediately disconnect the terminal from the video conference and issue a warning message. The warning message can be sent to the meeting host, administrator, and security team so that they can quickly take further countermeasures. Specifically, the server will send an alert to the relevant personnel via email, SMS or instant messaging tools to inform them that a terminal identity authentication failed and there is a potential security risk in the meeting.

[0092] For example, a government department held a meeting involving sensitive data. During the meeting, the server detected that the iris information of a participant did not match the sample information stored. To prevent unauthorized users from continuing to participate, the server immediately disconnected the terminal and sent an alert to the meeting host. The host can quickly decide whether to suspend the meeting, check the source of the terminal, and take further security measures. This real-time response mechanism ensures the security of the meeting and prevents the leakage of sensitive information.

[0093] By comparing biometric information in real time, the server of the embodiment of the present invention can quickly detect unauthorized users and take measures to interrupt their connection. This greatly improves the security of video conferencing, especially in meetings involving confidential information, which can prevent information leakage and intrusion by lawbreakers. The server can continuously authenticate each participant during the meeting to ensure the authenticity of their identity. This means that even if someone tries to change their identity in the middle of the meeting, the server can detect and respond in time to maintain the high security and reliability of the meeting. Through automated biometric comparison and processing procedures, the workload of conference administrators is reduced. The server can automatically decide whether to maintain or disconnect the connection based on the comparison results. The administrator only needs to handle abnormal situations to avoid human errors. When the identity comparison fails, the server can quickly issue an alarm, notify the relevant person in charge and disconnect the connection. This rapid response mechanism ensures that the security risks of the meeting can be controlled at the first time and effectively prevent the expansion of security incidents.

[0094] In an exemplary embodiment of the present invention, after interrupting a video conference and issuing a warning message, an implementation method is to record the session data of the video conference, start the access control mechanism and security monitoring measures of the video conference, etc. This implementation method is intended to address the security and defense issues after the video conference is interrupted, and through multi-level security mechanisms and data recording, ensure the integrity and security of the conference to prevent unauthorized users from continuing to interfere with the conference. After the video conference is interrupted and a warning message is issued, the server will immediately take a series of security measures, including recording the session data of the conference, starting the access control mechanism, and strengthening security monitoring to ensure the effectiveness and security of subsequent processing.

[0095] In actual application, after a video conference is interrupted, the server will record the key information of the current meeting in detail, including the start and end time of the meeting, the list of participants, the content of the speech, the video frame, and the results of the biometric comparison. This data will be securely stored in the server for subsequent security audits and analysis. For example, in a highly confidential meeting held by a government department, if the server detects that a participant's identity authentication fails and interrupts the meeting connection, the server will automatically save the participant's speech record and all session data before the meeting was interrupted. This data is very critical in subsequent investigations, helping to analyze potential security vulnerabilities, determine the time when the problem occurred, and evaluate sensitive information that may be exposed in the meeting.

[0096] After the video conference is interrupted, in order to prevent unauthorized users from continuing to try to access or interfere with the meeting, the server will temporarily lock or disable the terminal related to the authentication failure, prohibiting it from connecting to the meeting again. The access control mechanism can further strengthen the authentication process of other participants, such as requiring re-entry of biometrics, strengthening two-factor authentication (2FA), or allowing the administrator to manually authorize each participant to re-enter the right. Taking a board meeting of a large company as an example, if a participant's biometric information verification fails, the server will immediately lock the participant's account and require other participants to re-verify. This measure ensures that participants in the meeting are always in a safe state and avoid potential malicious attacks or unauthorized access.

[0097] In addition to access control, the server will also initiate security monitoring measures, which is an important step to ensure that the video conference is not further invaded or interfered with. The server will strengthen the monitoring of data transmission, security protocols, and network traffic throughout the meeting to ensure that there is no abnormal network activity or data leakage. For example, in meetings in sensitive industries such as medicine and finance, security monitoring measures may include real-time network traffic monitoring, upgrades to encrypted communication protocols (such as TransportLayer Security, or TLS), and real-time encryption of all communication data. In addition, the server will detect any possible abnormal behavior, such as multiple failed login attempts, suspicious access requests from different locations, etc., to ensure the security of the meeting environment. For example, in a cross-border video conference in the financial industry, if the server detects that a terminal has attempted to log in multiple times and failed authentication, the server will record these suspicious behaviors and upgrade the security protocol to prevent potential network attacks.

[0098] By recording complete session data, the server of the embodiment of the present invention ensures that all information during the meeting is saved for subsequent audit or analysis. This is particularly important in conference scenarios with high security requirements, such as government, corporate meetings or sensitive discussions involving confidential content. After the meeting, these data can help administrators and security teams analyze the reasons for the interruption in detail, evaluate potential security threats, and formulate corresponding preventive measures. By starting access control, the server can immediately lock the relevant terminal after the user identity authentication fails to prevent unauthorized users from accessing the meeting again. This instant access security defense mechanism not only improves the security of the meeting, but also reduces the risk of the spread of security threats, ensuring the smooth progress of the meeting. By starting the security monitoring mechanism, the server can comprehensively monitor the entire network environment after the meeting is interrupted to ensure that there are no potential security vulnerabilities. This real-time monitoring method can detect abnormal behavior in a timely manner and prevent further intrusion or data leakage. For example, measures such as network traffic monitoring and encryption protocol upgrades can effectively prevent hacker attacks and information leakage, and further ensure the communication security of the meeting.

[0099] Based on the above description of a video conference security defense method embodiment, the following introduces a video conference anti-hacker attack solution based on a computing power server. Figure 3 , shows a schematic diagram of the principle of a video conferencing anti-hacker attack solution based on a computing power server according to an embodiment of the present invention. The video conferencing anti-hacker attack solution based on a computing power server involves a visual network terminal, a visual network server and a computing power server.

[0100] The visual networking terminal joins the meeting, and the iris collection module in the visual networking terminal establishes a communication connection with the computing power server and the visual networking server.

[0101] When the visual networking terminal and the visual networking server are continuously connected, the visual networking server sends a video stream acquisition instruction to the visual networking terminal. After the visual networking terminal parses the instruction, it sends the captured frame image of the person speaking in the video conference to the computing power server.

[0102] The computing server receives the frame images sent by the visual network terminal, performs AI enhancement processing on the frame images, extracts iris information from the images, processes the iris information, and sends the extracted iris feature information to the visual network server.

[0103] The visual network server receives the iris feature information sent by the visual network terminal, and compares it with the iris feature information stored in the visual network server to obtain a comparison result.

[0104] If the comparison results are consistent, the video conference will continue; if the comparison results are inconsistent, the video conference will be interrupted and a warning will be issued.

[0105] Reference Figure 4 , showing a schematic diagram of a process of extracting iris feature information based on a computing power server in an embodiment of the present invention.

[0106] Step 401, obtaining a frame image.

[0107] Acquiring frames is the first step in iris feature extraction. In video conferencing applications, frames are usually captured in real time by the camera in the terminal device. The camera will continuously capture the eye area of ​​the participants to generate continuous video frames. These frames contain the iris information of the participants, but in the original state, the frames may contain too much background information or noise, which is not suitable for direct iris feature extraction. Therefore, multiple frames are first acquired to ensure that there is enough information for subsequent image processing.

[0108] Step 402, grayscale processing is performed on the frame image to obtain a grayscale image.

[0109] After the frame is acquired, the next step is to convert the color frame into a grayscale image. Grayscale processing is to convert each pixel value of the color image into a single grayscale value, thereby reducing the complexity of the image. In a grayscale image, each pixel has only one brightness value, usually ranging from 0 to 255, where 0 represents pure black and 255 represents pure white, and the numbers in between represent different grayscale levels.

[0110] The purpose of grayscale processing is to simplify image information and remove unnecessary color information, making subsequent image processing steps more efficient and accurate. For example, in the process of extracting iris features, color information is not necessary, and grayscale images can better present the boundaries and texture structure of the iris. Taking a real scene as an example, suppose there is bright light or a complex background around the iris area of ​​a participant. Through grayscale processing, these effects can be minimized, retaining the key information of the iris for subsequent processing.

[0111] Step 403: filter the grayscale image.

[0112] After the grayscale image is generated, filtering is required to reduce the noise in the image. Filtering can remove the noise and interference introduced by factors such as the camera and light, and improve the clarity of the iris area. Common filtering methods include Gaussian filtering and mean filtering, which can smooth the pixels in the image and remove unnecessary high-frequency noise.

[0113] Step 404: perform binarization threshold segmentation on the grayscale image after filtering to obtain the iris region.

[0114] Binarization threshold segmentation is a technique that converts a grayscale image into a binary image. In this step, a threshold is set to divide the pixel values ​​in the grayscale image into two categories: pixels above the threshold are set to white (1), and pixels below the threshold are set to black (0). This processing method can clearly distinguish the iris area from other background areas, making the outline of the iris more obvious.

[0115] Step 405: Optimize the iris region using morphological opening operation.

[0116] After binarization, there may still be some small noise points or holes in the iris area. In order to further optimize the iris area, the opening operation in image morphology is used. The opening operation is a processing method composed of dilation and erosion operations, which can effectively remove noise points in the image, smooth the edges, and retain the main shape of the target area.

[0117] Step 406: extract iris feature information from the optimized iris region using a region growing algorithm.

[0118] The region growing algorithm is a segmentation algorithm based on the similarity of image pixel values. In the process of extracting iris feature information, starting from a seed point in the iris area, it gradually expands to the adjacent pixel area until the boundary of the entire iris area is found. This method can accurately extract the edge features of the iris and the internal texture information.

[0119] Step 407: Encode the iris feature information to obtain an iris feature code.

[0120] Finally, the extracted iris feature information is encoded to generate an iris feature code. The purpose of the encoding process is to convert the complex iris image into digital information that can be quickly compared. The iris feature code is usually a unique code generated based on the spatial distribution of the iris texture, which can be quickly matched with the sample feature code in the database during the subsequent identity verification process.

[0121] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0122] Reference Figure 5 , shows a structural block diagram of a computing system according to an embodiment of the present invention. The computing system may specifically include the following modules.

[0123] An image and instruction acquisition module 51 is used to acquire a biometric image from a terminal and obtain a biometric extraction instruction;

[0124] A biometric feature extraction module 52, configured to perform artificial intelligence enhancement processing on the biometric feature image according to the biometric feature extraction instruction, and extract biometric feature information from the biometric feature image after artificial intelligence enhancement processing;

[0125] The biometric transmission module 53 is used to transmit the biometric information to the server, so that the server compares the biometric information with the biometric sample information to obtain a comparison result, and performs security defense on the video conference according to the comparison result.

[0126] In an exemplary embodiment of the present invention, the biometric feature extraction module 52 includes:

[0127] An artificial intelligence enhancement processing module, used to perform one or more of the following artificial intelligence enhancement processing on the biometric image using an artificial intelligence model: denoising, super-resolution reconstruction, contrast enhancement, edge enhancement, artifact removal, and geometric correction;

[0128] A grayscale processing module, used for graying the biometric image after artificial intelligence enhancement processing according to the biometric extraction instruction to obtain a grayscale image;

[0129] A binarization processing module, used for performing threshold segmentation processing on the grayscale image based on a binarization technique to determine a target area;

[0130] A morphological processing module, used for optimizing the target area based on image morphological operations;

[0131] The feature encoding module is used to extract the biometric feature information from the target area after optimization processing by using a region growing algorithm, and encode the biometric feature information to obtain a biometric feature code.

[0132] Reference Figure 6 , shows a structural block diagram of a security defense system for video conferencing according to an embodiment of the present invention. The security defense system for video conferencing is applied to a server, and the security defense system for video conferencing may specifically include the following modules.

[0133] An acquisition instruction generation and transmission module 61 is used to generate and transmit a video stream acquisition instruction to a terminal, so that the terminal collects a biometric image and transmits the biometric image to a computing system;

[0134] An extraction instruction generation and transmission module 62, used to generate and transmit a biometric extraction instruction to the computing system, so that the computing system performs artificial intelligence enhancement processing on the biometric image according to the biometric extraction instruction, and extracts biometric information from the biometric image after artificial intelligence enhancement processing;

[0135] A biometric information comparison module 63, used to obtain the biometric information from the computing system, and compare the biometric information with the biometric sample information to obtain a comparison result;

[0136] The video conference security defense module 64 is used to perform security defense on the video conference according to the comparison result.

[0137] In an exemplary embodiment of the present invention, the security defense system further includes:

[0138] A sample image acquisition and forwarding module, used for registering the terminal with the server before the acquisition instruction generation and transmission module 61 generates and transmits the video stream acquisition instruction to the terminal, or when the terminal is not logging into the server for the first time, acquiring a biometric sample image from the terminal, and forwarding the biometric sample image to the computing system;

[0139] A biometric sample information acquisition module, used to acquire from the computing system the biometric sample information extracted from the biometric sample image by the computing system;

[0140] The sample and identification pairing storage module is used to pair and store the terminal identification information of the terminal with the biometric sample information.

[0141] In an exemplary embodiment of the present invention, the video conference security defense module 64 includes:

[0142] a normal operation module, configured to maintain a normal operation state of the terminal in the video conference if the comparison result indicates that the biometric information is consistent with the biometric sample information;

[0143] The interruption warning module is used to interrupt the video conference and issue a warning message if the comparison result indicates that the biometric information is inconsistent with the biometric sample information.

[0144] In an exemplary embodiment of the present invention, the security defense system further includes:

[0145] The security control module is used to record the session data of the video conference and start the access control mechanism and security monitoring measures of the video conference after the interruption warning module interrupts the video conference and issues a warning message.

[0146] As for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0147] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0148] It will be appreciated by those skilled in the art that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0149] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0150] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0151] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1The steps for the functions specified in one or more boxes.

[0152] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0153] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0154] The above is a detailed introduction to a video conferencing security defense method, a video conferencing security defense system, and a computing system provided by the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A video conference security defense method, characterized in that: Applied to a computing power system, the method includes: Obtaining a biometric image from a terminal and obtaining a biometric extraction instruction; Performing artificial intelligence enhancement processing on the biometric image according to the biometric extraction instruction, and extracting biometric information from the biometric image after the artificial intelligence enhancement processing; The biometric information is transmitted to a server so that the server compares the biometric information with the biometric sample information to obtain a comparison result, and performs security defense on the video conference according to the comparison result.

2. The method according to claim 1, characterized in that The performing artificial intelligence enhancement processing on the biometric image according to the biometric extraction instruction, and extracting biometric information from the biometric image after artificial intelligence enhancement processing, includes: Using an artificial intelligence model to perform one or more of the following artificial intelligence enhancement processing on the biometric image: denoising, super-resolution reconstruction, contrast enhancement, edge enhancement, artifact removal, and geometric correction; According to the biometric feature extraction instruction, grayscale processing is performed on the biometric feature image after artificial intelligence enhancement processing to obtain a grayscale image; Performing threshold segmentation processing on the grayscale image based on binarization technology to determine the target area; Optimizing the target area based on image morphological operations; The biometric information is extracted from the optimized target area using a region growing algorithm, and the biometric information is encoded to obtain a biometric code.

3. A video conference security defense method, characterized in that: Applied to a server, the method comprises: Generate and transmit a video stream acquisition instruction to a terminal, so that the terminal collects a biometric image and transmits the biometric image to a computing system; Generate and transmit a biometric feature extraction instruction to the computing system, so that the computing system performs artificial intelligence enhancement processing on the biometric feature image according to the biometric feature extraction instruction, and extracts biometric feature information from the biometric feature image after artificial intelligence enhancement processing; Acquire the biometric information from the computing system, and compare the biometric information with the biometric sample information to obtain a comparison result; The video conference is protected against security issues according to the comparison results.

4. The method according to claim 3, characterized in that Before generating and transmitting the video stream acquisition instruction to the terminal, the method further includes: When the terminal registers with the server, or when the terminal logs into the server for a non-first time, obtaining a biometric sample image from the terminal, and forwarding the biometric sample image to the computing system; Acquire, from the computing system, the biometric sample information extracted from the biometric sample image by the computing system; The terminal identification information of the terminal is paired with the biometric sample information and stored.

5. The method according to claim 3, characterized in that: The performing security defense on the video conference according to the comparison result includes: If the comparison result indicates that the biometric information is consistent with the biometric sample information, maintaining the normal operation state of the terminal in the video conference; If the comparison result indicates that the biometric information is inconsistent with the biometric sample information, the video conference is interrupted and a warning message is issued.

6. The method according to claim 5, characterized in that After interrupting the video conference and issuing a warning message, the method further includes: The session data of the video conference is recorded, and the access control mechanism and security monitoring measures of the video conference are activated.

7. A computing power system, characterized in that: The computing power system comprises: An image and instruction acquisition module, used to acquire a biometric image from a terminal and obtain a biometric extraction instruction; A biometric feature extraction module, configured to perform artificial intelligence enhancement processing on the biometric feature image according to the biometric feature extraction instruction, and extract biometric feature information from the biometric feature image after artificial intelligence enhancement processing; The biometric transmission module is used to transmit the biometric information to the server, so that the server compares the biometric information with the biometric sample information to obtain a comparison result, and performs security defense on the video conference according to the comparison result.

8. A video conferencing security defense system, characterized in that: Applied to the server, the security defense system includes: An acquisition instruction generation and transmission module, used to generate and transmit a video stream acquisition instruction to a terminal, so that the terminal collects a biometric image and transmits the biometric image to a computing system; An extraction instruction generation and transmission module, used to generate and transmit a biometric feature extraction instruction to the computing system, so that the computing system performs artificial intelligence enhancement processing on the biometric feature image according to the biometric feature extraction instruction, and extracts biometric feature information from the biometric feature image after artificial intelligence enhancement processing; A biometric information comparison module, used to obtain the biometric information from the computing system, and compare the biometric information with the biometric sample information to obtain a comparison result; The video conference security defense module is used to perform security defense on the video conference according to the comparison result.

9. An electronic device, characterized in that: include: one or more processors; and One or more machine-readable media having instructions stored thereon, when executed by the one or more processors, enable the electronic device to execute the video conference security defense method as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: The computer program stored therein enables the processor to execute the security defense method for video conferencing as described in any one of claims 1 to 6.

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