Internet of Things equipment safety test system and test method

Abstract

The invention discloses an Internet of Things equipment security test system and test method, and relates to the technical field of Internet of Things equipment, and the system comprises a data acquisition module, an environment adaptation module, an optimization module and a detection defense module. The environment adaptation module receives the original data obtained by preprocessing of the data acquisition module, and the environment adaptation module is further used for testing scene configuration to obtain performance reports of the Internet of Things equipment in different environments and according to the performance reports in different environments; strict data privacy protection measures such as anonymization processing and encrypted storage are implemented, the security of data in the collecting and processing process is ensured, data leakage and unauthorized access are prevented, a distributed data collecting system is adopted, the real-time performance and accuracy of the data are ensured, meanwhile, through a data preprocessing technology, the availability of the data is improved, and the security of the data is improved. The method follows an Internet of Things standard system construction guide, and guarantees the compliance of a data processing and testing system.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things devices, and more specifically, to an Internet of Things device security testing system and a testing method. Background Art

[0002] In the digital age, Internet of Things technology has become a bridge connecting the physical world and the digital world. With the wide deployment of smart devices, from smart cities, smart homes to industrial automation, the number and types of Internet of Things devices have increased sharply. These devices collect and exchange data, which although improves production efficiency and quality of life, the popularity of Internet of Things devices also brings other problems. Since Internet of Things devices are usually deployed in unprotected environments and may lack sufficient security measures, they have become new targets for cyberattacks;

[0003] However, in the actual use process, the diversity and dynamics of the Internet of Things environment pose challenges to data collection. At the same time, data privacy and security issues also limit the availability of data;

[0004] Moreover, the wide deployment of Internet of Things devices in different environments and application scenarios makes it difficult to adapt to changing conditions and maintain stable performance. In reality, models often perform well on the specific distribution of training data, but may fail when facing new, unseen data. Machine learning models may be vulnerable to adversarial attacks, where attackers deceive the model by carefully designing input samples to make it make incorrect predictions. Summary of the Invention

[0005] To solve the above problems, the present invention provides an Internet of Things device security testing system and a testing method.

[0006] The present invention provides an Internet of Things device security testing system, including a data acquisition module, an environment adaptation module, an optimization module, and a detection and defense module;

[0007] The data acquisition module is used to collect the original data stream of the Internet of Things device, and preprocess the original data of the Internet of Things device and then transmit it to the environment adaptation module;

[0008] The environment adaptation module receives the original data preprocessed by the data acquisition module, and the environment adaptation module is also used for test scenario configuration to obtain the performance report of the Internet of Things device in different environments, and according to the performance report in different environments, evaluate the stability evaluation result of the Internet of Things device in different environments, and transmit the evaluation result and the performance report in different environments to the optimization module;

[0009] The optimization module receives the raw data preprocessed by the data acquisition module, the evaluation results of the environment adaptation module, and the performance reports under different environments, and then obtains optimized Internet of Things device parameter suggestions based on the received data, and transmits the optimized Internet of Things device parameter suggestions to the detection and defense module;

[0010] The detection and defense module is used to receive the optimized Internet of Things device parameter suggestions of the optimization module, simulate the attack scenarios and threat data of the Internet of Things device, and finally obtain the security monitoring results of the Internet of Things device.

[0011] Preferably, the specific working steps of the data acquisition module are as follows:

[0012] Identify and connect to Internet of Things devices;

[0013] Real-time monitor and capture the data streams sent by Internet of Things devices;

[0014] Ensure the time synchronization of the data streams and add timestamps to each data point;

[0015] Convert data in different formats and units into a unified format and unit, complete the processing and transmit it to the environment adaptation module.

[0016] Preferably, the specific working steps of the environment adaptation module are as follows:

[0017] Obtain the recommended usage environment parameters of the Internet of Things device;

[0018] Three environment parameter intervals are set in advance. The first environment parameter interval is within ±5% of the usage environment parameters, the second environment parameter interval is within ±5% to ±15% of the usage environment parameters, and the third environment parameter interval is within ±15% to ±30% of the usage environment parameters;

[0019] Collect the operation data of the Internet of Things device under the three environment parameter intervals, and generate performance reports of the Internet of Things device under the three environment parameter intervals according to the operation data;

[0020] Calculate the stability evaluation results of the Internet of Things device under the three environment parameter intervals according to the performance reports of the Internet of Things device under the three environment parameter intervals;

[0021] The stability evaluation results and performance reports are transmitted to the optimization module.

[0022] Preferably, the specific steps of generating the performance reports of the Internet of Things device under the three environment parameter intervals according to the operation data are as follows:

[0023] The performance indicators of the performance reports specifically include response time R, throughput T, error rate E, and energy consumption W;

[0024] Within each environmental parameter range, for the response time R, it is calculated according to the formula where t i is the response time of the i-th request, and N is the total number of requests;

[0025] For the throughput T, it is calculated through where N is the total number of requests, and Y is the total experimental time, that is, the total request time;

[0026] For the error rate E, it is obtained by dividing the number of request errors by the total number of requests N;

[0027] For the corresponding energy consumption W, it is obtained by multiplying the average power consumption by the total experimental time Y;

[0028] The response time R, throughput T, error rate E, and energy consumption W are transmitted as performance reports.

[0029] Preferably, the specific steps for calculating the stability evaluation results of the Internet of Things device in three environmental parameter ranges are as follows:

[0030] Collect the operation data of the Internet of Things device in three environmental parameter ranges multiple times, and receive the performance reports for each test in each environmental parameter range, specifically including the response time R, throughput T, error rate E, and energy consumption W for each test;

[0031] Calculate the variances corresponding to the response time R, throughput T, error rate E, and energy consumption W in all test performance reports, and mark them as response time variance R1, throughput variance T1, error rate variance E1, and energy consumption variance W1;

[0032] According to the formula S = 0.2 * R1 + 0.2 * T1 + 0.3 * E1 + 0.3 * W1, calculate the stability evaluation value S of the Internet of Things device in each environmental parameter range, and transmit the stability evaluation value S as the stability evaluation result.

[0033] Preferably, the specific working steps of the optimization module are as follows:

[0034] Obtain the existing Internet of Things device parameters, specifically including the transmission power F;

[0035] According to the formula F1 = F + 0.5 * (S - S1), calculate the adjustment value F1 of the Internet of Things device parameters in each environmental parameter range, where S1 is the threshold of the Internet of Things device stability evaluation value;

[0036] Transmit the adjustment value F1 of the Internet of Things device parameters in each environmental parameter range to the detection and defense module as the Internet of Things device parameter suggestion.

[0037] Preferably, the specific working steps of the detection and defense module are as follows:

[0038] Use the IoTSecSim framework to create an IoT network and simulate different attack behaviors;

[0039] Build a dataset by simulating the MQTT IoT network environment, use the tcpdump tool to record Ethernet traffic, and export it as a pcap file;

[0040] Extract multi-level features, including packet-level, one-way flow, and two-way flow features;

[0041] Based on the extracted features, calculate the security detection result.

[0042] Preferably, the specific steps for calculating the security monitoring result based on the extracted features are as follows:

[0043] Obtain the attack behavior frequency A, attack duration K, attack impact range L, and the deviation V between the attack and normal behavior;

[0044] According to the formula G = 0.2*RA + 0.2*K + 0.3*L + 0.3*V, calculate and obtain the security monitoring value G of the IoT device, and mark the security detection value G as the security monitoring result.

[0045] Preferably, the obtaining methods of the attack behavior frequency A, attack duration K, attack impact range L, and the deviation V between the attack and normal behavior are as follows:

[0046] For the attack behavior frequency A, obtain it by counting the total number of attack events, recording the total time, and then dividing the total number of attack events by the total time to get the attack frequency;

[0047] For the attack duration K, obtain it by recording the start time and end time of the attack, and then subtracting the start time from the end time to get the attack duration;

[0048] For the attack impact range L, obtain it by counting the number of devices affected by the attack, and this number is the attack impact range;

[0049] For the deviation V between the attack and normal behavior, obtain it by extracting the feature values of the attack behavior and the normal behavior, and then calculating the absolute difference between the two to get the deviation;

[0050] The present invention also proposes an IoT device security testing method, including the following steps:

[0051] Step 1: Collect the original data stream of the IoT device, and preprocess the collected original data, such as data cleaning, formatting, etc., for subsequent analysis;

[0052] Step 2: Receive the preprocessed data, and according to different test scenario configurations, evaluate the performance of the IoT devices in different environments, evaluate the stability of the devices in different environments, generate evaluation results, and propose optimized IoT device parameter suggestions to improve the device performance and stability;

[0053] Step 3: Receive the optimized IoT device parameter suggestions, simulate attack scenarios and threat data, obtain the security detection results of the IoT devices, evaluate the security performance of the devices when facing potential attacks, and implement corresponding defense measures to ensure the secure operation of the IoT devices.

[0054] Beneficial effects: By implementing strict data privacy protection measures, such as anonymization and encrypted storage, ensure the security of data during the collection and processing, prevent data leakage and unauthorized access, adopt a distributed data collection system to ensure the real-time and accuracy of data, and at the same time, through data preprocessing technology, improve the availability of data, and follow the construction guidelines of the IoT standard system to ensure the compliance of the data processing and testing system;

[0055] By simulating different environments and application scenarios, evaluate the performance of the IoT devices in different environments, improve the adaptability of the devices, evaluate the stability of the IoT devices according to the performance reports in different environments, optimize the device configuration and parameter settings to adapt to changing conditions and maintain stable performance, simulate the attack scenarios and threat data of the IoT devices, and enhance the security of the devices through the security detection results. Description of the Drawings

[0056] Figure 1 is the flowchart of the present invention. Detailed Embodiments

[0057] Application Scenario: In the actual use process, the diversity and dynamics of the IoT environment pose challenges to data collection. At the same time, data privacy and security issues also limit the availability of data;

[0058] Moreover, the wide deployment of IoT devices in different environments and application scenarios makes it difficult to adapt to changing conditions and maintain stable performance. The reality is that models often perform well on the specific distribution of training data, but may fail when facing new and unseen data. Machine learning models may be vulnerable to adversarial attacks, where attackers deceive the model by carefully designing input samples to make it make incorrect predictions.

[0059] Such as Figure 1 shown: An IoT device security testing system includes a data collection module, an environment adaptation module, an optimization module, and a detection and defense module;

[0060] The data acquisition module is used to collect the original data stream of Internet of Things devices, preprocess the original data of Internet of Things devices, and then transmit it to the environment adaptation module;

[0061] The environment adaptation module receives the original data preprocessed by the data acquisition module, and the environment adaptation module is also used to test the scenario configuration, obtain the performance reports of Internet of Things devices in different environments, and evaluate the stability evaluation results of Internet of Things devices in different environments according to the performance reports in different environments, and transmit the evaluation results and the performance reports in different environments to the optimization module;

[0062] The optimization module receives the original data preprocessed by the data acquisition module, the evaluation results of the environment adaptation module, and the performance reports in different environments, and then obtains the optimized parameter suggestions for Internet of Things devices according to the received data, and transmits the optimized parameter suggestions for Internet of Things devices to the detection and defense module;

[0063] The detection and defense module is used to receive the optimized parameter suggestions for Internet of Things devices from the optimization module, simulate the attack scenarios and threat data of Internet of Things devices, and finally obtain the security monitoring results of Internet of Things devices.

[0064] It should be noted that the data acquisition module is responsible for collecting the original data and providing input for the environment adaptation module. The environment adaptation module conducts tests based on the data of the data acquisition module and passes the results to the optimization module. The optimization module formulates optimization strategies according to the results of the environment adaptation module and outputs them to the detection and defense module. The detection and defense module implements security measures and adjusts the strategies of the optimization module according to the results;

[0065] As a further embodiment, the specific working steps of the data acquisition module are as follows:

[0066] Identify and connect to Internet of Things devices; ensure that all target devices are recognized by the system and incorporated into the data acquisition process, laying a foundation for data acquisition;

[0067] Real-time monitor and capture the data stream sent by Internet of Things devices; it should be noted that the data stream specifically includes the status and performance data of Internet of Things devices, as well as the environmental measurement data (temperature, humidity, and pressure) from the sensors of Internet of Things devices, and also includes the communication and interaction data between Internet of Things devices and other devices;

[0068] Ensure the time synchronization of the data stream and add a timestamp to each data point;

[0069] Convert data in different formats and units into a unified format and unit, complete the processing, and transmit it to the environment adaptation module.

[0070] As a further embodiment, the specific working steps of the environment adaptation module are as follows:

[0071] Obtain the recommended usage environment parameters of the Internet of Things device; it should be noted that the recommended usage environment parameters are obtained from the manufacturer of the Internet of Things device. The environment parameters include three parameters: temperature, humidity, and pressure. Generally, the recommended usage environment parameters are for normal temperature, normal pressure, and normal humidity environments;

[0072] Set three environmental parameter ranges in advance. The first environmental parameter range is within ±5% of the usage environment parameters, the second environmental parameter range is within ±5% to ±15% of the usage environment parameters, and the third environmental parameter range is within ±15% to ±30% of the usage environment parameters;

[0073] Collect the operation data of the Internet of Things device under the three environmental parameter ranges, and generate a performance report of the Internet of Things device under the three environmental parameter ranges based on the operation data;

[0074] Calculate the stability evaluation results of the Internet of Things device under the three environmental parameter ranges based on the performance report of the Internet of Things device under the three environmental parameter ranges;

[0075] Transmit the stability evaluation results and the performance report to the optimization module.

[0076] It should be noted that the operation data refers to the data generated during the actual operation of the Internet of Things device, specifically including performance indicators such as processing speed, response time, throughput, error rate, etc., resource utilization rates such as the usage rates of CPU and memory, and energy consumption data: the energy consumption situation of the device, including battery life (for mobile devices);

[0077] The performance report is a summary of the operation performance of the Internet of Things device under specific environmental parameters, and the stability evaluation result is a quantitative analysis of the stability of the Internet of Things device under different environmental parameters;

[0078] It should also be noted that it is possible to determine the performance and stability of the device under different environmental conditions, adjust the device configuration according to the evaluation results to improve its performance in various environments, and predict potential failures and take preventive measures by analyzing the performance report and stability evaluation;

[0079] By testing the performance of the device under different environmental parameters, the module can help the device better adapt to changing environmental conditions. By collecting data under different environmental parameters, the module helps to collect more comprehensive data to cope with the challenges brought by environmental diversity. By implementing security measures during data collection and processing, the module helps to protect data privacy and security. By evaluating the performance of the device under different environments, the module can help optimize the device configuration to maintain stable performance. By conducting stability evaluations, the module can help identify and prevent potential failures that may occur under different environmental conditions. By long-term monitoring of the device's performance under different environments, the module helps to improve the long-term reliability and durability of the device.

[0080] As a further embodiment, the specific steps for generating a performance report of the IoT device in three environmental parameter intervals based on the operation data are as follows:

[0081] The performance metrics of the performance report specifically include response time R, throughput T, error rate E, and energy consumption W;

[0082] Within each environmental parameter interval, for the response time R, according to the formula it is calculated and obtained, where t i is the response time of the i-th request, and N is the total number of requests;

[0083] For the throughput T, it is calculated and obtained through where N is the total number of requests, and Y is the total experimental time, that is, the total request time;

[0084] For the error rate E, it is obtained by dividing the number of request errors by the total number of requests N;

[0085] Corresponding to the energy consumption W, it is obtained by multiplying the average power consumption by the total experimental time Y;

[0086] The response time R, throughput T, error rate E, and energy consumption W are transmitted as the performance report.

[0087] As a further embodiment, the specific steps for calculating the stability evaluation results of the IoT device in three environmental parameter intervals are as follows:

[0088] Collect the operation data of the IoT device in three environmental parameter intervals multiple times, and receive the performance report of each test in each environmental parameter interval, specifically including the response time R, throughput T, error rate E, and energy consumption W of each test;

[0089] Calculate the variances corresponding to the response time R, throughput T, error rate E, and energy consumption W in all test performance reports, and mark them as response time variance R1, throughput variance T1, error rate variance E1, and energy consumption variance W1;

[0090] According to the formula S = 0.2*R1 + 0.2*T1 + 0.3*E1 + 0.3*W1, calculate and obtain the stability evaluation value S of the Internet of Things device in each environmental parameter interval, and transmit the stability evaluation value S as the stability evaluation result.

[0091] As a further embodiment, the specific working steps of the optimization module are as follows:

[0092] Obtain the existing Internet of Things device parameters, specifically including the transmission power F;

[0093] According to the formula F1 = F + 0.5*(S - S1), calculate the adjustment value F1 of the Internet of Things device parameters in each environmental parameter interval, where S1 is the threshold value of the Internet of Things device stability evaluation value;

[0094] Transmit the adjustment value F1 of the Internet of Things device parameters in each environmental parameter interval to the detection and defense module as the Internet of Things device parameter suggestion.

[0095] It should be noted that the threshold value of the Internet of Things device stability evaluation value is the average value of historical data.

[0096] As a further embodiment, the specific working steps of the detection and defense module are as follows:

[0097] Use the IoTSecSim framework to create an Internet of Things network and simulate different attack behaviors; IoTSecSim supports flexible setting of Internet of Things devices and topology information, and simulates attack behaviors as well as node-level and network-level defenses;

[0098] Build a dataset by simulating the MQTT Internet of Things network environment, use the tcpdump tool to record Ethernet traffic, and export it as a pcap file. Simulate network devices in a virtual machine, use Nmap for scanning attacks, VLC for simulating camera streams, and MQTT-PWN for simulating MQTT brute-force attacks;

[0099] Extract multi-level features, including packet-level, one-way flow, and two-way flow features; covering source and destination IP addresses, protocols, timestamps, packet lengths, TCP and MQTT flags, etc., analyze the pcap file, and extract relevant features for security detection;

[0100] Based on the extracted features, calculate the security detection result. Use simple statistical analysis methods, such as calculating the frequency, duration, and scope of influence of attack behaviors, as well as their deviations from normal behaviors.

[0101] As a further embodiment, the specific steps for calculating the security monitoring result based on the extracted features are as follows:

[0102] Obtain the attack behavior frequency A, the attack duration K, the attack influence range L, and the behavior deviation V between the attack and the normal behavior;

[0103] According to the formula G = 0.2 * RA + 0.2 * K + 0.3 * L + 0.3 * V, calculate and obtain the security monitoring value G of the Internet of Things device, and mark the security detection value G as the security monitoring result.

[0104] As a further embodiment, the obtaining methods of the attack behavior frequency A, the attack duration K, the attack influence range L, and the behavior deviation V between the attack and the normal behavior are as follows:

[0105] For the attack behavior frequency A, obtain it by counting the total number of attack events, recording the total time, and then dividing the total number of attack events by the total time to get the attack frequency;

[0106] For the attack duration K, obtain it by recording the start time and the end time of the attack, and then subtracting the start time from the end time;

[0107] For the attack influence range L, obtain it by counting the number of devices affected by the attack, and this number is the attack influence range;

[0108] For the behavior deviation V between the attack and the normal behavior, obtain it by extracting the feature values of the attack behavior and the feature values of the normal behavior, and then calculating the absolute difference between the two;

[0109] The present invention also proposes a security testing method for Internet of Things devices. The above-mentioned security testing system for Internet of Things devices includes the following steps:

[0110] Step 1: Collect the original data stream of the Internet of Things device, and preprocess the collected original data, such as data cleaning, formatting, etc., for subsequent analysis;

[0111] Step 2: Receive the preprocessed data, and according to different test scenario configurations, evaluate the performance of the Internet of Things device in different environments, evaluate the stability of the device in different environments, generate an evaluation result, and propose optimized parameter suggestions for the Internet of Things device to improve the device performance and stability;

[0112] Step 3: Receive the optimized parameter suggestions for the Internet of Things device, simulate the attack scenario and threat data, obtain the security detection result of the Internet of Things device, evaluate the security performance of the device when facing potential attacks, and implement corresponding defense measures to ensure the secure operation of the Internet of Things device.

[0113] Working principle:

[0114] It should be noted that the data acquisition module is responsible for collecting raw data and providing input for the environment adaptation module. The environment adaptation module conducts tests based on the data from the data acquisition module and passes the results to the optimization module. The optimization module formulates optimization strategies according to the results of the environment adaptation module and outputs them to the detection and defense module. The detection and defense module implements security measures and adjusts the strategies of the optimization module according to the results;

[0115] By implementing strict data privacy protection measures, such as anonymization and encrypted storage, ensure the security of data during collection and processing, prevent data leakage and unauthorized access. Adopt a distributed data acquisition system to ensure the timeliness and accuracy of data. At the same time, through data preprocessing techniques, improve the usability of data, and follow the construction guidelines of the Internet of Things standard system to ensure the compliance of the data processing and testing system;

[0116] By simulating different environments and application scenarios, evaluate the performance of Internet of Things devices in different environments, improve the adaptability of the devices. According to the performance reports in different environments, evaluate the stability of Internet of Things devices, optimize the device configuration and parameter settings to adapt to changing conditions and maintain stable performance. Simulate the attack scenarios and threat data of Internet of Things devices, and enhance the security of the devices through security detection results.

[0117] The above are only the preferred embodiments of the present invention. The protection scope of the present invention is not limited to the above embodiments. All technical solutions within the idea of the present invention belong to the protection scope of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements should also be regarded as within the protection scope of this template.

Claims

1. An Internet of Things device security testing system, characterized in that: It includes data acquisition module, environment adaptation module, optimization module and detection and defense module; The data acquisition module is used to collect the original data stream of the IoT device, and pre-process the original data of the IoT device before transmitting it to the environment adaptation module; The environmental adaptation module receives the raw data preprocessed by the data acquisition module, and the environmental adaptation module is also used to test the scene configuration, obtain the performance report of the Internet of Things device in different environments, and evaluate the stability evaluation results of the Internet of Things device in different environments according to the performance reports in different environments, and transmit the evaluation results and the performance reports in different environments to the optimization module; The optimization module receives the raw data preprocessed by the data acquisition module, the evaluation results of the environment adaptation module, and the performance reports under different environments, then obtains optimized IoT device parameter recommendations based on the received data, and transmits the optimized IoT device parameter recommendations to the detection and defense module; The detection and defense module is used to receive the IoT device parameter suggestions optimized by the optimization module, and simulate the attack scenarios and threat data of the IoT devices, and finally obtain the security monitoring results of the IoT devices.

2. The IoT device security testing system according to claim 1, characterized in that: The specific working steps of the data acquisition module are as follows: Identify and access IoT devices; Monitor and capture data streams from IoT devices in real time; Ensure time synchronization of data streams and add timestamps to each data point; The data in different formats and units are converted into a unified format and unit, processed and transmitted to the environment adaptation module.

3. The IoT device security testing system according to claim 2, characterized in that: The specific working steps of the environment adaptation module are as follows: Obtain the recommended operating environment parameters of the IoT device; Three environmental parameter intervals are set in advance, the first environmental parameter interval is within the range of ±5% of the environmental parameter, the second environmental parameter interval is within the range of ±5% to ±15% of the environmental parameter, and the third environmental parameter interval is within the range of ±15% to ±30% of the environmental parameter; Collect the operating data of IoT devices in three environmental parameter ranges, and generate performance reports of IoT devices in three environmental parameter ranges based on the operating data; The stability evaluation results of the IoT devices in the three environmental parameter intervals are calculated based on the performance reports of the IoT devices in the three environmental parameter intervals; The stability assessment results and performance reports are transmitted to the optimization module.

4. The IoT device security testing system according to claim 3, characterized in that: The specific steps of generating a performance report of the IoT device under three environmental parameter intervals according to the operating data are as follows: The performance indicators of the performance report specifically include response time R, throughput T, error rate E and energy consumption W; In each environmental parameter range, for the response time R, according to the formula Calculate and obtain, where t i is the response time of the i-th request, and N is the total number of requests; For throughput T, by The calculation results are: N is the total number of requests, and Y is the total experimental time, that is, the total request time; For the error rate E, it is obtained by dividing the number of request errors by the total number of requests N; The corresponding energy consumption W is obtained by multiplying the average power consumption by the total experimental time Y; The response time R, throughput T, error rate E and energy consumption W are transmitted as performance reports.

5. The IoT device security testing system according to claim 4, characterized in that: The specific steps of calculating the stability evaluation results of the IoT device under three environmental parameter ranges are as follows: Collect the operation data of IoT devices in three environmental parameter ranges multiple times, and receive the performance report of each test in each environmental parameter range, including the response time R, throughput T, error rate E and energy consumption W of each test; Calculate the variances of response time R, throughput T, error rate E, and energy consumption W in all test performance reports, and mark them as response time variance R1, throughput variance T1, error rate variance E1, and energy consumption variance W1; According to the formula S=0.2*R1+0.2*T1+0.3*E1+0.3*W1, the stability evaluation value S of the IoT device in each environmental parameter interval is calculated and obtained, and the stability evaluation value S is transmitted as the stability evaluation result.

6. The IoT device security testing system according to claim 5, characterized in that: The specific working steps of the optimization module are as follows: Obtain the existing IoT device parameters, including transmission power F; According to the formula F1=F+0.5*(S-S1), the adjustment value F1 of the IoT device parameters in each environmental parameter range is calculated, where S1 is the threshold of the IoT device stability assessment value; The adjustment value F1 of the IoT device parameter in each environmental parameter interval is transmitted to the detection and defense module as an IoT device parameter suggestion.

7. The IoT device security testing system according to claim 6, characterized in that: The specific working steps of the detection and defense module are as follows: Use the IoTSecSim framework to create IoT networks and simulate different attack behaviors; The dataset was constructed by simulating the MQTT IoT network environment, using the tcpdump tool to record Ethernet traffic and export it as a pcap file. Extract multi-level features, including packet-level, unidirectional flow, and bidirectional flow features; Based on the extracted features, the security detection results are calculated.

8. The IoT device security testing system according to claim 7, characterized in that: The specific steps of calculating the security detection results based on the extracted features are as follows: Obtain the attack behavior frequency A, attack duration K, attack impact range L and the deviation between attack and normal behavior V; According to the formula G=0.2*RA+0.2*K+0.3*L+0.3*V, the security monitoring value G of the IoT device is calculated and the security detection value G is marked as the security monitoring result.

9. The IoT device security testing system according to claim 8, characterized in that: The attack behavior frequency A, attack duration K, attack impact range L and attack and normal behavior deviation V are obtained as follows: For the frequency of aggressive behavior A, we counted the total number of attack events and recorded the total time, then divided the total number of attack events by the total time to get the attack frequency; For the attack duration K, the attack duration is obtained by recording the start time and the end time of the attack, and then subtracting the start time from the end time; For the attack impact range L, the number of devices affected by the attack is counted, and this number is the attack impact range; For the deviation V between attack and normal behavior, the deviation is obtained by extracting the characteristic value of the attack behavior and the characteristic value of the normal behavior, and then calculating the absolute difference between the two.

10. A method for security testing of an Internet of Things device, applicable to an Internet of Things device security testing system according to any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: Collect the raw data stream of IoT devices and pre-process the collected raw data, such as data cleaning and formatting, to facilitate subsequent analysis; Step 2: Receive the pre-processed data and evaluate the performance of IoT devices in different environments according to different test scenario configurations, evaluate the stability of devices in different environments, generate evaluation results, and propose optimized IoT device parameter recommendations to improve device performance and stability; Step 3: Receive optimized IoT device parameter recommendations, simulate attack scenarios and threat data, obtain security detection results for IoT devices, evaluate the security performance of devices in the face of potential attacks, implement corresponding defense measures, and ensure the safe operation of IoT devices.

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