Static traffic network security protection method and system, electronic equipment and medium

Abstract

The invention belongs to the technical field of network security, and relates to a static traffic network security protection method and system, an electronic device and a medium, and the method comprises the steps: firstly designing an edge block chain authentication module, and guaranteeing the data security through data privatization and an efficient block chain network in combination with a multi-level security policy; designing a traffic analysis module, monitoring network traffic and equipment state in real time at an edge node, performing an automatic response mechanism, effectively ensuring data security in a networking environment by efficiently fusing edge computing and a block chain technology in combination with a multi-level security policy, and monitoring the network traffic and the equipment state in real time at the edge node; and an automatic response mechanism obviously improves the actual protection capability of the system.

Description

Technical Field

[0001] The present invention belongs to the field of network security technology, and relates to a static traffic network security protection method, system, electronic device and medium. Background Art

[0002] In the static traffic complex intelligent network environment of the intelligent parking system, information security is particularly critical. Since the end-side and edge-side devices are usually installed in an open-air environment, they are vulnerable to physical and network attacks. When the devices communicate with the parking cloud platform, the data transmission faces the risk of being intercepted or tampered with. In addition, the frequent and complex data exchange involves a large amount of vehicle and user information, and these data may be intercepted or maliciously tampered with during the transmission process, resulting in data leakage and system security vulnerabilities. Therefore, it is necessary to ensure the secure connection and authentication authorization mechanism between the devices and the internal network, and implement effective security protection measures. At the same time, it is necessary to monitor the network traffic in real time during the data exchange process to ensure the security of data exchange and the overall stability of the network, including detecting and responding to potential security threats in the Ethernet environment, and maintaining the normal operation of the system and data integrity. These two tasks are crucial for ensuring the information security of the intelligent parking system. However, there is currently no method specifically for the authentication and traffic monitoring problems in the intelligent parking networking environment.

[0003] In the existing Internet of Things authentication and authorization methods, the authentication method based on edge computing and blockchain deploys edge computing nodes in each device box and processes data at the edge nodes, which can promote data privatization, retain sensitive data at the edge nodes, and generate and authenticate unique digital identities through blockchain. Registration and authentication are carried out through blockchain, and the proof-of-work (PoW) consensus mechanism is further used to ensure data security, because an attacker needs to control more than 50% of the computing power to tamper with the blockchain record. However, the method based on edge computing and blockchain is not efficient. The proof-of-work (PoW) mechanism requires a large amount of power and computing resources due to its computational complexity, resulting in high energy consumption and is not suitable for the intelligent parking system. Moreover, the existing methods focus on a single strategy, such as using edge computing, blockchain, or physical device encryption alone. Currently, there are mainly two categories of Ethernet network security monitoring methods: one is the real-time traffic monitoring and log management method, which regularly audits and analyzes log data, and the other is the traffic analysis method, which analyzes and predicts traffic data in real time through a time series model to identify abnormal traffic patterns and ensure the overall security of the network system. However, the real-time traffic monitoring and log management method mainly relies on manual operations and is ineffective in dealing with massive data in the big data era. Although the traffic analysis method can analyze and classify traffic patterns, it has less research on real-time monitoring and automated response, which limits its practicality and effectiveness and is difficult to effectively guarantee network security. Therefore, there is an urgent need for a static traffic network security protection method to overcome the above problems. Summary of the Invention

[0004] The object of the present invention is to overcome the disadvantages existing in the prior art, and to design and provide a static traffic network security protection method, system, electronic device and medium, effectively solve the problems of network connection, authentication and authorization verification, data exchange and network security monitoring, and realize the security protection of the static traffic network.

[0005] To achieve the above object, the present invention adopts the following technical solutions: In the first aspect, the present invention provides a static traffic network security protection method, which specifically includes the following steps: S1. Edge blockchain authentication: Design an edge blockchain authentication module, and through data privatization and an efficient blockchain network, combined with multi-level security policies, ensure data security; S2. Traffic analysis: Design a traffic analysis module, real-time monitor network traffic and device status at the edge node, and perform an automated response mechanism to improve the security protection ability.

[0006] As a further technical solution of the present invention, the data privatization in step S1 is to deploy edge nodes in each intelligent parking equipment box, locally process data, the edge nodes real-time process parking data, and the parking data includes vehicle entry and exit records and parking space status, and exchange or upload sensitive data when necessary.

[0007] As a further technical solution of the present invention, the efficient blockchain network in step S1 takes each edge node as a node in the blockchain network, generates a unique digital identity, registers and authenticates through the blockchain. When an external device accesses the network, it needs to use its digital certificate for identity verification. At the same time, the Byzantine Fault Tolerance (BFT) consensus mechanism is adopted, allowing normal operation in the case of up to node failures or malicious behaviors, where is the number of edge nodes.

[0008] As a further technical solution of the present invention, the multi-level security policies in step S1 include physical security protection, network transmission encryption and data storage security. Among them, physical security protection: adopt a Hardware Security Module (HSM) to avoid physical tampering, and the Hardware Security Module (HSM) includes an anti-theft lock, a pry-proof alarm and a surveillance camera; network transmission encryption uses the Transport Layer Security (TLS) protocol to encrypt data transmission to prevent man-in-the-middle attacks; data storage security is to adopt fully homomorphic encryption storage technology on cloud devices. Fully homomorphic encryption directly performs calculations on ciphertexts, and the result of the calculation is still ciphertext, which is consistent with the result of performing the same calculation on plaintexts after decryption, ensuring the security of data during storage.

[0009] As a further technical solution of the present invention, the specific process of step S2 is: S21. Data collection and preprocessing: Use a traffic monitoring tool (such as Wireshark) to collect data at key network nodes. The collected data includes timestamps, source IPs, destination IPs, port numbers, and packet sizes. Clean the collected data, remove noise, and then extract features. The extracted features include the average packet size of the packets and the arrival interval time of the packets. S22. Time series modeling: Select to use a Long Short-Term Memory network (LSTM) for modeling. The Long Short-Term Memory network (LSTM) receives time series data of network traffic. The time series data includes the arrival time, size, source IP, and destination IP of the packets. Through the processing of the time series data, the Long Short-Term Memory network (LSTM) extracts key features, retains important information in the memory cells, and discards irrelevant information through the forget gate at the same time. At each time step, the Long Short-Term Memory network (LSTM) updates the memory cells and hidden states through the input gate and output gate, gradually capturing and updating the important information in the time series. S23. Real-time anomaly detection and response: Monitor the traffic in real time, compare the actual data with the predicted value, calculate the error, and when the error exceeds the threshold, it is determined as an anomaly: , where is the actual value, is the predicted value, is the error, and the set threshold , when , trigger an alarm; S24. Automatic response: After detecting abnormal traffic, automatically execute the preset security response strategy.

[0010] In a second aspect, the present invention provides a static traffic network security protection system, including: Edge blockchain authentication module: The edge blockchain authentication module ensures data security through data privatization and an efficient blockchain network, combined with multi-level security strategies. Traffic analysis module: The traffic analysis module monitors network traffic and device status in real time at the edge node and has an automatic response mechanism to enhance the security protection ability.

[0011] In a third aspect, the present invention provides an electronic device, including a memory, a processor, and computer instructions stored on the memory and running on the processor. When the computer instructions are run by the processor, the method described in the first aspect is completed.

[0012] In a fourth aspect, the present invention provides a computer-readable storage medium for storing computer instructions. When the computer instructions are executed by the electronic device, the method described in the first aspect is completed.

[0013] Compared with the prior art, the present invention has the following advantages: First, a solution to the authorization authentication and traffic monitoring problems in the intelligent parking system is proposed for the first time to ensure the stability and security of the network system. Second, an edge blockchain authentication module is proposed. By efficiently integrating edge computing and blockchain technologies and combining multi-level security strategies, the data security in the networking environment is effectively guaranteed. Third, a traffic analysis module with real-time and automated response is proposed. The network traffic and device status are monitored in real time at the edge nodes, and the automated response mechanism significantly improves the actual protection ability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a flowchart of the working process of the static traffic network security protection method of the present invention.

[0015] Figure 2 It is a structural block diagram of the static traffic network security protection system of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] The present invention will be further described below through embodiments in conjunction with the drawings.

[0017] Embodiment 1: As Figure 1 shown, this embodiment provides a static traffic network security protection method, which specifically includes the following steps: S1. Edge blockchain authentication: Design an edge blockchain authentication module. By data privatization and an efficient blockchain network, and combining multi-level security strategies, data security is guaranteed. Among them, data privatization is to deploy edge nodes in each intelligent parking equipment box, locally process data, and the edge nodes process parking data in real time. The parking data includes vehicle entry and exit records and parking space status, and sensitive data is exchanged or uploaded when necessary. The efficient blockchain network takes each edge node as a node in the blockchain network, generates a unique digital identity, registers and authenticates through the blockchain. When an external device accesses the network, it needs to use its digital certificate for identity verification. At the same time, the Byzantine Fault Tolerance (BFT) consensus mechanism is adopted, allowing normal operation in the case of up to node failures or malicious behaviors, where is the number of edge nodes. The multi-level security strategies include physical security protection, network transmission encryption, and data storage security. Among them, physical security protection: Use a Hardware Security Module (HSM) to avoid physical tampering. The Hardware Security Module (HSM) includes an anti-theft lock, anti-pry alarm, and surveillance camera. Network transmission encryption uses the Transport Layer Security (TLS) protocol to encrypt data transmission to prevent man-in-the-middle attacks. Data storage security is to adopt fully homomorphic encryption storage technology on cloud devices. Fully homomorphic encryption directly performs calculations on ciphertext, and the result of the calculation is still ciphertext, which is consistent with the result of performing the same calculation on plaintext after decryption, ensuring the security of data during storage.

[0018] S2. Traffic Analysis: Design a traffic analysis module to monitor network traffic and device status in real time at the edge node and implement an automated response mechanism to enhance the security protection ability. The specific process is as follows: S21. Data Collection and Preprocessing: Use traffic monitoring tools (such as Wireshark) to collect data at key network nodes. The collected data includes timestamps, source IPs, destination IPs, port numbers, and packet sizes. Clean the collected data, remove noise, and then extract features. The extracted features include the average packet size of the packets and the arrival interval time of the packets; S22. Time Series Modeling: Select to use a Long Short-Term Memory network (LSTM) for modeling. The Long Short-Term Memory network (LSTM) receives time series data of network traffic. The time series data includes the arrival time, size, source IP, and destination IP of the packets; Through the processing of the time series data, the Long Short-Term Memory network (LSTM) extracts key features, retains important information in the memory cells, and discards irrelevant information through the forget gate at the same time; At each time step, the Long Short-Term Memory network (LSTM) updates the memory cells and hidden states through the input gate and output gate, gradually capturing and updating the important information in the time series; S23. Real-Time Anomaly Detection and Response: Monitor the traffic in real time, compare the actual data with the predicted values, calculate the error, and when the error exceeds the threshold, it is determined as an anomaly: , where, is the actual value, is the predicted value, is the error, set the threshold, when , trigger an alarm; S24. Automated Response: After detecting abnormal traffic, automatically execute the preset security response strategy.

[0019] This embodiment proposes an edge blockchain authentication module. This module utilizes lightweight blockchain protocols and the Byzantine Fault Tolerance (BFT) mechanism to achieve efficient and secure data processing on edge nodes. In addition, this module combines physical security protection, network transmission encryption (such as TLS), data storage encryption (such as fully homomorphic encryption algorithms), etc., to provide comprehensive security protection from the physical layer to the storage layer. This multi-level security strategy can effectively prevent physical attacks and data interception, ensure the communication security between devices and the network, and achieve efficient and secure data processing and traffic monitoring in the intelligent parking system; in terms of data exchange and Ethernet network security monitoring, a traffic analysis module is designed. This module uses an advanced time series analysis model (Long Short-Term Memory Network LSTM) to model and real-time monitor the network traffic of edge nodes. By comparing the actual traffic and the predicted traffic values, abnormal behaviors are detected. Once an anomaly is found, the system will automatically trigger a preset security response mechanism, such as traffic isolation and bandwidth limitation, to ensure timely response to potential threats. The real-time monitoring and automated response mechanism can not only improve the accuracy of anomaly detection but also take immediate action when abnormal traffic is detected, enhancing the overall protection ability of the system. Compared with existing research, this embodiment not only provides customized security protection but also introduces real-time and automated response mechanisms to ensure that the system can respond quickly and effectively when facing potential threats. This innovative design has significant application value and is expected to achieve good results in actual deployment.

[0020] Embodiment 2: As Figure 2 shown, this embodiment provides a static traffic network security protection system, including: Edge blockchain authentication module: The edge blockchain authentication module ensures data security through data privatization and an efficient blockchain network, combined with a multi-level security strategy; Traffic analysis module: The traffic analysis module real-time monitors network traffic and device status at edge nodes and conducts an automated response mechanism to enhance the security protection ability.

[0021] In more embodiments, there is also provided: An electronic device, including a memory and a processor, as well as computer instructions stored on the memory and running on the processor. When the computer instructions are run by the processor, the method described in Embodiment 1 is completed. For the sake of simplicity, the detailed method content is not repeated here.

[0022] It should be clear that the processor in this embodiment is not limited to the central processing unit CPU. It can also be a general-purpose processor core, a digital signal processor DSP, an application-specific integrated circuit ASIC, a field-programmable gate array FPGA, or other programmable logic devices PLD, discrete gate circuits or transistor logic components, discrete hardware modules, etc. In addition, the general-purpose processor can be a microprocessor MPU, or any conventional arithmetic core.

[0023] The memory can include a read-only memory and a random access memory, and provide instructions and data to the processor. A part of the memory can also include a non-volatile random access memory. For example, the memory can also store information about the device type.

[0024] A computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by the processor, the method described in Embodiment 1 is completed.

[0025] The method in Embodiment 1 can be directly embodied as being executed by a hardware processor, or by a combination of hardware and software modules in the processor. The software modules can be located in mature storage media in the art such as random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, registers, etc. This storage medium is located in the memory, and the processor reads the information in the memory and combines its hardware to complete the steps of the above method. To avoid repetition, it will not be described in detail here.

[0026] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with this embodiment can be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but this implementation should not be considered to exceed the scope of this application.

[0027] The above is only the preferred embodiment of the present invention and is not used to limit the present invention. The systems and algorithms not described in detail in the present invention are all common technologies in the field. For those skilled in the art, the present invention can have various changes and modifications. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

[0028] Although the specific implementation manners of the present invention have been described above in conjunction with the accompanying drawings, it is not a limitation on the protection scope of the present invention. Those skilled in the art should understand that based on the technical solution of the present invention, various modifications or deformations that can be made by those skilled in the art without creative labor are still within the protection scope of the present invention.

Claims

1. A static traffic network security protection method, characterized in that: The specific steps include: S1. Edge blockchain authentication: Design edge blockchain authentication module to ensure data security through data privatization and efficient blockchain network, combined with multi-level security strategies; S2. Traffic analysis: Design a traffic analysis module to monitor network traffic and device status in real time at edge nodes and implement an automated response mechanism.

2. The static traffic network security protection method according to claim 1 is characterized in that: The data privatization described in step S1 is to deploy edge nodes in each smart parking equipment box to process data locally. The edge nodes process parking data in real time. The parking data includes vehicle entry and exit records and parking space status, and sensitive data is exchanged or uploaded.

3. The static traffic network security protection method according to claim 2 is characterized in that: Step S1 The efficient blockchain network uses each edge node as a node in the blockchain network, generates a unique digital identity, registers and authenticates through the blockchain, and external devices need to use their digital certificates for identity authentication when accessing the network. At the same time, the Byzantine fault-tolerant consensus mechanism is adopted, allowing up to Normal operation in the event of node failure or malicious behavior is the number of edge nodes.

4. The static traffic network security protection method according to claim 3 is characterized in that: Step S1 The multi-level security strategy includes physical security protection, network transmission encryption and data storage security. Physical security protection: adopt hardware security module to avoid physical tampering. The hardware security module includes anti-theft locks, anti-pry alarms and surveillance cameras; network transmission encryption uses the transport layer security protocol to encrypt data transmission to prevent man-in-the-middle attacks; Data storage security is achieved by using fully homomorphic encryption storage technology on cloud devices. Fully homomorphic encryption performs calculations directly on ciphertext, and the result of the calculation is still ciphertext. After decryption, it is consistent with the result of the same calculation on the plaintext.

5. The static traffic network security protection method according to claim 4 is characterized in that: The specific process of step S2 is: S21. Data collection and preprocessing: Use traffic monitoring tools to collect data at key network nodes. The collected data includes timestamp, source IP, destination IP, port number and packet size. Clean the collected data, remove noise and extract features. The extracted features include the average packet size and the arrival interval of the data packets. S22, Time Series Modeling: Choose to use the long short-term memory network for modeling. The long short-term memory network receives the time series data of network traffic, which includes the arrival time, size, source IP and destination IP of the data packet. By processing the time series data, the long short-term memory network extracts key features and retains important information in the memory cells, while discarding irrelevant information through the forget gate. At each time step, the long short-term memory network updates the memory cells and hidden states through the input gate and output gate, gradually capturing and updating important information in the time series. S23, Real-time anomaly detection and response: Monitor traffic in real time, compare actual data with predicted values, calculate errors, and determine anomalies when the error exceeds the threshold: ,in, is the actual value, is the predicted value, is the error, set the threshold ,when When , the alarm is triggered; S24, Automated response: After detecting abnormal traffic, the preset security response strategy is automatically executed.

6. A static traffic network security protection system, characterized in that: The method according to any one of claims 1 to 5 is performed, comprising: Edge blockchain authentication module: The edge blockchain authentication module ensures data security through data privatization and efficient blockchain network, combined with multi-level security strategies; Traffic analysis module: The traffic analysis module monitors network traffic and device status in real time at edge nodes, and performs automated response mechanisms to enhance security protection capabilities.

7. An electronic device, characterized in that: The invention comprises a memory and a processor and computer instructions stored in the memory and executed on the processor, wherein when the computer instructions are executed by the processor, the method according to any one of claims 1 to 5 is completed.

8. A computer-readable storage medium, characterized in that: Used to store computer instructions, which, when executed by the electronic device, complete the method described in any one of claims 1 to 5.

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