Computer network security intrusion detection system and device based on artificial intelligence

Abstract

The invention relates to the field of computer network security intrusion detection, in particular to a computer network security intrusion detection system based on artificial intelligence, which comprises an intrusion detection module and a control module, the data acquisition module comprises a network flow detection module and a system resource use condition detection module; the control module internally comprises an intrusion alarm module and a linkage control module, and the linkage control module is connected with and controls the clamping jaw clamping module through an electric signal; according to the invention, by monitoring the network flow and the CPU utilization rate, timely detecting and responding to abnormal conditions, network attacks and malicious programs are prevented, the system security is protected, physical network disconnection is realized by cooperating with the linkage of the clamping jaw clamping unit, the malicious programs are prevented from recovering network connection, the network system is protected from being damaged, and the network security is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of computer network security intrusion detection technology, and in particular to a computer network security intrusion detection system and device based on artificial intelligence. Background Art

[0002] An AI-based computer network security intrusion detection system is a system that uses artificial intelligence technologies such as machine learning and deep learning to detect and defend against network intrusions.

[0003] Most current computer network security warning systems rely on the computer's internal network security warning module to detect network failures and then display a pop-up window to alert users. However, this type of network security warning method has a significant flaw: users can only detect and address network failures in a timely manner when the computer is in use. If the computer is unused, it's difficult for staff to immediately notice the pop-up window, resulting in delayed network fault resolution and a high risk of serious network security issues. Summary of the Invention

[0004] The purpose of the present invention is to solve the shortcomings of the existing technology and to propose a computer network security intrusion detection system and device based on artificial intelligence.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A computer network security intrusion detection system based on artificial intelligence, comprising an intrusion detection module and a control module, wherein the intrusion detection module includes a data acquisition module, and the data acquisition module includes a network traffic detection module and a system resource usage detection module;

[0007] The control module includes an intrusion alarm module and a linkage control module, and the linkage control module is connected to control the clamping module through electrical signals;

[0008] The network traffic detection module is used to monitor the network traffic usage of the computer in real time, and is used to determine whether the maximum value range of network traffic usage is exceeded through the intrusion detection and judgment module. When the network traffic usage is lower than or equal to the maximum value range, or when the network traffic usage is higher than the maximum value range and the duration is longer than the maximum duration, the network traffic detection module continues to operate. When the network traffic usage is higher than the maximum value range and the duration is not longer than the maximum duration, the intrusion detection and judgment module controls the linkage control module through an electrical signal connection, and the linkage control module controls the gripper clamping module through an electrical signal connection;

[0009] The system resource usage detection module is used to monitor the CPU usage rate in real time, and is used to determine whether the CPU usage rate exceeds the maximum value range through the intrusion detection judgment module. When the CPU usage rate is lower than or equal to the maximum value range, or when the CPU usage rate is higher than the maximum value range and the duration is greater than the maximum duration, the system resource usage detection module continues to operate. When the CPU usage rate is higher than the maximum value range and the duration is not greater than the maximum duration, the intrusion detection judgment module controls the linkage control module through an electrical signal connection, and the linkage control module controls the gripper clamping module through an electrical signal connection.

[0010] Preferably, the intrusion detection module further includes a conventional data module, an intrusion detection judgment module, and an AI dynamic value range setting module;

[0011] The regular data module is used to record normal data of historical CPU usage and normal data of network traffic usage;

[0012] The AI dynamic value range setting module is used to learn and record the normal data of historical CPU usage and the normal data of network traffic usage, and then generate the dynamic maximum value range of CPU usage and the dynamic maximum value range of network traffic usage in real time.

[0013] Preferably, the intrusion alarm module is used to send a text message notification to the mobile phone of the corresponding administrator.

[0014] Preferably, the gripper drive module includes a screw drive unit and a bidirectional screw drive unit.

[0015] A computer network security intrusion detection device based on artificial intelligence includes a chassis body, a wireless network card body for connecting to WiFi is plugged into one side of the mechanical body, and one end of the mechanical body is located on the side of the wireless network card body and is provided with a clamping claw clamping unit, and the clamping claw clamping unit includes a fixed seat, and the fixed seat is moved toward the wireless network card body through a screw drive unit and is provided with a movable seat, and one side of the movable seat is provided with two clamping blocks through a bidirectional screw drive unit, and the two clamping blocks are symmetrically arranged.

[0016] Preferably, magnetic protrusions are symmetrically installed in the middle of both ends of the wireless network card body, and a magnetic groove is opened on the clamping block near the clamping surface and located at the magnetic protrusion, and a magnetic material that is attracted to the magnetic protrusion is set in the magnetic groove.

[0017] Preferably, a plurality of auxiliary reinforcement seats are installed at equal distances on the other end of the fixing seat, and the cross-section of the auxiliary reinforcement seat is in the shape of a triangular prism.

[0018] Preferably, an intrusion detection module and a control module are provided in the auxiliary reinforcement seat.

[0019] The beneficial effects of the present invention are:

[0020] In the present invention, by monitoring network traffic and CPU usage, abnormal situations are detected and responded to in a timely manner, network attacks and malicious programs are prevented, and system security is protected. In addition, the clamping unit is linked to achieve physical network disconnection, preventing malicious programs from restoring network connections, protecting the network system from infringement, and enhancing network security. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is the detection system diagram of the data acquisition module;

[0022] Figure 2 This is a diagram of a computer network security intrusion detection system based on artificial intelligence proposed by the present invention;

[0023] Figure 3 This is the system diagram of the gripper clamping module;

[0024] Figure 4 This is a schematic diagram of the structure of a computer network security intrusion detection device based on artificial intelligence proposed by the present invention;

[0025] Figure 5 This is a schematic diagram of a partial split structure of an artificial intelligence-based computer network security intrusion detection device proposed by the present invention;

[0026] Figure 6 Schematic diagram of the structure of the gripper clamping unit.

[0027] In the figure: 1. Chassis body; 11. Wireless network card body; 111. Magnetic protrusion; 2. Clamping claw unit; 21. Fixed seat; 211. Auxiliary reinforcement seat; 22. Movable seat; 23. Clamping block; 24. Bidirectional screw drive unit; 25. Screw drive unit. DETAILED DESCRIPTION

[0028] The technical solutions 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, rather than all the embodiments.

[0029] Reference Figure 1-6 , a computer network security intrusion detection system based on artificial intelligence, including an intrusion detection module and a control module, the intrusion detection module including a data acquisition module, the data acquisition module including a network traffic detection module and a system resource usage detection module;

[0030] The control module includes an intrusion alarm module and a linkage control module, and the linkage control module is connected to the control claw clamping module through electrical signals;

[0031] The network traffic detection module is used to monitor the network traffic usage of the computer in real time, and is used to determine whether the maximum value range of network traffic usage is exceeded through the intrusion detection and judgment module. When the network traffic usage is lower than or equal to the maximum value range, or when the network traffic usage is higher than the maximum value range and the duration is longer than the maximum duration, the network traffic detection module continues to operate. When the network traffic usage is higher than the maximum value range and the duration is not longer than the maximum duration, the intrusion detection and judgment module controls the linkage control module through an electrical signal connection, and the linkage control module controls the gripper clamping module through an electrical signal connection;

[0032] The system resource usage detection module is used to monitor the CPU usage in real time, and is used to determine whether the CPU usage exceeds the maximum value range through the intrusion detection and judgment module. When the CPU usage is lower than or equal to the maximum value range, or when the CPU usage is higher than the maximum value range and the duration is greater than the maximum duration, the system resource usage detection module continues to operate. When the CPU usage is higher than the maximum value range and the duration is not greater than the maximum duration, the intrusion detection and judgment module controls the linkage control module through an electrical signal connection, and the linkage control module controls the gripper clamping module through an electrical signal connection.

[0033] At the same time, the intrusion detection module also includes a regular data module, an intrusion detection judgment module, and an AI dynamic value range setting module;

[0034] The general data module is used to record the normal data of historical CPU usage and network traffic usage;

[0035] The AI dynamic value range setting module is used to learn and record the normal data of historical CPU usage and normal data of network traffic usage, and then generate the dynamic maximum value range of CPU usage and the dynamic maximum value range of network traffic usage in real time.

[0036] Furthermore, the intrusion alarm module is used to send SMS notifications to the corresponding administrator's mobile phone.

[0037] At the same time, the gripper drive module includes a screw drive unit and a bidirectional screw drive unit.

[0038] A computer network security intrusion detection device based on artificial intelligence includes a chassis body 1, a wireless network card body 11 for connecting to WiFi is plugged into one side of the mechanical body 1, and one end of the mechanical body 1 is located on the side of the wireless network card body 11 and is provided with a clamping claw clamping unit 2, and the clamping claw clamping unit 2 includes a fixed seat 21, the fixed seat 21 moves toward the wireless network card body 11 and is provided with a movable seat 22 through a screw drive unit 25, and two clamping blocks 23 are provided on one side of the movable seat 22 through a bidirectional screw drive unit, and the two clamping blocks 23 are symmetrically arranged.

[0039] Among them, magnetic protrusions 111 are symmetrically installed in the middle of both ends of the wireless network card body 11, and a magnetic groove is opened on the clamping surface side of the clamping block 23 and located at the magnetic protrusion 111, and a magnetic material that is attracted to the magnetic protrusion 111 is set in the magnetic groove.

[0040] A magnetic induction switch is provided in the magnetic suction groove, and the magnetic induction switch controls the screw drive unit through an electrical signal connection.

[0041] At the same time, a plurality of auxiliary reinforcement seats 211 are installed at equal distances at the other end of the fixing seat 21 , and the cross-section of the auxiliary reinforcement seat 211 is in the shape of a triangular prism.

[0042] In addition, an intrusion detection module and a control module are provided in the auxiliary reinforcement seat 211 .

[0043] Among them, it is worth noting that the specific structure, connection method and working principle of the chassis body 1 and the wireless network card body 11 are existing technologies currently disclosed on the market, and do not belong to the main technical problems to be solved in the present invention, so they will not be repeated in the present invention.

[0044] In the present invention, an intrusion detection and judgment module is used to judge whether the maximum value range of network traffic usage is exceeded. When the network traffic usage is lower than or equal to the maximum value range, or when the network traffic usage is higher than the maximum value range and the duration is longer than the maximum duration, the network traffic detection module continues to operate. When the network traffic usage is higher than the maximum value range and the duration is not longer than the maximum duration, the intrusion detection and judgment module controls the linkage control module through an electrical signal connection, and the linkage control module controls the gripper clamping module through an electrical signal connection.

[0045] The intrusion detection and judgment module is used to determine whether the maximum value range of the CPU usage is exceeded. When the CPU usage is lower than or equal to the maximum value range, or when the CPU usage is higher than the maximum value range and the duration is greater than the maximum duration, the system resource usage detection module continues to operate. When the CPU usage is higher than the maximum value range and the duration is not greater than the maximum duration, the intrusion detection and judgment module controls the linkage control module through an electrical signal connection, and the linkage control module controls the gripper clamping module through an electrical signal connection.

[0046] Among them, the clamping module controls the bidirectional screw drive unit 24 to move toward the wireless network card body 11 through electrical signals until the clamping surface of the clamping block 23 is in contact with the wireless network card body 11, and its magnetic suction groove is magnetically adsorbed and connected with the magnetic suction protrusion 111. At this time, after the magnetic suction sensing switch is attracted to the magnetic suction protrusion 111, the magnetic sensing switch controls the screw drive unit through electrical signal connection.

[0047] Then, the screw drive unit 25 drives the clamping block 23 and the clamped wireless network card body 11 to move away from the chassis body 1, and the chassis body 1 is completely disconnected from the network, preventing attackers from using network resources to cause further damage or preventing malicious programs from obtaining instructions or transmitting data to the outside through the network, thereby protecting the network system from infringement and enhancing network security.

[0048] In the present invention, by monitoring network traffic and CPU usage, abnormal situations are detected and responded to in a timely manner, network attacks and malicious programs are prevented, and system security is protected. In addition, the clamping unit is linked to achieve physical network disconnection, preventing malicious programs from restoring network connections, protecting the network system from infringement, and enhancing network security.

[0049] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A computer network security intrusion detection system based on artificial intelligence, comprising an intrusion detection module and a control module, characterized in that: The intrusion detection module includes a data acquisition module, which includes a network traffic detection module and a system resource usage detection module; The control module includes an intrusion alarm module and a linkage control module, and the linkage control module is connected to control the clamping module through electrical signals; The network traffic detection module is used to monitor the network traffic usage of the computer in real time, and is used to determine whether the maximum value range of network traffic usage is exceeded through the intrusion detection and judgment module. When the network traffic usage is lower than or equal to the maximum value range, or when the network traffic usage is higher than the maximum value range and the duration is longer than the maximum duration, the network traffic detection module continues to operate. When the network traffic usage is higher than the maximum value range and the duration is not longer than the maximum duration, the intrusion detection and judgment module controls the linkage control module through an electrical signal connection, and the linkage control module controls the gripper clamping module through an electrical signal connection; The system resource usage detection module is used to monitor the CPU usage rate in real time, and is used to determine whether the CPU usage rate exceeds the maximum value range through the intrusion detection judgment module. When the CPU usage rate is lower than or equal to the maximum value range, or when the CPU usage rate is higher than the maximum value range and the duration is greater than the maximum duration, the system resource usage detection module continues to operate. When the CPU usage rate is higher than the maximum value range and the duration is not greater than the maximum duration, the intrusion detection judgment module controls the linkage control module through an electrical signal connection, and the linkage control module controls the gripper clamping module through an electrical signal connection.

2. The computer network security intrusion detection system based on artificial intelligence according to claim 1 is characterized in that: The intrusion detection module also includes a conventional data module, an intrusion detection judgment module, and an AI dynamic value range setting module; The regular data module is used to record normal data of historical CPU usage and normal data of network traffic usage; The AI dynamic value range setting module is used to learn and record the normal data of historical CPU usage and the normal data of network traffic usage, and then generate the dynamic maximum value range of CPU usage and the dynamic maximum value range of network traffic usage in real time.

3. The computer network security intrusion detection system based on artificial intelligence according to claim 1 is characterized in that: The intrusion alarm module is used to send SMS notifications to the corresponding administrator's mobile phone.

4. The computer network security intrusion detection system based on artificial intelligence according to claim 1, characterized in that: The gripper drive module includes a screw drive unit and a bidirectional screw drive unit.

5. A computer network security intrusion detection device based on artificial intelligence, comprising a chassis body (1), characterized in that: A wireless network card body (11) for connecting to WiFi is plugged into one side of the mechanical body (1), and a clamping claw holding unit (2) is provided at one end of the mechanical body (1) located on one side of the wireless network card body (11), and the clamping claw holding unit (2) includes a fixed seat (21), and the fixed seat (21) is provided with a movable seat (22) that moves toward the wireless network card body (11) through a screw drive unit (25), and one side of the movable seat (22) is provided with two clamping blocks (23) through a bidirectional screw drive unit, and the two clamping blocks (23) are symmetrically arranged.

6. The computer network security intrusion detection device based on artificial intelligence according to claim 5, characterized in that: Magnetic protrusions (111) are symmetrically installed in the middle of both ends of the wireless network card body (11), and a magnetic groove is provided on the clamping block (23) near the clamping surface and located at the magnetic protrusion (111), and a magnetic material that is attracted to the magnetic protrusion (111) is provided in the magnetic groove.

7. The computer network security intrusion detection device based on artificial intelligence according to claim 5, characterized in that: A plurality of auxiliary reinforcement seats (211) are installed at equal distances on the other end of the fixing seat (21), and the cross section of the auxiliary reinforcement seat (211) is in the shape of a triangular prism.

8. The computer network security intrusion detection device based on artificial intelligence according to claim 7, characterized in that: An intrusion detection module and a control module are provided in the auxiliary reinforcement seat (211).

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