CN115460304A - Protocol layer data analysis method and system for intercepting wireless communication - Google Patents
Protocol layer data analysis method and system for intercepting wireless communication Download PDFInfo
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Abstract
The invention relates to the technical field of ETC data interception, and particularly discloses a protocol layer data analysis method and a system for intercepting wireless communication, wherein the method comprises the steps of acquiring communication data containing an initial signal and a cut-off signal in real time, and determining a time window according to the acquisition time of the initial signal and the cut-off signal; intercepting communication data according to the time window to obtain a subdata segment, and determining characteristic parameters of the subdata segment; counting the characteristic parameters to obtain n-dimensional characteristics of the communication data, and clustering the communication data according to the n-dimensional characteristics; and when the cutoff signal is not acquired within a preset time range, classifying the communication data according to the initial signal, and judging whether the data downlink process has a problem according to a classification result. The invention provides a dynamic and intelligent communication data identification process, which has stronger adaptability compared with the traditional static comparison algorithm (comparing the communication data with the preset standard data).
Description
Technical Field
The invention relates to the technical field of ETC data interception, in particular to a protocol layer data analysis method and system for intercepting wireless communication.
Background
ETC equipment on the existing market, the main body communication function is the receiving and sending of 5.8G signals. However, different ETC devices of different types and brands have different performances, and the problem of device loss is solved, so that the problem of abnormal communication is difficult to avoid in the communication process, and for the problem of abnormal communication, the ETC devices are difficult to directly position for solution, especially the ETC devices at the installed positions. For example, after the RSU device transmits the BST, it cannot directly determine whether the BST transmitted by the RSU is faulty, whether the OBU does not receive the BST information, or whether the OBU transmits the VST information but the RSU does not successfully receive the BST information.
Wherein, each noun is described as follows:
the RSU equipment: the RSU is used as a roadside unit of the C-V2X technology and is responsible for receiving real-time traffic information such as road condition information and the like sent by a traffic signal machine/application server and dynamically broadcasting the real-time traffic information to passing vehicles, so that traffic accidents are reduced and avoided, and traffic passing efficiency is improved.
An OBU: vehicle-mounted electronic tag. The OBU equipment is mostly arranged on a front windshield of an automobile, and is communicated with a Road Side Unit (RSU) through microwaves at a toll station. When the vehicle approaches the gear lever, the RSU recognizes a signal from the OBU, and the gear lever is automatically opened, so that the function of automatically controlling passing is realized.
The english acronym "BST" is often used as an abbreviation for "Beacon Service Table," which stands for: "Beacon service Table".
VST information: and responding the information.
Disclosure of Invention
The present invention is directed to a method and a system for parsing protocol layer data for intercepting wireless communications, so as to solve the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme:
a protocol layer data parsing method for listening for wireless communications, the method comprising:
acquiring communication data containing an initial signal and a cut-off signal in real time, and determining a time window according to the acquisition time of the initial signal and the cut-off signal;
intercepting communication data according to the time window to obtain a subdata segment, and determining characteristic parameters of the subdata segment; the characteristic parameters comprise time characteristics and function characteristics of a superposition function obtained after Fourier transform is carried out on the communication data;
counting the characteristic parameters to obtain n-dimensional characteristics of the communication data, and clustering the communication data according to the n-dimensional characteristics;
and when the cutoff signal is not acquired within a preset time range, classifying the communication data according to the initial signal, and judging whether the data downlink process has a problem according to a classification result.
As a further scheme of the invention: the step of acquiring communication data containing an initial signal and a cut-off signal in real time and determining a time window according to the acquisition time of the initial signal and the cut-off signal comprises the following steps:
when an initial signal is received according to a preset trigger, reading communication data in real time until a cut-off signal is received by the preset trigger; wherein the trigger records the receiving time in real time;
determining a time interval according to the receiving time of the cutoff signal and the receiving time of the initial signal;
determining sampling points according to the time intervals, and correcting the sampling points according to the data quantity at the sampling points;
and determining a time window according to the corrected sampling points.
As a further scheme of the invention: the step of intercepting the communication data according to the time window to obtain a sub-data segment and determining the characteristic parameters of the sub-data segment comprises the following steps:
intercepting communication data according to the time window to obtain sub data segments;
performing Fourier transform on the sub data segments to obtain a superposition function consisting of trigonometric functions; the number of terms of the superposition function is a preset value;
sequentially acquiring trigonometric function characteristics of each item in the superposition function, and generating a characteristic matrix according to a preset arrangement sequence;
and reading the time window of the sub data segment, generating a time sequence, and inserting a characteristic matrix to obtain the characteristic parameters of the sub data segment.
As a further scheme of the invention: the step of counting the characteristic parameters to obtain n-dimensional characteristics of the communication data, and the step of clustering each communication data according to the n-dimensional characteristics comprises the following steps:
reading and connecting the feature matrix of each sub-data segment, and extracting n-dimensional features from the feature matrix according to a preset rule; wherein the n-dimensional feature comprises a temporal feature determined by a time series;
determining K central points according to the time characteristics, and classifying communication data according to the central points to obtain K point families;
and updating the central points in each point family according to a preset iteration formula until the iteration difference value between the central points of two adjacent times is smaller than a preset threshold value.
As a further scheme of the invention: the step of determining K central points according to the time characteristics and classifying the communication data according to the central points to obtain K point families comprises the following steps:
receiving K time periods input by a user, matching the time periods with the time sequences in each piece of communication data according to the classification time periods, and randomly selecting K central points; one time period corresponds to one central point;
sequentially reading n-dimensional features of the communication data, and inputting a preset distance formula of the n-dimensional features containing the central point to obtain a distance;
selecting a central point corresponding to the minimum distance, and classifying the communication data and the central point into one class;
the distance formula is:
As a further scheme of the invention: the iterative formula is:
in the formula (I), the compound is shown in the specification,
is the center point of the kth point family;
the number of points in the kth point family;
a set of kth point families;
is the ith point in the kth family of points.
As a further scheme of the invention: when the cutoff signal is not acquired within a preset time range, classifying the communication data according to the initial signal, and judging whether the data downlink process has problems according to the classification result comprises the following steps:
when the cutoff signal is not acquired within a preset time range, generating a cutoff instruction;
determining a time window according to the acquisition time of the initial signal and the generation time of the cut-off instruction;
intercepting the communication data according to the time window to obtain sub data segments and determining characteristic parameters of the sub data segments to obtain n-dimensional characteristics of the communication data;
inputting the n-dimensional features into the distance formula, and determining a corresponding central point of the communication data;
inquiring the time sequence of the central point, and judging the abnormal probability of the time window according to the time sequence;
and when the abnormal probability reaches a preset abnormal condition, judging that the data downlink process has a problem.
The technical scheme of the invention also provides a protocol layer data analysis system for intercepting wireless communication, which comprises:
the time window determining module is used for acquiring communication data containing an initial signal and a cut-off signal in real time and determining a time window according to the acquisition time of the initial signal and the cut-off signal;
the characteristic parameter determining module is used for intercepting communication data according to the time window to obtain a subdata segment and determining the characteristic parameter of the subdata segment; the characteristic parameters comprise time characteristics and function characteristics of a superposition function obtained after Fourier transform is carried out on the communication data;
the data clustering module is used for counting the characteristic parameters to obtain n-dimensional characteristics of the communication data and clustering the communication data according to the n-dimensional characteristics;
and the problem judgment module is used for classifying the communication data according to the initial signal when the cutoff signal is not acquired within a preset time range, and judging whether the data downlink process has a problem or not according to a classification result.
As a further scheme of the invention: the time window determination module comprises:
the signal receiving unit is used for reading communication data in real time when an initial signal is received according to a preset trigger until a cut-off signal is received by the preset trigger; wherein the trigger records the receiving time in real time;
an interval calculation unit for determining a time interval according to a reception time of the cutoff signal and a reception time of the initial signal;
the sampling point determining unit is used for determining sampling points according to the time intervals and correcting the sampling points according to the data quantity of the sampling points;
and the execution unit is used for determining a time window according to the corrected sampling point.
As a further scheme of the invention: the characteristic parameter determination module comprises:
the data intercepting unit is used for intercepting the communication data according to the time window to obtain the subdata segments;
the data transformation unit is used for carrying out Fourier transformation on the sub data segments to obtain a superposition function consisting of trigonometric functions; the number of terms of the superposition function is a preset value;
the characteristic matrix generating unit is used for sequentially acquiring the trigonometric function characteristics of all items in the superposition function and generating a characteristic matrix according to a preset arrangement sequence;
and the time sequence filling unit is used for reading the time window of the sub data segment, generating a time sequence and inserting the characteristic matrix to obtain the characteristic parameters of the sub data segment.
Compared with the prior art, the invention has the beneficial effects that: the method comprises the steps of processing a data transmission process at one end in a single way, extracting communication data, segmenting the communication data into subsections, and extracting characteristics of the subsections to obtain the characteristics of the communication data; clustering according to the characteristics of normal communication data, classifying abnormal communication data based on a clustering result when the abnormal communication data is received, and judging whether a problem exists in the data transmission process according to the classification result; the invention provides a dynamic and intelligent communication data identification process, which has stronger adaptability compared with the traditional static comparison algorithm (comparing the communication data with the preset standard data).
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention.
Fig. 1 is a flow diagram of a protocol layer data parsing method for listening for wireless communications.
Fig. 2 is a first sub-flow block diagram of a protocol layer data parsing method for listening for wireless communications.
Fig. 3 is a second sub-flow block diagram of a protocol layer data parsing method for listening for wireless communications.
Fig. 4 is a third sub-flow block diagram of a protocol layer data parsing method for listening for wireless communications.
Fig. 5 is a fourth sub-flow block diagram of a protocol layer data parsing method for listening for wireless communications.
Fig. 6 is a block diagram of a protocol layer data parsing system for listening for wireless communications.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects to be solved by the present invention more clearly apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example 1
Fig. 1 is a flow chart of a protocol layer data parsing method for intercepted wireless communication, in an embodiment of the present invention, a protocol layer data parsing method for intercepted wireless communication includes:
step S100: acquiring communication data containing an initial signal and a cut-off signal in real time, and determining a time window according to the acquisition time of the initial signal and the cut-off signal;
for example, after the RSU device transmits the BST, it cannot directly determine whether the BST transmitted by the RSU is faulty, or the OBU does not receive the BST information, or the OBU transmits the VST information but the RSU does not successfully receive the BST information. The BST is sent to be an initial signal, and the VST information returned by the OBU is received to be cut-off information; the technical scheme of the invention aims to judge whether the process of transmitting BST by RSU equipment has problems; a time window sequence can be calculated by the initial signal and the cut-off signal, communication data are intercepted according to the time window sequence, the communication data are screened, data identification amount is reduced, and data identification efficiency is improved.
Step S200: intercepting communication data according to the time window to obtain a subdata segment, and determining characteristic parameters of the subdata segment; the characteristic parameters comprise time characteristics and function characteristics of a superposition function obtained after Fourier transform is carried out on the communication data;
intercepting the communication data according to the time window to obtain a plurality of sub-data sections, and extracting characteristic parameters of the sub-data sections to reflect the characteristics of the communication data; since the sub-data segments are signals, and all the signals can understand the superposition state of a plurality of trigonometric functions, the signals can be converted into functions according to Fourier transform, and further characteristic parameters of the sub-data segments are determined according to the function characteristics.
Step S300: counting the characteristic parameters to obtain n-dimensional characteristics of the communication data, and clustering the communication data according to the n-dimensional characteristics;
the characteristic of one communication data is determined by characteristic parameters of a plurality of sub-data segments, and the dimension of the characteristic is determined by a worker according to the situation and is not limited specifically; from the n-dimensional features, the communication data may be clustered.
Step S400: when the cutoff signal is not acquired within a preset time range, classifying the communication data according to the initial signal, and judging whether a problem exists in the data downlink process according to a classification result;
when the cutoff signal is not acquired within a preset time range, the communication process is indicated to have a problem, at the moment, communication data are acquired, the communication data are classified, and the real-time classification result and the theoretical classification result are compared, so that whether the data issuing process has a problem or not can be judged; the theoretical classification result is related to time information, and normal communication data in the same time period are classified into one class.
It should be noted that the application main body of the technical scheme of the present invention is the upper end, that is, the party issuing data, and therefore, it is determined whether there is a problem in the data issuing process; if the application main body of the technical scheme of the invention is the lower end, whether the data uploading process has a problem is judged.
Further, the above nouns are explained:
the RSU equipment: the RSU is used as a roadside unit of the C-V2X technology and is responsible for receiving real-time traffic information such as road condition information and the like sent by a traffic signal machine/application server and dynamically broadcasting the real-time traffic information to passing vehicles, so that traffic accidents are reduced and avoided, and traffic passing efficiency is improved.
An OBU: vehicle-mounted electronic tag. The OBU equipment is mostly arranged on the front windshield of the automobile, and is communicated with the road side unit RSU through microwaves at the toll station. When the vehicle approaches the gear lever, the RSU recognizes a signal from the OBU, and the gear lever is automatically opened, so that the function of automatically controlling passing is realized.
The english acronym "BST" is often used as an abbreviation for "Beacon Service Table," which stands for: beacon service table "
VST information: and responding to the information.
Fig. 2 is a first sub-flow diagram of a protocol layer data parsing method for intercepting wireless communications, where the step of acquiring communication data containing an initial signal and a stop signal in real time and determining a time window according to acquisition times of the initial signal and the stop signal includes:
step S101: when an initial signal is received according to a preset trigger, reading communication data in real time until a cut-off signal is received by the preset trigger; wherein the trigger records the receiving time in real time;
the trigger comprises a software layer and a hardware layer and is used for detecting an initial signal and a cut-off signal;
step S102: determining a time interval according to the receiving time of the cutoff signal and the receiving time of the initial signal;
the time interval, which is the period to be analyzed, is determined from the cutoff signal and the initial signal, and the communication data in this period is the data to be analyzed.
Step S103: determining sampling points according to the time intervals, and correcting the sampling points according to the data quantity at the sampling points;
determining sampling points in the time interval according to a preset sampling frequency, and correcting the sampling points according to whether data exist at the sampling points or not; the correction mode can be that if there is no data at the sampling point, the corresponding sampling point is deleted, if there is data at the sampling point, the adjacent sampling point is judged to have data, if there is no data at the adjacent sampling point, the sampling point is translated to determine the data boundary; the above process is repeated so that the sample point comprises a signal segment in which data is present.
Step S104: determining a time window according to the corrected sampling point;
and determining a signal section with data according to the corrected sampling point, wherein the corresponding time period is the time window.
Fig. 3 is a second sub-flow diagram of a protocol layer data parsing method for intercepting wireless communications, where the intercepting of the communication data according to the time window to obtain sub-data segments and the determining of the characteristic parameters of the sub-data segments include:
step S201: intercepting communication data according to the time window to obtain sub data segments;
intercepting the communication data into separated subdata segments according to the time window, and carrying out data analysis on the subdata segments;
step S202: performing Fourier transform on the sub-data segments to obtain a superposition function consisting of trigonometric functions; the number of terms of the superposition function is a preset value;
the data analysis mode of the sub-data segment is a data processing mode based on Fourier transform, the Fourier transform is carried out on the communication data, a plurality of superposed trigonometric functions can be obtained, and the first few items can be selected to be used as superposition functions.
Step S203: sequentially acquiring trigonometric function characteristics of each item in the superposition function, and generating a characteristic matrix according to a preset arrangement sequence;
the characteristics of the trigonometric function include amplitude, frequency and phase, and the characteristics are counted and arranged to obtain a matrix, wherein each row (column) in the matrix corresponds to a superposition function.
Step S204: reading the time window of the sub data segment, generating a time sequence, and inserting a characteristic matrix to obtain the characteristic parameters of the sub data segment;
except for the trigonometric function, the time window of the subdata segment reflects the time characteristics, the time characteristics are converted into a time sequence, and the characteristic matrix is inserted to obtain the characteristic parameters of the subdata segment.
Fig. 4 is a third sub-flow diagram of a protocol layer data parsing method for intercepting wireless communications, where the step of counting the characteristic parameters to obtain n-dimensional characteristics of the communication data and clustering the communication data according to the n-dimensional characteristics includes:
step S301: reading and connecting the feature matrix of each sub-data segment, and extracting n-dimensional features from the feature matrix according to a preset rule; wherein the n-dimensional feature comprises a temporal feature determined by a time series;
step S302: determining K central points according to the time characteristics, and classifying communication data according to the central points to obtain K point families;
step S303: and updating the central points in each point family according to a preset iteration formula until the iteration difference value between the central points of two adjacent times is smaller than a preset threshold value.
The clustering process of the communication data is specifically described, and the clustering process aims to classify the communication data in the same large time period into one class, wherein the reference basis of the classification is an n-dimensional feature; the n-dimensional features are extracted from the feature matrix of each sub-data segment, and specifically, the feature matrices of the sub-data segments are sequentially connected according to the time sequence of the sub-data segments to obtain a large matrix corresponding to the communication data; in this large matrix, n features, referred to as n-dimensional features, can be extracted to reflect the state of the communication data.
Determining some central points according to the time characteristics in the n-dimensional characteristics, and classifying all the points according to the central points in sequence; where a "point" is the representation of an n-dimensional feature in its n-dimensional space.
Further, the step of determining K central points according to the time characteristics and classifying the communication data according to the central points to obtain K point families includes:
receiving K time periods input by a user, matching the time periods with the time sequences in each piece of communication data according to the classification time periods, and randomly selecting K central points; one time period corresponds to one central point;
sequentially reading n-dimensional features of the communication data, and inputting a preset distance formula of the n-dimensional features containing the central point to obtain a distance;
selecting a central point corresponding to the minimum distance, and classifying the communication data and the central point into one class;
the distance formula is:
in the formula (I), the compound is shown in the specification,
the distance between the ith point and the central point; the n is the dimension of the n-dimensional feature vector;
the nth dimension characteristic of the ith point;
is the central point of the image,
the nth dimension feature of the center point.
The distance formula adopts an Euler formula, the distances between each point and a preset central point are sequentially calculated, and communication data are classified according to the distances.
Further, the iterative formula is:
in the formula (I), the compound is shown in the specification,
is the center point of the kth point family;
the number of points in the kth point family;
a set of kth point families;
is the ith point in the kth family of points.
After classifying all the communication data, calculating the average distance value between all the points and the central point in the same point family, determining a new central point according to the average value, clustering all the communication data again by taking the new central point as a reference, then re-determining the central point, and recursively executing the contents until the difference between the central points determined twice or more is small to a certain extent, and at the moment, finishing the clustering process.
Fig. 5 is a fourth sub-flow block diagram of a protocol layer data parsing method for intercepting wireless communications, where when a cutoff signal is not obtained within a preset time range, the step of classifying communication data according to the initial signal and determining whether a problem exists in a data downlink process according to a classification result includes:
step S401: when the cutoff signal is not acquired within a preset time range, generating a cutoff instruction;
step S402: determining a time window according to the acquisition time of the initial signal and the generation time of the cut-off instruction;
step S403: intercepting the communication data according to the time window to obtain sub data segments and determining characteristic parameters of the sub data segments to obtain n-dimensional characteristics of the communication data;
steps S401 to S403 are repeated for existing content, and are different in that when the cutoff signal is not received, a cutoff command is automatically generated as the cutoff signal.
Step S404: inputting the n-dimensional features into the distance formula, and determining a corresponding central point of the communication data;
inputting the n-dimensional characteristics of the communication data into a distance formula, calculating the distance between the n-dimensional characteristics and each central point, and classifying the communication data according to the distance, which is an actual classification result;
step S405: inquiring the time sequence of the central point, and judging the abnormal probability of the time window according to the time sequence;
inquiring the time sequence of the central point, obtaining a large time period of an actual classification result from the time sequence, at the moment, obtaining the time sequence in the n-dimensional feature, judging whether the time sequence in the n-dimensional feature is contained in the large time period, and determining the abnormal probability of the time window according to the inclusion relation of the two time sequences, for example, if the two time sequences are not jointed, the abnormal probability is 100%, if the time sequence in the n-dimensional feature is contained in the large time period, the abnormal probability is 0%, and if the two time sequences have an intersection, determining the abnormal probability according to the span of the intersection.
It should be noted that, the premise of the above is that the K central points are divided in a time series, so that the influence of the time feature in the n-dimensional feature is the largest.
Step S406: when the abnormal probability reaches a preset abnormal condition, judging that a problem exists in the data downlink process;
and comparing the abnormal probability with some preset abnormal threshold values to judge whether the data downlink process has problems.
It is worth mentioning that the data downlink process is judged unilaterally to be enough to carry out risk positioning on the system operation process, if the data downlink process has no problem but the communication process has a problem, the problem is indicated to be at other ports, and if the data downlink process has a problem, the communication process is indicated to be old and has a problem after the data downlink process is repaired, the problem is indicated to be at other ports; the technical scheme of the invention is mostly applied to the field of double-end interaction, and the actual problem can be positioned by judging a process in a single way.
Example 2
Fig. 6 is a block diagram of a protocol layer data parsing system for intercepting wireless communications, in an embodiment of the present invention, the protocol layer data parsing system for intercepting wireless communications includes:
the time window determining module 11 is configured to obtain communication data including an initial signal and a stop signal in real time, and determine a time window according to the obtaining time of the initial signal and the stop signal;
a characteristic parameter determining module 12, configured to intercept communication data according to the time window to obtain a sub data segment, and determine a characteristic parameter of the sub data segment; the characteristic parameters comprise time characteristics and function characteristics of a superposition function obtained after Fourier transform is carried out on the communication data;
the data clustering module 13 is configured to count the feature parameters to obtain n-dimensional features of the communication data, and perform clustering on each communication data according to the n-dimensional features;
and the problem judging module 14 is configured to classify the communication data according to the initial signal when the cutoff signal is not obtained within a preset time range, and judge whether a problem exists in a data downlink process according to a classification result.
The time window determination module 11 comprises:
the signal receiving unit is used for reading communication data in real time when an initial signal is received according to a preset trigger until a cut-off signal is received by the preset trigger; wherein, the trigger records the receiving time in real time;
an interval calculation unit for determining a time interval according to a reception time of the cutoff signal and a reception time of the initial signal;
the sampling point determining unit is used for determining sampling points according to the time intervals and correcting the sampling points according to the data quantity at the sampling points;
and the execution unit is used for determining a time window according to the corrected sampling point.
The characteristic parameter determination module 12 includes:
the data intercepting unit is used for intercepting the communication data according to the time window to obtain the subdata segments;
the data transformation unit is used for carrying out Fourier transformation on the sub data sections to obtain a superposition function consisting of trigonometric functions; the number of terms of the superposition function is a preset value;
the characteristic matrix generating unit is used for sequentially acquiring the trigonometric function characteristics of all items in the superposition function and generating a characteristic matrix according to a preset arrangement sequence;
and the time sequence filling unit is used for reading the time window of the sub data segment, generating a time sequence and inserting the characteristic matrix to obtain the characteristic parameters of the sub data segment.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (9)
1. A method of protocol layer data parsing for intercepted wireless communications, the method comprising:
acquiring communication data containing an initial signal and a cut-off signal in real time, and determining a time window according to the acquisition time of the initial signal and the cut-off signal;
intercepting communication data according to the time window to obtain a subdata segment, and determining characteristic parameters of the subdata segment; the characteristic parameters comprise time characteristics and function characteristics of a superposition function obtained after Fourier transform is carried out on the communication data;
counting the characteristic parameters to obtain n-dimensional characteristics of the communication data, and clustering the communication data according to the n-dimensional characteristics;
when a cutoff signal is not acquired within a preset time range, classifying the communication data according to the initial signal, and judging whether a problem exists in a data downlink process according to a classification result;
the step of counting the characteristic parameters to obtain n-dimensional characteristics of the communication data, and the step of clustering each communication data according to the n-dimensional characteristics comprises the following steps:
reading and connecting the feature matrix of each sub-data segment, and extracting n-dimensional features from the feature matrix according to a preset rule; wherein the n-dimensional feature contains a temporal feature determined by a time series;
determining K central points according to the time characteristics, and classifying communication data according to the central points to obtain K point families;
and updating the central points in each point family according to a preset iteration formula until the iteration difference value between the central points of two adjacent times is smaller than a preset threshold value.
2. The protocol layer data parsing method for intercepting wireless communications according to claim 1, wherein the step of acquiring the communication data containing the initial signal and the cutoff signal in real time, and the step of determining the time window according to the acquisition time of the initial signal and the cutoff signal comprises:
when an initial signal is received according to a preset trigger, reading communication data in real time until a cut-off signal is received by the preset trigger; wherein, the trigger records the receiving time in real time;
determining a time interval according to the receiving time of the cutoff signal and the receiving time of the initial signal;
determining sampling points according to the time intervals, and correcting the sampling points according to the data quantity at the sampling points;
and determining a time window according to the corrected sampling points.
3. The method according to claim 1, wherein the step of intercepting the communication data according to the time window to obtain sub-data segments and determining the characteristic parameters of the sub-data segments comprises:
intercepting communication data according to the time window to obtain sub data segments;
performing Fourier transform on the sub-data segments to obtain a superposition function consisting of trigonometric functions; the number of terms of the superposition function is a preset value;
sequentially acquiring trigonometric function characteristics of each item in the superposition function, and generating a characteristic matrix according to a preset arrangement sequence;
and reading the time window of the sub data segment, generating a time sequence, and inserting the characteristic matrix to obtain the characteristic parameters of the sub data segment.
4. The method according to claim 1, wherein the determining K central points according to the time characteristic and classifying the communication data according to the central points to obtain K point families comprises:
receiving K time periods input by a user, matching the time periods with the time sequences in each piece of communication data according to the classification time periods, and randomly selecting K central points; one time period corresponds to one central point;
sequentially reading n-dimensional features of the communication data, and inputting a preset distance formula of the n-dimensional features containing the central point to obtain a distance;
selecting a central point corresponding to the minimum distance, and classifying the communication data and the central point into one class;
the distance formula is:
in the formula (I), the compound is shown in the specification,
the distance between the ith point and the central point; the n is the dimension of the n-dimensional feature vector;
the nth dimension characteristic of the ith point;
is the central point of the image,
the nth dimension feature of the center point.
5. The method of claim 4, wherein the iterative formula is:
in the formula (I), the compound is shown in the specification,
is the center point of the kth point family;
the number of points in the kth point family;
a set of kth point families;
is the ith point in the kth family of points.
6. The method for parsing protocol layer data for intercepting wireless communication according to claim 5, wherein when a cutoff signal is not obtained within a preset time range, the step of classifying communication data according to the initial signal and determining whether a problem exists in a data downlink process according to a classification result comprises:
when the cutoff signal is not acquired within a preset time range, generating a cutoff instruction;
determining a time window according to the acquisition time of the initial signal and the generation time of the cut-off instruction;
intercepting the communication data according to the time window to obtain sub data segments and determining characteristic parameters of the sub data segments to obtain n-dimensional characteristics of the communication data;
inputting the n-dimensional features into the distance formula, and determining a corresponding central point of the communication data;
inquiring the time sequence of the central point, and judging the abnormal probability of the time window according to the time sequence;
and when the abnormal probability reaches a preset abnormal condition, judging that a problem exists in the data downlink process.
7. A protocol layer data parsing system for intercepting wireless communications, the system comprising:
the time window determining module is used for acquiring communication data containing an initial signal and a cut-off signal in real time and determining a time window according to the acquisition time of the initial signal and the cut-off signal;
the characteristic parameter determining module is used for intercepting communication data according to the time window to obtain a subdata segment and determining the characteristic parameter of the subdata segment; the characteristic parameters comprise time characteristics and function characteristics of a superposition function obtained after Fourier transform is carried out on the communication data;
the data clustering module is used for counting the characteristic parameters to obtain n-dimensional characteristics of the communication data and clustering the communication data according to the n-dimensional characteristics;
the problem judging module is used for classifying the communication data according to the initial signal when a cut-off signal is not obtained within a preset time range, and judging whether a problem exists in the data downlink process according to a classification result;
the step of counting the characteristic parameters to obtain n-dimensional characteristics of the communication data, and the step of clustering each communication data according to the n-dimensional characteristics comprises the following steps:
reading and connecting the feature matrix of each sub-data segment, and extracting n-dimensional features from the feature matrix according to a preset rule; wherein the n-dimensional feature contains a temporal feature determined by a time series;
determining K central points according to the time characteristics, and classifying communication data according to the central points to obtain K point families;
and updating the central points in each point family according to a preset iteration formula until the iteration difference value between the central points of two adjacent times is smaller than a preset threshold value.
8. The protocol layer data parsing system for listening to wireless communications of claim 7 wherein said time window determining module comprises:
the signal receiving unit is used for reading communication data in real time when an initial signal is received according to a preset trigger until a cut-off signal is received by the preset trigger; wherein the trigger records the receiving time in real time;
an interval calculation unit for determining a time interval according to a reception time of the cutoff signal and a reception time of the initial signal;
the sampling point determining unit is used for determining sampling points according to the time intervals and correcting the sampling points according to the data quantity at the sampling points;
and the execution unit is used for determining a time window according to the corrected sampling point.
9. The system of claim 7, wherein the feature parameter determination module comprises:
the data intercepting unit is used for intercepting the communication data according to the time window to obtain the subdata segments;
the data transformation unit is used for carrying out Fourier transformation on the sub data segments to obtain a superposition function consisting of trigonometric functions; the number of terms of the superposition function is a preset value;
the characteristic matrix generating unit is used for sequentially acquiring the trigonometric function characteristics of all items in the superposition function and generating a characteristic matrix according to a preset arrangement sequence;
and the time sequence filling unit is used for reading the time window of the sub data segment, generating a time sequence and inserting the characteristic matrix to obtain the characteristic parameters of the sub data segment.
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