A communication network security detection system based on Bragg grating

Abstract

The present invention discloses a communication network security detection system based on Bragg grating, which relates to the technical field of communication networks, and includes: the data acquisition module is used to obtain the historical communication spectrum data of the target optical fiber; the threshold analysis module is used to analyze the trend in the historical communication spectrum data, and obtain the communication spectrum curve range threshold; the real-time monitoring module is used to obtain and determine the communication spectrum curve value of the target optical fiber at the current moment; the preliminary screening module is used to determine whether the communication spectrum curve value of the target optical fiber at the current moment exceeds the communication spectrum curve range threshold; the abnormal judgment module is used to perform abnormal fitting analysis on the spectrum parameters exceeding the range threshold, and determine whether the abnormal fitting degree matches the corresponding communication network attack event. The advantages of the present invention are: it realizes the detection of light leakage attack and light injection attack at the physical level.

Description

Technical Field

[0001] The invention relates to the technical field of communication network security, and in particular to a communication network security detection system based on Bragg grating. Background Art

[0002] Bragg grating means that when a light wave is irradiated onto the grating, if the wavelength, angle of the incident light and the period of the grating meet the Bragg condition, the light wave will be reflected back to the original direction by the grating to form a specific reflection wavelength, thereby realizing the frequency selection or splitting function of the light.

[0003] In the existing communication network security attack and defense, the main defense means are to set up software firewalls to intercept network attacks, ignoring physical network theft, that is, connecting to the target optical fiber, performing optical reading and optical injection to attack the target platform's communication network and obtain communication secrets. Therefore, conventional firewalls have poor defense against such attacks. Summary of the invention

[0004] In order to solve the above technical problems, a communication network security detection system based on Bragg grating is provided. This technical solution solves the above-mentioned problem that in the existing communication network attack and defense, the main defense means are to set up software firewalls to intercept network attacks, and ignore physical network theft, that is, by connecting to the target optical fiber, performing optical reading and optical injection to attack the target platform's communication network and obtain communication secrets. Therefore, conventional firewalls have poor defense against such attacks.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A communication network security detection system based on Bragg grating, comprising:

[0007] Data acquisition module, threshold analysis module, real-time monitoring module, preliminary screening module, abnormality judgment module;

[0008] The data acquisition module is used to deploy Bragg gratings according to the communication nodes of the target optical fiber to obtain the historical communication spectrum data of the target optical fiber;

[0009] The threshold analysis module is electrically connected to the data acquisition module, and the threshold analysis module is used to analyze the optical signal change trend in the historical communication spectrum data based on the historical communication spectrum data to obtain the communication spectrum curve range threshold;

[0010] The real-time monitoring module is used to obtain the real-time communication spectrum data of the target optical fiber and determine the communication spectrum curve value of the target optical fiber at the current moment;

[0011] The preliminary screening module is electrically connected to the threshold analysis module and the real-time monitoring module. The preliminary screening module is used to determine whether the communication spectrum curve value of the target optical fiber at the current moment exceeds the communication spectrum curve range threshold. If not, no response is made. If so, the spectrum parameter exceeding the range threshold is marked.

[0012] The abnormal judgment module is electrically connected to the preliminary screening module. The abnormal judgment module is used to perform abnormal fitting analysis on the spectral parameters that exceed the range threshold, and determine whether the abnormal fitting degree matches the corresponding communication network attack event. If not, report optical fiber damage. If so, intercept the optical signal and report the physical communication network attack.

[0013] Preferably, the analyzing the optical signal variation trend in the historical communication spectrum data based on the historical communication spectrum data to obtain the communication spectrum curve range threshold specifically includes:

[0014] Based on the historical communication spectrum data of the target optical fiber, the spectrum parameters in the spectrum data are screened out to obtain the communication spectrum parameter data;

[0015] According to the communication spectrum parameter data, the parameter values ​​of the corresponding spectrum parameters are counted to obtain the communication time-domain spectrum characteristic parameter data; the communication time-domain spectrum characteristic parameters include: the mean value of the optical signal, the standard deviation of the optical signal, and the extreme value of the optical signal;

[0016] According to the communication spectrum parameter data, the communication spectrum parameter data is converted into the frequency domain through the Fourier transform function, and the parameter value of the frequency domain spectrum parameter is marked to obtain the communication frequency domain spectrum characteristic parameter data; the communication frequency domain spectrum characteristic parameters include: the main frequency of the optical signal, the bandwidth of the optical signal, and the power spectrum density of the optical signal;

[0017] Based on time series analysis SARIMA, a communication spectrum trend analysis model is trained;

[0018] Substitute the communication spectrum parameter data into the communication spectrum trend analysis model, take the time domain spectrum characteristic parameters and frequency domain spectrum characteristic parameters in the communication spectrum parameter data within a unit time as input, and predict the spectrum curve value within the corresponding time in the future as output to obtain the communication spectrum curve range threshold;

[0019] Among them, the communication spectrum trend analysis model expression is:

[0020]

[0021] Where S is the communication spectrum curve range threshold, is the time domain coefficient of the i-th time domain spectral characteristic parameter, is the i-th time-domain spectral characteristic parameter, is the frequency domain coefficient of the jth frequency domain spectral characteristic parameter, is the jth frequency domain spectral characteristic parameter, is the time operator, is the total number of time-domain spectral characteristic parameters, is the total number of frequency domain spectral characteristic parameters.

[0022] Preferably, the determining whether the communication spectrum curve value of the target optical fiber at the current moment exceeds the communication spectrum curve range threshold specifically includes:

[0023] Deploy several positions of Bragg gratings according to the communication nodes of the target optical fiber, divide the target optical fiber into several detection nodes, and obtain the real-time communication spectrum curve value of each detection node;

[0024] Based on a number of detection nodes of the target optical fiber, analyzing the operating status of the detection nodes, and evaluating the compensation coefficient of the detection nodes of the target optical fiber;

[0025] The real-time communication spectrum curve value of each detection node is compensated by using the compensation coefficient of the detection node of the target optical fiber to obtain the real-time communication spectrum curve compensation value of the detection node of the target optical fiber;

[0026] Determine whether the real-time communication spectrum curve compensation value of the detection node of the target optical fiber exceeds the communication spectrum curve range threshold, if not, do not make any response, if yes, mark the spectrum parameter that exceeds the range threshold;

[0027] Among them, the real-time communication spectrum curve compensation value of the detection node of the target optical fiber is specifically:

[0028]

[0029] In the formula, is the real-time communication spectrum curve compensation value of the kth detection node of the target optical fiber, is the real-time communication spectrum curve value of the kth detection node, is the compensation coefficient of the kth detection node, and L is the total number of detection nodes.

[0030] Preferably, the analyzing the operating status of the detection nodes based on the target optical fiber and evaluating the compensation coefficient of the detection node of the target optical fiber specifically includes:

[0031] Determine the basic loss rate of the target optical fiber based on the service life of the target optical fiber;

[0032] Acquire historical maintenance data of a target optical fiber, divide the historical maintenance data according to a number of detection nodes of the target optical fiber, and obtain historical maintenance data of the detection nodes of the target optical fiber;

[0033] Based on the historical maintenance data of the detection node of the target optical fiber, abnormal events appearing in the historical maintenance data are marked and recorded as loss influencing factors of the detection node;

[0034] Determine the quantitative value of each loss influencing factor according to the loss degree of each loss influencing factor on the target optical fiber;

[0035] Based on the quantified value of each loss influencing factor, the basic loss rate of the target optical fiber is corrected to obtain the corrected loss rate of the detection node of the target optical fiber;

[0036] Based on the basic loss rate of the target optical fiber and the corrected loss rate of the detection node of the target optical fiber, a compensation coefficient of the detection node of the target optical fiber is calculated through a compensation algorithm;

[0037] The compensation algorithm expression is:

[0038]

[0039] In the formula, is the compensation coefficient of the kth detection node, is the corrected loss rate of the kth detection node of the target optical fiber, is the basic loss rate of the target optical fiber, is the quantified value of the vth loss influencing factor of k detection nodes, is the weight of the vth loss influencing factor, is the margin factor, is the total number of factors affecting loss.

[0040] Preferably, performing abnormal fitting analysis on the spectral parameters exceeding the range threshold and judging whether the abnormal fitting degree matches the corresponding communication network attack event specifically includes:

[0041] Based on the physical communication network attack events of known target optical fibers, active attack verification is performed to collect the spectral characteristic curve data under physical communication network attacks;

[0042] Based on the spectral parameters marked as exceeding the range threshold, intercepting the real-time communication spectral curve data corresponding to the spectral parameters exceeding the range threshold;

[0043] The spectral characteristic curve data under the attack of the physical communication network is taken as a matching set, and the real-time communication spectral curve data corresponding to the spectral parameters exceeding the range threshold is taken as a to-be-matched set. The matching set is fragmented according to the minimum transmission unit of the optical signal, and the to-be-matched set is fragmented and randomly stored to obtain an ordered matching set and an unordered to-be-matched set.

[0044] According to the data index of the unordered set to be matched, each fragmented spectral characteristic curve in the ordered matching set is fitted and checked cyclically to obtain the abnormal fitting index of the spectral parameters exceeding the range threshold;

[0045] Setting the fitting threshold of communication network attack events;

[0046] Determine whether the abnormal fitting index of the spectral parameter exceeding the range threshold exceeds the communication network attack event fitting threshold, if not, report the optical fiber damage, if so, intercept the optical signal and report the physical communication network attack;

[0047] Among them, the calculation expression of the abnormal fitting index of the spectral parameters exceeding the range threshold is:

[0048]

[0049] In the formula, is the abnormal fitting index of the spectral parameters beyond the range threshold, is the spectral characteristic curve parameter value of the zth sample in the ordered matching set, is the spectral characteristic curve parameter value of the zth sample in the unordered matching set, is the total number of samples.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] The present invention proposes a communication network security detection scheme based on Bragg grating. Based on the Bragg grating reflection principle, the optical signal reflection spectrum data inside the optical fiber during data communication is collected for learning, the corresponding spectrum curve threshold in the future moment is analyzed, and the spectrum curve value of the optical signal in the real-time communication process is compared to screen out abnormal communication spectrum curves, perform abnormal event fitting verification, determine whether the corresponding abnormal event is a communication network attack behavior, and realize the detection of light leakage attack and light injection attack at the physical level. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 This is a framework diagram of a communication network security detection system based on Bragg grating;

[0053] Figure 2 A flow chart of a method for obtaining a range threshold value of a communication spectrum curve;

[0054] Figure 3 Flowchart of a method for marking spectral parameters that exceed a range threshold;

[0055] Figure 4 A flow chart of a method for evaluating a compensation coefficient of a detection node of a target optical fiber;

[0056] Figure 5A flow chart of a method for determining whether an abnormal fit matches a corresponding communication network attack event. DETAILED DESCRIPTION

[0057] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0058] Reference Figure 1 As shown, a communication network security detection system based on Bragg grating includes:

[0059] Data acquisition module, threshold analysis module, real-time monitoring module, preliminary screening module, abnormality judgment module;

[0060] The data acquisition module is used to deploy Bragg gratings according to the communication nodes of the target optical fiber to obtain the historical communication spectrum data of the target optical fiber;

[0061] The threshold analysis module is electrically connected to the data acquisition module, and the threshold analysis module is used to analyze the optical signal change trend in the historical communication spectrum data based on the historical communication spectrum data to obtain the communication spectrum curve range threshold;

[0062] The real-time monitoring module is used to obtain the real-time communication spectrum data of the target optical fiber and determine the communication spectrum curve value of the target optical fiber at the current moment;

[0063] The preliminary screening module is electrically connected to the threshold analysis module and the real-time monitoring module. The preliminary screening module is used to determine whether the communication spectrum curve value of the target optical fiber at the current moment exceeds the communication spectrum curve range threshold. If not, no response is made. If so, the spectrum parameter exceeding the range threshold is marked.

[0064] The abnormal judgment module is electrically connected to the preliminary screening module. The abnormal judgment module is used to perform abnormal fitting analysis on the spectral parameters that exceed the range threshold, and determine whether the abnormal fitting degree matches the corresponding communication network attack event. If not, report optical fiber damage. If so, intercept the optical signal and report the physical communication network attack.

[0065] This solution is based on the Bragg grating reflection principle. It collects the optical signal reflection spectral data inside the optical fiber during data communication for learning, analyzes the corresponding spectral curve threshold in the future, and compares it with the optical signal spectral curve value in the real-time communication process. It screens out abnormal communication spectral curves, performs abnormal event fitting verification, and determines whether the corresponding abnormal event is a communication network security attack behavior, thereby realizing the detection of optical leakage attacks and optical injection attacks at the physical level.

[0066] Reference Figure 2As shown, the analysis of the optical signal change trend in the historical communication spectrum data based on the historical communication spectrum data and obtaining the communication spectrum curve range threshold specifically includes:

[0067] Based on the historical communication spectrum data of the target optical fiber, the spectrum parameters in the spectrum data are screened out to obtain the communication spectrum parameter data;

[0068] According to the communication spectrum parameter data, the parameter values ​​of the corresponding spectrum parameters are counted to obtain the communication time-domain spectrum characteristic parameter data; the communication time-domain spectrum characteristic parameters include: the mean value of the optical signal, the standard deviation of the optical signal, and the extreme value of the optical signal;

[0069] According to the communication spectrum parameter data, the communication spectrum parameter data is converted into the frequency domain through the Fourier transform function, and the parameter value of the frequency domain spectrum parameter is marked to obtain the communication frequency domain spectrum characteristic parameter data; the communication frequency domain spectrum parameter includes: the main frequency of the optical signal, the bandwidth of the optical signal, and the power spectrum density of the optical signal;

[0070] Based on time series analysis SARIMA, a communication spectrum trend analysis model is trained;

[0071] Substitute the communication spectrum parameter data into the communication spectrum trend analysis model, take the time domain spectrum characteristic parameters and frequency domain spectrum characteristic parameters in the communication spectrum parameter data within a unit time as input, and predict the spectrum curve value within the corresponding time in the future as output to obtain the communication spectrum curve range threshold;

[0072] Among them, the communication spectrum trend analysis model expression is:

[0073]

[0074] Where S is the communication spectrum curve range threshold, is the time domain coefficient of the i-th time domain spectral characteristic parameter, is the i-th time-domain spectral characteristic parameter, is the frequency domain coefficient of the jth frequency domain spectral characteristic parameter, is the jth frequency domain spectral characteristic parameter, is the time operator, is the total number of time-domain spectral characteristic parameters, is the total number of frequency domain spectral characteristic parameters.

[0075] It can be understood that although the values ​​observed in the time scale of the near-end observation window for data transmission are usually disordered and non-normally distributed, when the time scale of the observation window is taken as the total amount of data as the observation target, the values ​​of the transmission data are regular and observable. Therefore, by analyzing the values ​​of the transmission data under the total time length and learning the trend of the transmission data under time correlation, the value range of the spectral curve in the target optical fiber corresponding to the transmission data in each time period can be analyzed;

[0076] Reference Figure 3 As shown, the determination of whether the communication spectrum curve value of the target optical fiber at the current moment exceeds the communication spectrum curve range threshold specifically includes:

[0077] Deploy several positions of Bragg gratings according to the communication nodes of the target optical fiber, divide the target optical fiber into several detection nodes, and obtain the real-time communication spectrum curve value of each detection node;

[0078] Based on a number of detection nodes of the target optical fiber, analyzing the operating status of the detection nodes, and evaluating the compensation coefficient of the detection nodes of the target optical fiber;

[0079] The real-time communication spectrum curve value of each detection node is compensated by using the compensation coefficient of the detection node of the target optical fiber to obtain the real-time communication spectrum curve compensation value of the detection node of the target optical fiber;

[0080] Determine whether the real-time communication spectrum curve compensation value of the detection node of the target optical fiber exceeds the communication spectrum curve range threshold, if not, do not make any response, if yes, mark the spectrum parameter that exceeds the range threshold;

[0081] Among them, the real-time communication spectrum curve compensation value of the detection node of the target optical fiber is specifically:

[0082]

[0083] In the formula, is the real-time communication spectrum curve compensation value of the kth detection node of the target optical fiber, is the real-time communication spectrum curve value of the kth detection node, is the compensation coefficient of the kth detection node, and L is the total number of detection nodes.

[0084] It is understandable that since the reflection characteristic of the Bragg grating is based on the reflection spectrum every time a light signal passes through, the reflection value of the spectrum is also affected by the state of the target optical fiber. For example, at several locations where the Bragg grating is deployed, due to the wear of the protective layer of the target optical fiber at one or more of the deployment locations, the reflected spectral data is different. At this time, due to the volatility of the spectral data, misjudgment is prone to occur, affecting the final detection result. Therefore, the real-time communication spectral curve value is compensated by analyzing the state of the target optical fiber to ensure the accuracy of the data.

[0085] Reference Figure 4 As shown, the analysis of the operating status of the detection nodes based on the target optical fiber and the evaluation of the compensation coefficient of the detection node of the target optical fiber specifically include:

[0086] Determine the basic loss rate of the target optical fiber based on the service life of the target optical fiber;

[0087] Acquire historical maintenance data of a target optical fiber, divide the historical maintenance data according to a number of detection nodes of the target optical fiber, and obtain historical maintenance data of the detection nodes of the target optical fiber;

[0088] Based on the historical maintenance data of the detection node of the target optical fiber, abnormal events appearing in the historical maintenance data are marked and recorded as loss influencing factors of the detection node;

[0089] Determine the quantitative value of each loss influencing factor according to the loss degree of each loss influencing factor on the target optical fiber;

[0090] Based on the quantified value of each loss influencing factor, the basic loss rate of the target optical fiber is corrected to obtain the corrected loss rate of the detection node of the target optical fiber;

[0091] Based on the basic loss rate of the target optical fiber and the corrected loss rate of the detection node of the target optical fiber, a compensation coefficient of the detection node of the target optical fiber is calculated through a compensation algorithm;

[0092] The compensation algorithm expression is:

[0093]

[0094] In the formula, is the compensation coefficient of the kth detection node, is the corrected loss rate of the kth detection node of the target optical fiber, is the basic loss rate of the target optical fiber, is the quantified value of the vth loss influencing factor of k detection nodes, is the weight of the vth loss influencing factor, is the margin factor, is the total number of factors affecting loss.

[0095] It should be noted that the quantified value of the loss influencing factor is an assessment of the loss state of the target optical fiber based on the score of the abnormal event given by the maintenance personnel in the maintenance log, which is well known to those skilled in the art and will not be described in detail here.

[0096] Reference Figure 5 As shown, the abnormal fitting analysis is performed on the spectral parameters exceeding the range threshold, and judging whether the abnormal fitting degree matches the corresponding communication network attack event specifically includes:

[0097] Based on the physical communication network attack events of known target optical fibers, active attack verification is performed to collect the spectral characteristic curve data under physical communication network attacks;

[0098] Based on the spectral parameters marked as exceeding the range threshold, intercepting the real-time communication spectral curve data corresponding to the spectral parameters exceeding the range threshold;

[0099] The spectral characteristic curve data under the attack of the physical communication network is taken as a matching set, and the real-time communication spectral curve data corresponding to the spectral parameters exceeding the range threshold is taken as a to-be-matched set. The matching set is fragmented according to the minimum transmission unit of the optical signal, and the to-be-matched set is fragmented and randomly stored to obtain an ordered matching set and an unordered to-be-matched set.

[0100] According to the data index of the unordered set to be matched, each fragmented spectral characteristic curve in the ordered matching set is fitted and checked cyclically to obtain the abnormal fitting index of the spectral parameters exceeding the range threshold;

[0101] Setting the fitting threshold of communication network attack events;

[0102] Determine whether the abnormal fitting index of the spectral parameter exceeding the range threshold exceeds the communication network attack event fitting threshold, if not, report the optical fiber damage, if so, intercept the optical signal and report the physical communication network attack;

[0103] Among them, the calculation expression of the abnormal fitting index of the spectral parameters exceeding the range threshold is:

[0104]

[0105] In the formula, is the abnormal fitting index of the spectral parameters beyond the range threshold, is the spectral characteristic curve parameter value of the zth sample in the ordered matching set, is the spectral characteristic curve parameter value of the zth sample in the unordered matching set, is the total number of samples.

[0106] It can be understood that the communication network attack event fitting threshold is assigned based on the frequency of attacks on the target optical fiber combined with actual experience. For example, when the target optical fiber is historically attacked at a high frequency, its corresponding attack confidence is relatively high. Therefore, the sensitivity of the communication network attack event fitting threshold to the abnormal fitting index of the spectral parameters exceeding the range threshold needs to be set based on actual experience and the attack frequency. This is a method well known to those skilled in the art and will not be described in detail here.

[0107] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A communication network security detection system based on Bragg grating, characterized in that: include: Data acquisition module, threshold analysis module, real-time monitoring module, preliminary screening module, abnormality judgment module; The data acquisition module is used to deploy Bragg gratings according to the communication nodes of the target optical fiber to obtain the historical communication spectrum data of the target optical fiber; The threshold analysis module is electrically connected to the data acquisition module, and the threshold analysis module is used to analyze the optical signal change trend in the historical communication spectrum data based on the historical communication spectrum data to obtain the communication spectrum curve range threshold; The real-time monitoring module is used to obtain the real-time communication spectrum data of the target optical fiber and determine the communication spectrum curve value of the target optical fiber at the current moment; The preliminary screening module is electrically connected to the threshold analysis module and the real-time monitoring module. The preliminary screening module is used to determine whether the communication spectrum curve value of the target optical fiber at the current moment exceeds the communication spectrum curve range threshold. If not, no response is made. If so, the spectrum parameter exceeding the range threshold is marked. The abnormality judgment module is electrically connected to the preliminary screening module, and is used to perform abnormal fitting analysis on the spectral parameters exceeding the range threshold, and judge whether the abnormal fitting degree matches the corresponding communication network attack event. If not, report the optical fiber damage, and if so, intercept the optical signal and report the physical communication network attack; The method of analyzing the optical signal variation trend in the historical communication spectrum data based on the historical communication spectrum data and obtaining the communication spectrum curve range threshold specifically includes: Based on the historical communication spectrum data of the target optical fiber, the spectrum parameters in the spectrum data are screened out to obtain the communication spectrum parameter data; According to the communication spectrum parameter data, the parameter values ​​of the corresponding spectrum parameters are counted to obtain the communication time-domain spectrum characteristic parameter data; the communication time-domain spectrum characteristic parameters include: the mean value of the optical signal, the standard deviation of the optical signal, and the extreme value of the optical signal; According to the communication spectrum parameter data, the communication spectrum parameter data is converted into the frequency domain through the Fourier transform function, and the parameter value of the frequency domain spectrum parameter is marked to obtain the communication frequency domain spectrum characteristic parameter data; the communication frequency domain spectrum characteristic parameters include: the main frequency of the optical signal, the bandwidth of the optical signal, and the power spectrum density of the optical signal; Based on time series analysis SARIMA, a communication spectrum trend analysis model is trained; Substitute the communication spectrum parameter data into the communication spectrum trend analysis model, take the time domain spectrum characteristic parameters and frequency domain spectrum characteristic parameters in the communication spectrum parameter data within a unit time as input, and predict the spectrum curve value within the corresponding time in the future as output to obtain the communication spectrum curve range threshold; The abnormal fitting analysis is performed on the spectral parameters exceeding the range threshold, and judging whether the abnormal fitting degree matches the corresponding communication network attack event specifically includes: Based on the physical communication network attack events of known target optical fibers, active attack verification is performed to collect the spectral characteristic curve data under physical communication network attacks; Based on the spectral parameters marked as exceeding the range threshold, intercepting the real-time communication spectral curve data corresponding to the spectral parameters exceeding the range threshold; The spectral characteristic curve data under the attack of the physical communication network is taken as a matching set, and the real-time communication spectral curve data corresponding to the spectral parameters exceeding the range threshold is taken as a to-be-matched set. The matching set is fragmented according to the minimum transmission unit of the optical signal, and the to-be-matched set is fragmented and randomly stored to obtain an ordered matching set and an unordered to-be-matched set. According to the data index of the unordered set to be matched, each fragmented spectral characteristic curve in the ordered matching set is fitted and checked cyclically to obtain the abnormal fitting index of the spectral parameters exceeding the range threshold; Setting the fitting threshold of communication network attack events; Determine whether the abnormal fitting index of the spectral parameters that exceed the range threshold exceeds the communication network attack event fitting threshold. If not, report optical fiber damage. If so, intercept the optical signal and report the physical communication network attack.

2. A communication network security detection system based on Bragg grating according to claim 1, characterized in that: The communication spectrum trend analysis model expression is: Where S is the communication spectrum curve range threshold, is the time domain coefficient of the i-th time domain spectral characteristic parameter, is the i-th time-domain spectral characteristic parameter, is the frequency domain coefficient of the jth frequency domain spectral characteristic parameter, is the jth frequency domain spectral characteristic parameter, is the time operator, is the total number of time-domain spectral characteristic parameters, is the total number of frequency domain spectral characteristic parameters.

3. A communication network security detection system based on Bragg grating according to claim 2, characterized in that: The determining whether the communication spectrum curve value of the target optical fiber at the current moment exceeds the communication spectrum curve range threshold specifically includes: Deploy several positions of Bragg gratings according to the communication nodes of the target optical fiber, divide the target optical fiber into several detection nodes, and obtain the real-time communication spectrum curve value of each detection node; Based on a number of detection nodes of the target optical fiber, analyzing the operating status of the detection nodes, and evaluating the compensation coefficient of the detection nodes of the target optical fiber; The real-time communication spectrum curve value of each detection node is compensated by using the compensation coefficient of the detection node of the target optical fiber to obtain the real-time communication spectrum curve compensation value of the detection node of the target optical fiber; It is determined whether the real-time communication spectrum curve compensation value of the detection node of the target optical fiber exceeds the communication spectrum curve range threshold. If not, no response is made. If yes, the spectrum parameter exceeding the range threshold is marked.

4. A communication network security detection system based on Bragg grating according to claim 3, characterized in that: The method of analyzing the operating status of the detection nodes based on the target optical fiber and evaluating the compensation coefficient of the detection nodes of the target optical fiber specifically includes: Determine the basic loss rate of the target optical fiber based on the service life of the target optical fiber; Acquire historical maintenance data of a target optical fiber, divide the historical maintenance data according to a number of detection nodes of the target optical fiber, and obtain historical maintenance data of the detection nodes of the target optical fiber; Based on the historical maintenance data of the detection node of the target optical fiber, abnormal events appearing in the historical maintenance data are marked and recorded as loss influencing factors of the detection node; Determine the quantitative value of each loss influencing factor according to the loss degree of each loss influencing factor on the target optical fiber; Based on the quantified value of each loss influencing factor, the basic loss rate of the target optical fiber is corrected to obtain the corrected loss rate of the detection node of the target optical fiber; Based on the basic loss rate of the target optical fiber and the corrected loss rate of the detection node of the target optical fiber, a compensation coefficient of the detection node of the target optical fiber is calculated through a compensation algorithm.

5. A communication network security detection system based on Bragg grating according to claim 4, characterized in that: The compensation algorithm expression is: In the formula, is the compensation coefficient of the kth detection node, is the corrected loss rate of the kth detection node of the target optical fiber, is the basic loss rate of the target optical fiber, is the quantified value of the vth loss influencing factor of k detection nodes, is the weight of the vth loss influencing factor, is the margin factor, is the total number of factors affecting loss.

6. A communication network security detection system based on Bragg grating according to claim 5, characterized in that: The calculation expression of the abnormal fitting index of the spectral parameters beyond the range threshold is: In the formula, is the abnormal fitting index of the spectral parameters beyond the range threshold, is the spectral characteristic curve parameter value of the zth sample in the ordered matching set, is the spectral characteristic curve parameter value of the zth sample in the unordered matching set, is the total number of samples.

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