Authentication Method, Apparatus and Storage Medium

Abstract

An embodiment of the present application provides an authentication method, device, and storage medium. The method includes: measuring the result of multiplying a first frequency-domain response vector by a second reference signal vector and the result of multiplying a second frequency-domain response vector by a first reference signal vector to obtain a first measurement result; determining whether the first measurement result exceeds a threshold and completing the authentication. The authentication method, device, and storage medium provided by the embodiments of the present application cross-multiply the frequency-domain responses of two specific signals within a frame collected in real time with the reference signals in the fingerprint database. The two products contain the same ideal signal part and approximately the same wireless channel part. Through similarity measurement, radio frequency fingerprint authentication and recognition can be efficiently achieved, the influence of wireless multipath and channel noise can be reduced, the amount of radio frequency fingerprint features obtained can be increased, and the robustness of radio frequency fingerprint authentication can be improved.

Description

Technical Field

[0001] The present invention relates to the field of communication technologies, and in particular, to an authentication method, apparatus, and storage medium. Background Art

[0002] Radio Frequency Fingerprint (RFF) stems from the differences in transmitter circuit designs and the manufacturing tolerances of hardware circuits during the production process. There are subtle differences in device parameters even for different production batches or even within the same production batch, and it has uniqueness and is difficult to clone. This characteristic of radio frequency fingerprint can be used to identify wireless transmitters and also to authenticate the identity of transmitters to protect communication security. However, since wireless transmission signals usually reach the receiver through wireless multipath channels, the transmitted signal has a convolutional relationship with the multipath effect, and the radio frequency fingerprint also has a convolutional relationship with the transmitted signal to a certain extent. Removing the multipath channel will inevitably damage the radio frequency fingerprint. Therefore, the multipath effect greatly limits the accurate extraction of radio frequency fingerprints.

[0003] Existing technologies have proposed methods of dividing the power spectra of different preambles and subtracting in the cepstrum domain. By dividing the power spectrum of the long pilot code by the power spectrum of the short pilot code and subtracting the cepstrum of the power spectrum of the long pilot code from the cepstrum of the power spectrum of the short pilot code, the influence of the multipath channel is removed. However, the method has fewer remaining radio frequency fingerprint feature quantities and is greatly affected by channel noise. Using this method will reduce the robustness of radio frequency fingerprint authentication. Summary of the Invention

[0004] The present invention provides an authentication method, apparatus, and storage medium to solve the defect of low robustness in existing radio frequency fingerprint authentication.

[0005] In a first aspect, an embodiment of the present application provides an authentication method, including:

[0006] Measuring the result of multiplying the first frequency-domain response vector by the second reference signal vector and the result of multiplying the second frequency-domain response vector by the first reference signal vector to obtain a first measurement result;

[0007] Determining whether the first measurement result exceeds a threshold and completing authentication;

[0008] Wherein, the first frequency-domain response vector is the frequency-domain response vector corresponding to the first signal, the second frequency-domain response vector is the frequency-domain response vector corresponding to the second signal, the first signal and the second signal are obtained based on two different signals in the first device signal, the first device signal is the signal received from the first device, the first reference signal vector is the reference signal vector of the first frequency-domain response vector, and the second reference signal vector is the reference signal vector of the second frequency-domain response vector.

[0009] In some embodiments, the method further includes:

[0010] Obtaining a first device number sent by a first device and a first device signal sent by the first device;

[0011] Based on the first device signal, obtaining a first frequency-domain response vector of the first device and a second frequency-domain response vector of the first device.

[0012] In some embodiments, obtaining the first frequency-domain response of the first device and the second frequency-domain response of the first device based on the first device signal includes:

[0013] Based on the first device signal, obtaining a first signal and a second signal;

[0014] Performing Fourier transforms on the first signal and the second signal respectively to obtain the first frequency-domain response vector and the second frequency-domain response vector.

[0015] In some embodiments, the method further includes:

[0016] Obtaining a first reference signal vector corresponding to the first device number from a fingerprint database;

[0017] Obtaining a second reference signal vector corresponding to the first device number from the fingerprint database.

[0018] In some embodiments, the first reference signal vector includes one or more of the following vectors:

[0019] The first frequency-domain response vector of the signal corresponding to the first device number; or,

[0020] The average vector of the multiple frequency-domain response vectors of the signal corresponding to the first device number;

[0021] The second reference signal vector includes one or more of the following vectors:

[0022] The first frequency-domain response vector of the signal corresponding to the first device number; or,

[0023] The average vector of the multiple frequency-domain response vectors of the signal corresponding to the first device number.

[0024] In some embodiments, determining whether the first metric result exceeds a threshold and completing authentication includes:

[0025] Determining whether the first metric result exceeds the threshold;

[0026] If the first metric result exceeds the threshold, the authentication is passed, and it is confirmed that the first device signal is sent by the first device registered in the fingerprint database;

[0027] If the first measurement result does not exceed the threshold, the authentication fails, and it is confirmed that the first device signal is sent by a device outside the library.

[0028] In some embodiments, the method of measurement includes one or more of the following methods:

[0029] Correlation coefficient measurement;

[0030] Vector inner product measurement;

[0031] Euclidean distance measurement;

[0032] Mahalanobis distance measurement; or,

[0033] Similarity measurement.

[0034] In a second aspect, an embodiment of the present application provides an electronic device, including a memory, a transceiver, and a processor;

[0035] The memory is used to store a computer program; the transceiver is used to transmit and receive data under the control of the processor; the processor is used to read the computer program in the memory and perform the following operations:

[0036] Measure the result of multiplying the first frequency-domain response vector by the second reference signal vector and the result of multiplying the second frequency-domain response vector by the first reference signal vector to obtain a first measurement result;

[0037] Determine whether the first measurement result exceeds the threshold and complete the authentication;

[0038] Wherein, the first frequency-domain response vector is the frequency-domain response vector corresponding to the first signal, the second frequency-domain response vector is the frequency-domain response vector corresponding to the second signal, the first signal and the second signal are obtained based on two different signals in the first device signal, the first device signal is the signal sent by the received first device, the first reference signal vector is the reference signal vector of the first frequency-domain response vector, and the second reference signal vector is the reference signal vector of the second frequency-domain response vector.

[0039] In some embodiments, the processor is further used to read the computer program in the memory and perform the following operations:

[0040] Obtain the first device number sent by the first device and the first device signal sent by the first device;

[0041] Based on the first device signal, obtain the first frequency-domain response vector of the first device and the second frequency-domain response vector of the first device.

[0042] In some embodiments, obtaining the first frequency-domain response vector of the first device and the second frequency-domain response vector of the first device based on the first device signal includes:

[0043] Obtain a first signal and a second signal based on the first device signal;

[0044] Perform Fourier transforms on the first signal and the second signal respectively to obtain the first frequency-domain response vector and the second frequency-domain response vector.

[0045] In some embodiments, the processor is further configured to read a computer program in the memory and perform the following operations:

[0046] Obtain a first reference signal vector corresponding to the first device number from the fingerprint database;

[0047] Obtain a second reference signal vector corresponding to the first device number from the fingerprint database.

[0048] In some embodiments, the first reference signal vector includes one or more of the following vectors:

[0049] The first frequency-domain response vector of the signal corresponding to the first device number; or,

[0050] The average vector of the multiple frequency-domain response vectors of the signal corresponding to the first device number;

[0051] The second reference signal vector includes one or more of the following vectors:

[0052] The first frequency-domain response vector of the signal corresponding to the first device number; or,

[0053] The average vector of the multiple frequency-domain response vectors of the signal corresponding to the first device number.

[0054] In some embodiments, determining whether the first metric result exceeds a threshold and completing authentication includes:

[0055] Determine whether the first metric result exceeds the threshold;

[0056] If the first metric result exceeds the threshold, the authentication passes, and it is confirmed that the first device signal is sent by the first device registered in the fingerprint database;

[0057] If the first metric result does not exceed the threshold, the authentication fails, and it is confirmed that the first device signal is sent by a device outside the database.

[0058] In some embodiments, the method of the metric includes one or more of the following methods:

[0059] Correlation coefficient metric;

[0060] Vector inner product metric;

[0061] Euclidean distance metric;

[0062] Mahalanobis distance metric; or,

[0063] similarity metric.

[0064] In a third aspect, an embodiment of the present application further provides an authentication device, including:

[0065] A first operation module: configured to measure the result of multiplying the first frequency-domain response vector by the second reference signal vector and the result of multiplying the second frequency-domain response vector by the first reference signal vector, to obtain a first measurement result;

[0066] A first measurement module: configured to determine whether the first measurement result exceeds a threshold and complete authentication;

[0067] Wherein, the first frequency-domain response vector is the frequency-domain response vector corresponding to the first signal, the second frequency-domain response vector is the frequency-domain response vector corresponding to the second signal, the first signal and the second signal are obtained based on two different segments of signals in the first device signal, the first device signal is the signal received from the first device, the first reference signal vector is the reference signal vector of the first frequency-domain response vector, and the second reference signal vector is the reference signal vector of the second frequency-domain response vector.

[0068] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and the computer program is used to cause a computer to execute the authentication method described in the first aspect above.

[0069] The authentication method, device, and storage medium provided by the embodiments of the present application cross-multiply the frequency-domain responses of two specific signals within one frame collected in real time with the reference signals in the fingerprint database. The two products contain the same ideal signal part and approximately the same wireless channel part. Through similarity measurement, radio frequency fingerprint authentication and identification can be efficiently achieved, the influence of wireless multipath and channel noise can be reduced, the amount of radio frequency fingerprint features obtained can be increased, and the robustness of radio frequency fingerprint authentication can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0071] Figure 1 is one of the schematic flowcharts of the authentication method provided by the embodiments of the present application;

[0072] Figure 2It is the second flowchart diagram of the authentication method provided by the embodiments of the present application

[0073] Figure 3 It is one of the cross - product result diagrams provided by the embodiments of the present application;

[0074] Figure 4 It is the second cross - product result diagram provided by the embodiments of the present application;

[0075] Figure 5 It is the third cross - product result diagram provided by the embodiments of the present application;

[0076] Figure 6 It is the fourth cross - product result diagram provided by the embodiments of the present application;

[0077] Figure 7 It is the structural schematic diagram of an electronic device provided by the embodiments of the present application;

[0078] Figure 8 It is the structural schematic diagram of an authentication device provided by the embodiments of the present application. Detailed implementation manners

[0079] RF fingerprints have uniqueness and are difficult to clone. This property of RF fingerprints can be used not only to identify wireless transmitters but also to authenticate the identity of transmitters to protect communication security. RF fingerprints are minute signal distortions parasitic on transmitted signals, and their generation mechanism is very complex and difficult to accurately model and characterize through a mathematical model. Therefore, it is also difficult to find a theoretically optimal RF fingerprint extraction method.

[0080] Existing technologies have proposed methods of dividing different preamble power spectra and subtracting in the cepstrum domain. By dividing the long - code power spectrum by the short - code power spectrum and subtracting the cepstrum of the long - code power spectrum from the cepstrum of the short - code power spectrum, the influence of the multipath channel is removed. However, the remaining RF fingerprint feature quantities of this method are few. When the number of devices to be identified is large, the recognition performance drops sharply. And this method is very sensitive to channel noise. In practical applications, it is usually necessary to stack hundreds or even thousands of frames of signals to improve the signal - to - noise ratio and then obtain relatively stable RF fingerprints. Therefore, it is necessary to find a channel - robust and efficient RF fingerprint authentication method.

[0081] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0082] Figure 1 is one of the schematic flowcharts of the authentication method provided by the embodiments of the present application. As Figure 1 shown, the embodiments of the present application provide an authentication method, including:

[0083] Step 101: Measure the result of multiplying the first frequency-domain response vector by the second reference signal vector and the result of multiplying the second frequency-domain response vector by the first reference signal vector to obtain a first measurement result.

[0084] Specifically, first obtain the device number i claimed by the current signal frame, and then cross-multiply the current frequency-domain response {Y1 i , Y2 i} with the radio frequency fingerprint reference signal of device i to obtain and Finally, measure and to obtain a measurement result. Wherein, device i is the device with device number i, and the device number i refers to the device number with a value of i. Y1 i is the first frequency-domain response vector, Y2 i is the second frequency-domain response vector, is the first reference signal vector, is the second reference signal vector.

[0085] Wherein, is obtained based on the frequency-domain response {Y1 i , Y2 i} of device i, can be the frequency-domain response obtained under a single high signal-to-noise ratio acquisition, or the average value of the frequency-domain responses obtained under multiple acquisitions. Wherein, the average value is the average vector.

[0086] In the embodiments of the present application, the method for measuring and can include similarity measurement, correlation coefficient measurement, etc.

[0087] Step 102: Determine whether the first measurement result exceeds a threshold and complete the authentication.

[0088] Specifically, if and the similarity is higher than the threshold value, it is determined that the current signal is sent by device i, and the radio frequency fingerprint authentication passes. Otherwise, the radio frequency fingerprint authentication fails and enters the identification stage. In the identification stage, further cross-multiply the current frequency-domain response {Y1 i , Y2 i} with the radio frequency fingerprint reference signals of other devices j in the library in sequence to obtain and If and If the similarity is the highest and higher than the threshold value, it is determined that the current signal is sent by the registered device j in the library, and the radio frequency fingerprint recognition is successful; otherwise, it is determined that the device is sent by an unregistered device outside the library. Herein, the threshold value is the threshold.

[0089] The radio frequency fingerprint authentication method with channel robustness provided in this embodiment realizes radio frequency fingerprint authentication and recognition efficiently through cross - multiplying the frequency - domain response collected in real - time with the reference signal in the fingerprint library. The two products contain the same ideal signal part and approximately the same wireless channel part. Through similarity measurement, it can reduce the influence of wireless multipath and channel noise, increase the amount of radio frequency fingerprint features obtained, and improve the robustness of radio frequency fingerprint authentication.

[0090] In some embodiments, the method further includes:

[0091] Obtaining a first device number sent by a first device and a first device signal sent by the first device;

[0092] Based on the first device signal, obtaining a first frequency - domain response vector of the first device and a second frequency - domain response vector of the first device.

[0093] Specifically, two different time - domain signals {y1 i , y2 i} are selected from a frame of time - domain signal of device i received at the receiving end, where {y1 i , y2 i} are the time - domain signals received at the receiving end after two different time - domain signals {s1 i , s2 i} sent by the sending device i are transmitted through the channel. Fourier transform is performed on {y1 i , y2 i} to obtain the frequency - domain responses {Y1 i , Y2 i}. Herein, i is the first device number sent by the first device, and {y1 i , y2 i} is the first device signal sent by the first device received.

[0094] The radio frequency fingerprint authentication method with channel robustness provided in this embodiment can reduce the influence of wireless multipath and channel noise, increase the amount of radio frequency fingerprint features obtained, and improve the robustness of radio frequency fingerprint authentication by cross - multiplying the frequency - domain responses of two specific signals within a frame collected in real - time with the reference signal in the fingerprint library.

[0095] In some embodiments, obtaining a first frequency - domain response vector of the first device and a second frequency - domain response vector of the first device based on the first device signal includes:

[0096] Obtain a first signal and a second signal based on the first device signal;

[0097] Perform Fourier transforms on the first signal and the second signal respectively to obtain the first frequency-domain response vector and the second frequency-domain response vector.

[0098] Specifically, select two different time-domain signals {y1 i , y2 i} from one frame of time-domain signal of device i received at the receiving end, where {y1 i , y2 i} are two different time-domain signals {s1 i , s2 i} transmitted by device i after passing through the channel and received at the receiving end. Perform Fourier transform on {y1 i , y2 i} to obtain the frequency-domain responses {Y1 i , Y2 i}. Among them, y1 i is the first signal, y2 i is the second signal, and one frame of time-domain signal of device i is the first device signal.

[0099] Among them, {s1 i , s2 i} are two different time-domain signals of the ideal signals {x1 i , x2 i} transmitted by device i. Among them, the {x1 i , x2 i} and {x1 j , x2 j} selected by different transmitting devices i and j can be the same. For example, select a short preamble as x1 i and x1 j , select a long preamble as x2 i and x2 j , then {x1 i , x2 i} is the same as {x1 j , x2 j}. The {x1 i , x2 i} and {x1 j , x2 j} selected by different transmitting devices i and j can also be different. For example, both select a long preamble as x1 i and x1 j and x1 i is the same as x1 j , select the MAC address segment as x2i and x2 j and x2 i with x2 j is different, then {x1 i , x2 i} is different from {x1 j , x2 j}.

[0100] This embodiment provides a channel - robust RF fingerprint authentication method. By cross - multiplying the frequency - domain responses of two specific signals within a frame collected in real - time with the reference signals in the fingerprint database, it can reduce the influence of wireless multipath and channel noise, increase the amount of RF fingerprint features obtained, and improve the robustness of RF fingerprint authentication.

[0101] In some embodiments, the method further includes:

[0102] Obtaining a first reference signal vector corresponding to the first device number from the fingerprint database;

[0103] Obtaining a second reference signal vector corresponding to the first device number from the fingerprint database.

[0104] Specifically, in the training stage, store as the RF fingerprint reference signal REF of device i i in the fingerprint database, which is based on the frequency - domain response {Y1 i , Y2 i} of device i. In the authentication stage, obtain from the fingerprint database according to the device number i

[0105] This embodiment provides a channel - robust RF fingerprint authentication method. By cross - multiplying the RF reference signal stored in the training stage with the frequency - domain response collected in real - time, the two products contain the same ideal signal part and approximately the same wireless channel part, which can reduce the influence of wireless multipath and channel noise, increase the amount of RF fingerprint features obtained, and improve the robustness of RF fingerprint authentication.

[0106] In some embodiments, the first reference signal vector includes one or more of the following vectors:

[0107] The first - order frequency - domain response vector of the signal corresponding to the first device number; or,

[0108] The average vector of the multi - order frequency - domain response vectors of the signal corresponding to the first device number;

[0109] The second reference signal vector includes one or more of the following vectors:

[0110] The primary frequency domain response vector of the signal corresponding to the first device number; or,

[0111] The average vector of the multiple frequency domain response vectors of the signal corresponding to the first device number.

[0112] Specifically, It can be the frequency domain response obtained under a single high signal-to-noise ratio acquisition, or it can be the average value of the frequency domain responses obtained under multiple acquisitions.

[0113] For example, under the training acquisition condition of 30 dB signal-to-noise ratio, acquiring once, we get

[0114] For another example, under the training acquisition condition of 20 dB signal-to-noise ratio, acquiring 100 times and calculating the average value of the 100 frequency domain responses to get

[0115] This embodiment provides a channel-robust RF fingerprint authentication method. By improving the signal quality of the reference signal, it can reduce the influence of wireless multipath and channel noise, increase the obtained RF fingerprint feature quantity, and improve the robustness of RF fingerprint authentication.

[0116] In some embodiments, determining whether the first metric result exceeds a threshold and completing the authentication includes:

[0117] Determining whether the first metric result exceeds the threshold;

[0118] If the first metric result exceeds the threshold, the authentication passes, and it is confirmed that the first device signal is sent by the first device registered in the fingerprint database;

[0119] If the first metric result does not exceed the threshold, the authentication fails, and it is confirmed that the first device signal is sent by a device outside the database.

[0120] Specifically, if and The similarity is higher than the threshold value, then it is determined that the current signal is sent by device i, and the RF fingerprint authentication passes; otherwise, the RF fingerprint authentication fails and enters the identification stage. In the identification stage, further cross-multiply the current frequency domain response {Y1 i , Y2 i} with the RF fingerprint reference signals of other devices j in the database in turn to obtain and If and The similarity is the highest and higher than the threshold value, then it is determined that the current signal is sent by the registered device j in the database, and the RF fingerprint identification is successful; otherwise, it is determined that the device is sent by an unregistered device outside the database.

[0121] This embodiment provides a radio frequency fingerprint authentication method with channel robustness. By measuring the similarity of two products that contain the same ideal signal part and approximately the same wireless channel part and setting a threshold value, it is convenient to view the robustness of the authentication result.

[0122] In some embodiments, the measurement method includes one or more of the following methods:

[0123] Correlation coefficient measurement;

[0124] Vector inner product measurement;

[0125] Euclidean distance measurement;

[0126] Mahalanobis distance measurement; or,

[0127] Similarity measurement.

[0128] Specifically, in this embodiment, for and the method of using similarity measurement is used for radio frequency fingerprint authentication. However, various distance and similarity measurement methods such as correlation coefficient, vector inner product, Euclidean distance, and Mahalanobis distance can also be used.

[0129] For example, the correlation coefficient can be used to measure and ..

[0130] For another example, the vector inner product can be used to measure and ..

[0131] For another example, the Euclidean distance can be used to measure and ..

[0132] For another example, the Mahalanobis distance can be used to measure and ..

[0133] This embodiment provides a radio frequency fingerprint authentication method with channel robustness. By cross - multiplying the real - time collected frequency - domain response with the reference signal in the fingerprint database, the two products contain the same ideal signal part and approximately the same wireless channel part. Through similarity measurement, radio frequency fingerprint authentication and identification can be efficiently realized, the influence of wireless multipath and channel noise can be reduced, the amount of radio frequency fingerprint features obtained can be increased, and the robustness of radio frequency fingerprint authentication can be improved.

[0134] The following specific examples are used to further illustrate the method in the above - mentioned embodiment.

[0135] Figure 2 is the second schematic diagram of the process of the authentication method provided by the embodiment of the present application. AsFigure 2 As shown in the figure, the embodiments of the present application include the following steps:

[0136] (1) Select two different time-domain signals {y1 i , y2 i} from a frame of time-domain signal of device i received by the receiving end, where {y1 i , y2 i} are two different time-domain signals {s1 i , s2 i} sent by the sending device i after being transmitted through the channel and received by the receiving end.

[0137] In this embodiment, an IEEE 802.11n device is selected for scheme verification, and the sampling rate is 20 Msps. {s1 i , s2 i} are two different time-domain signals of the ideal signals {x1 i , x2 i} sent by the sending device i respectively. Among them, x1 i is the short preamble part, and x2 i is the long preamble part. That is, different devices all select the same short preamble part x1 and long preamble part x2 for radio frequency fingerprint authentication, so {x1 i , x2 i} is the same as {x1, x2}. The two different time-domain signals {s1 i , s2 i} contain the radio frequency fingerprint time-domain information rff i () of device i and can be expressed as:

[0138] s1 i = rff i (x1)

[0139] s2 i = rff i (x2)

[0140] {y1 i , y2 i} are the signals received by the receiving end after the two different time-domain signals {s1 i , s2 i} sent by the sending device i are respectively transmitted through the wireless channels {h1, h2}, and can be expressed as:

[0141] y1 i = s1 i * h1 + n1

[0142] y2 i = s2 i * h2 + n2

[0143] Wherein, * represents a convolution operation, {h1, h2} represents the corresponding time-domain channel response, and {n1, n2} represents the corresponding time-domain channel noise.

[0144] (2) Perform Fourier transform on {y1 i , y2 i} to obtain the frequency-domain responses {Y1 i , Y2 i}. In this embodiment, the frequency-domain responses {Y1 i , T2 i} are expressed as:

[0145] Y1 i = FFT(y1 i ) = S1 i ·H1 + N1

[0146] Y2 i = FFT(y2 i ) = S2 i ·H2 + N2

[0147] Wherein, FFT() represents the Fourier transform, {S1 i , S2 i} is the frequency-domain representation of the signal segments {s1 i , s2 i}, {H1, H2} are the corresponding frequency-domain channel responses, and {N1, N2} are the corresponding frequency-domain channel noises.

[0148] Furthermore, {S1 i , S2 i} can also be expressed as:

[0149] S1 i = RFF i (X1)

[0150] S2 i = RFF i (X2)

[0151] Wherein, RFF i () is the frequency-domain response of the radio frequency fingerprint of device i, and {X1, X2} is the frequency-domain representation of the ideal preamble signals {x1, x2}.

[0152] (3) In the training stage, store the frequency-domain responses as the radio frequency fingerprint reference signal REF i of device i.

[0153] In this embodiment, under the training acquisition condition of about 20 dB signal-to-noise ratio, N is collected 100 times, and the average value of the 100 frequency-domain responses is calculated as the reference signal, that is

[0154]

[0155] Wherein, is the frequency-domain response calculated during the k-th acquisition, {H1 k , H2 k} is the corresponding frequency-domain channel response during the k-th acquisition, and {N1 k , N2 k} is the corresponding frequency-domain channel noise during the k-th acquisition. is the average value of the frequency-domain channel responses corresponding to 100 acquisitions, is the average value of the frequency-domain channel noises corresponding to 100 acquisitions.

[0156] (4) Authentication stage: First, obtain the device number i claimed by the current signal frame, and then cross-multiply the current frequency-domain response {Y1 i , Y2 i} with the radio frequency fingerprint reference signal of device i to obtain and

[0157] In this embodiment, the device number i claimed by the current signal frame is obtained according to the MAC address information in the frame, and then the current frequency-domain response {Y1 i , Y2 i} is cross-multiplied with the radio frequency fingerprint reference signal of device i to obtain two products and

[0158]

[0159]

[0160] When the signal-to-noise ratio is relatively high, the noise can be further ignored, and the above formula can be further simplified to:

[0161]

[0162]

[0163] Furthermore, considering that the wireless channel is almost unchanged in a short period of time, therefore, H1 and H2 are approximated, and are approximated. From this, it can be known that the and of a legitimate device are approximated.

[0164] Figure 3 is one of the cross-product result diagrams provided by the embodiments of the present application, as shown in Figure 3As shown in the figure, the embodiments of the present application provide two cross-products of the single-frame signal spectrum response of the legitimate device 1 and the spectrum response reference signal of the in-library device 1. When the signal-to-noise ratio of the received signal is about 20 dB, it can be seen that the two product vectors of the legitimate device 1 are relatively similar.

[0165] Figure 4 is the second cross-product result diagram provided by the embodiments of the present application, as Figure 4 shown, the embodiments of the present application provide two cross-products of the single-frame signal spectrum response of the illegal device 2 and the spectrum response reference signal of the in-library device 1. There are obvious differences between the two product vectors of the illegal device 2.

[0166] In order to further improve the robustness of the radio frequency fingerprint recognition and authentication algorithm, the current frequency-domain responses {Y1i, Y2i} can also be multi-frame superimposed and then the cross-product is further calculated.

[0167] Figure 5 is the third cross-product result diagram provided by the embodiments of the present application, as Figure 5 shown, the embodiments of the present application provide two cross-products of the average spectrum response of 10 frames of signals of the legitimate device 1 and the spectrum response reference signal of the in-library device 1. It can be seen that the product vectors obtained after superposition are highly similar.

[0168] Figure 6 is the fourth cross-product result diagram provided by the embodiments of the present application, as Figure 6 shown, the embodiments of the present application provide two cross-products of the average spectrum response of 10 frames of signals of the illegal device 2 and the spectrum response reference signal of the in-library device 1. It can be seen that the product vectors obtained after superposition are quite different.

[0169] (5) If and the similarity is higher than the threshold value, it is determined that the current signal is sent by device i, and the radio frequency fingerprint authentication passes; otherwise, the radio frequency fingerprint authentication fails and enters the recognition stage.

[0170] In this embodiment, the correlation coefficient is used to calculate and the similarity. In the scenario where the received signal-to-noise ratio is about 20 dB, the specific authentication experimental results are shown in Table 1.

[0171] The similarity calculated for each single frame during 1000 acquisitions of the legitimate device 1 was statistically analyzed. The mean value was 0.9618 and the standard deviation was 0.0382. If the authentication threshold is set to 0.9, the authentication pass rate of the legitimate device 1 is 96.9%. If the authentication threshold is set to 0.95, the authentication pass rate of the legitimate device 1 is 69.9%. The similarity calculated by averaging consecutive 10 frames during 1000 acquisitions of the legitimate device 1 was statistically analyzed. The mean value was 0.9912 and the standard deviation was 0.0047. If the authentication threshold is set to 0.95, the authentication pass rate of the legitimate device 1 is 100%.

[0172] The spoofing attack on device 1 was carried out using device 2. The similarity calculated for each single frame during 1000 acquisitions of the illegal device 2 was statistically analyzed. The mean value was 0.8671 and the standard deviation was 0.0609. If the authentication threshold is set to 0.9, the successful rejection rate of the illegal device 2 is 67.0%. If the authentication threshold is set to 0.95, the successful rejection rate of the illegal device 2 is 97.3%. The similarity calculated by averaging consecutive 10 frames during 1000 acquisitions of the illegal device 2 was statistically analyzed. The mean value was 0.8162 and the standard deviation was 0.0306. If the authentication threshold is set to 0.95, the successful rejection rate of the illegal device 2 is 100%.

[0173] Table 1 Authentication experiment results

[0174]

[0175]

[0176] (6) In the identification stage, further, the current frequency-domain response {Y1 i , Y2 i} is successively cross-multiplied with the RF fingerprint reference signals of other devices j in the library to obtain and

[0177] In this embodiment, when the illegal device 2 fails the authentication during the spoofing attack on the legitimate device 1, it enters the identification stage for further identification. At this time, the currently acquired spectral response of the illegal device 2 is successively cross-multiplied with the RF fingerprint reference signals of the remaining N - 1 devices in the library except device 1 j = 2, 3,... N, to obtain N - 1 pairs of cross-products and

[0178] (7) If and have the highest similarity and are higher than the threshold value, it is determined that the current signal is sent by the registered device j in the library, and the RF fingerprint identification is successful; otherwise, it is determined that the device is sent by an unregistered device outside the library.

[0179] In this embodiment, the spectral response {Y1 i , Y2 i} of the spoofing signal has the highest similarity with the two cross-products calculated from the radio frequency fingerprint reference signal of the in-library device 2 and exceeds the threshold value of 0.9. Thus, it is determined that the spoofing signal is sent by the in-library device 2, and the radio frequency fingerprint recognition is successful.

[0180] Figure 7 FIG. is a schematic structural diagram of an electronic device provided by an embodiment of the present application. As Figure 7 shown, the electronic device includes a memory 720, a transceiver 700, and a processor 710, where:

[0181] The memory 720 is used to store a computer program; the transceiver 700 is used to receive and send data under the control of the processor 710; the processor 710 is used to read the computer program in the memory 720 and perform the following operations:

[0182] Measure the result of multiplying the first frequency-domain response vector by the second reference signal vector and the result of multiplying the second frequency-domain response vector by the first reference signal vector to obtain a first measurement result;

[0183] Determine whether the first measurement result exceeds the threshold and complete the authentication;

[0184] Wherein, the first frequency-domain response vector is the frequency-domain response vector corresponding to the first signal, the second frequency-domain response vector is the frequency-domain response vector corresponding to the second signal, the first signal and the second signal are obtained based on two different signals in the first device signal, the first device signal is the signal sent by the received first device, the first reference signal vector is the reference signal vector of the first frequency-domain response vector, and the second reference signal vector is the reference signal vector of the second frequency-domain response vector.

[0185] Specifically, the transceiver 700 is used to receive and send data under the control of the processor 710.

[0186] Wherein, in Figure 7Among them, the bus architecture may include any number of interconnected buses and bridges, specifically various circuits of one or more processors represented by processor 710 and memory represented by memory 720 are linked together. The bus architecture may also link together various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art, and thus will not be further described herein. The bus interface provides an interface. The transceiver 700 may be a plurality of components, that is, including a transmitter and a receiver, and provides a unit for communicating with various other devices on a transmission medium, and these transmission media include transmission media such as wireless channels, wired channels, and optical cables. For different user devices, the user interface 730 may also be an interface capable of externally connecting and internally connecting required devices, and the connected devices include but are not limited to a keypad, a display, a speaker, a microphone, a joystick, etc.

[0187] The processor 710 is responsible for managing the bus architecture and general processing, and the memory 720 may store data used by the processor 710 when executing operations.

[0188] In some embodiments, the processor 710 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a complex programmable logic device (CPLD), and the processor may also adopt a multi-core architecture.

[0189] The processor is used to execute any of the methods provided in the embodiments of the present application according to the obtained executable instructions by calling the computer program stored in the memory. The processor and the memory may also be physically separated.

[0190] In some embodiments, the processor is further used to read the computer program in the memory and perform the following operations:

[0191] Obtain a first device number sent by a first device and a first device signal sent by the first device;

[0192] Obtain a first frequency domain response vector of the first device and a second frequency domain response vector of the first device based on the first device signal.

[0193] In some embodiments, obtaining a first frequency domain response vector of the first device and a second frequency domain response vector of the first device based on the first device signal includes:

[0194] Obtain a first signal and a second signal based on the first device signal;

[0195] Perform Fourier transforms on the first signal and the second signal respectively to obtain the first frequency-domain response vector and the second frequency-domain response vector.

[0196] In some embodiments, the processor is further configured to read a computer program in the memory and perform the following operations:

[0197] Obtain a first reference signal vector corresponding to the first device number from the fingerprint database;

[0198] Obtain a second reference signal vector corresponding to the first device number from the fingerprint database.

[0199] In some embodiments, the first reference signal vector includes one or more of the following vectors:

[0200] The first-order frequency-domain response vector of the signal corresponding to the first device number; or,

[0201] The average vector of the multi-order frequency-domain response vectors of the signal corresponding to the first device number;

[0202] The second reference signal vector includes one or more of the following vectors:

[0203] The first-order frequency-domain response vector of the signal corresponding to the first device number; or,

[0204] The average vector of the multi-order frequency-domain response vectors of the signal corresponding to the first device number.

[0205] In some embodiments, determining whether the first metric result exceeds a threshold and completing authentication includes:

[0206] Determine whether the first metric result exceeds the threshold;

[0207] If the first metric result exceeds the threshold, the authentication is passed, and it is confirmed that the first device signal is sent by the first device registered in the fingerprint database;

[0208] If the first metric result does not exceed the threshold, the authentication fails, and it is confirmed that the first device signal is sent by a device outside the database.

[0209] In some embodiments, the method of the metric includes one or more of the following methods:

[0210] Correlation coefficient metric;

[0211] Vector inner product metric;

[0212] Euclidean distance metric;

[0213] Mahalanobis distance metric; or,

[0214] Similarity metric.

[0215] Figure 8 is a schematic structural diagram of an authentication device provided by an embodiment of the present application. As Figure 8 shown, the embodiment of the present application provides an authentication device, including a first operation module 801 and a first measurement module 802, where:

[0216] The first operation module: is used to measure the result of multiplying the first frequency-domain response vector by the second reference signal vector and the result of multiplying the second frequency-domain response vector by the first reference signal vector to obtain a first measurement result;

[0217] The first measurement module: is used to determine whether the first measurement result exceeds a threshold and complete authentication;

[0218] Among them, the first frequency-domain response vector is the frequency-domain response vector corresponding to the first signal, the second frequency-domain response vector is the frequency-domain response vector corresponding to the second signal, the first signal and the second signal are obtained based on two different signals in the first device signal, the first device signal is the signal received from the first device, the first reference signal vector is the reference signal vector of the first frequency-domain response vector, and the second reference signal vector is the reference signal vector of the second frequency-domain response vector.

[0219] In some embodiments, the first operation module and the first measurement module are further used for:

[0220] Obtain the first device number sent by the first device and the first device signal sent by the first device;

[0221] Based on the first device signal, obtain the first frequency-domain response vector of the first device and the second frequency-domain response vector of the first device.

[0222] In some embodiments, obtaining the first frequency-domain response vector of the first device and the second frequency-domain response vector of the first device based on the first device signal includes:

[0223] Obtain the first signal and the second signal based on the first device signal;

[0224] Perform Fourier transform on the first signal and the second signal respectively to obtain the first frequency-domain response vector and the second frequency-domain response vector.

[0225] In some embodiments, the first operation module and the first measurement module are further used for:

[0226] Obtain the first reference signal vector corresponding to the first device number from the fingerprint database;

[0227] Obtain the second reference signal vector corresponding to the first device number from the fingerprint database.

[0228] In some embodiments, the first reference signal

[0229] vector includes one or more of the following vectors:

[0230] the primary frequency-domain response vector of the signal corresponding to the first device number; or,

[0231] the average vector of the multiple frequency-domain response vectors of the signal corresponding to the first device number;

[0232] The second reference signal vector includes one or more of the following vectors:

[0233] the primary frequency-domain response vector of the signal corresponding to the first device number; or,

[0234] the average vector of the multiple frequency-domain response vectors of the signal corresponding to the first device number.

[0235] In some embodiments, determining whether the first metric result exceeds a threshold and completing authentication includes:

[0236] Determining whether the first metric result exceeds the threshold;

[0237] If the first metric result exceeds the threshold, the authentication is passed, and it is confirmed that the first device signal is sent by the first device registered in the fingerprint database;

[0238] If the first metric result does not exceed the threshold, the authentication fails, and it is confirmed that the first device signal is sent by a device outside the database.

[0239] In some embodiments, the method of the metric includes one or more of the following methods:

[0240] Correlation coefficient metric;

[0241] Vector inner product metric;

[0242] Euclidean distance metric;

[0243] Mahalanobis distance metric; or,

[0244] Similarity metric.

[0245] Specifically, the above authentication device provided by the embodiments of the present application can implement all the method steps implemented by the method embodiments with the above execution subject being an electronic device, and can achieve the same technical effects. The same parts and beneficial effects as those in the method embodiments are not specifically described herein again.

[0246] It should be noted that the division of units / modules in the above embodiments of the present application is illustrative, merely a logical function division, and there may be other division methods in actual implementation. In addition, in each embodiment of the present application, each functional unit may be integrated in a processing unit, may exist separately physically for each unit, or two or more units may be integrated in one unit. The above integrated unit may be implemented in the form of hardware or in the form of a software functional unit.

[0247] If the above integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a processor-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs that can store program codes.

[0248] In some embodiments, a computer-readable storage medium is further provided. The computer-readable storage medium stores a computer program, and the computer program is used to cause a computer to execute the authentication method provided in the above method embodiments.

[0249] Specifically, the computer-readable storage medium provided in the embodiments of the present application can implement all the method steps implemented in the above method embodiments, and can achieve the same technical effects. The same parts and beneficial effects as those in the method embodiments will not be specifically described in this embodiment.

[0250] It should be noted that the computer-readable storage medium may be any available medium or data storage device accessible by a processor, including but not limited to magnetic memories (such as floppy disks, hard disks, magnetic tapes, magneto-optical discs (MO), etc.), optical memories (such as CDs, DVDs, BDs, HVDs, etc.), and semiconductor memories (such as ROM, EPROM, EEPROM, non-volatile memories (NAND FLASH), solid-state drives (SSD), etc.).

[0251] It should be further noted that in the embodiments of the present application, terms such as "first" and "second" are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that such terms can be interchanged under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first" and "second" are usually of the same type, and the number of objects is not limited. For example, the first object can be one or more.

[0252] In the embodiments of the present application, the term "and / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects before and after.

[0253] In the embodiments of the present application, the term "plurality" refers to two or more, and other quantifiers are similar.

[0254] "Determining B based on A" in the present application means that the factor A should be considered when determining B. It is not limited to "determining B only based on A", but also includes: "determining B based on A and C", "determining B based on A, C, and E", "determining C based on A and further determining B based on C", etc. In addition, it can also include using A as a condition for determining B. For example, "when A meets the first condition, use the first method to determine B"; for another example, "when A meets the second condition, determine B"; for another example, "when A meets the third condition, determine B based on the first parameter", etc. Of course, it can also be a condition for using A as a factor for determining B. For example, "when A meets the first condition, use the first method to determine C and further determine B based on C", etc.

[0255] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program code.

[0256] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and combinations of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer-executable instructions. These computer-executable instructions can be provided to the processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing device produce a means for implementing the functions specified in the Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0257] These processor-executable instructions can also be stored in a processor-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, such that the instructions stored in the processor-readable memory produce a manufacture including an instruction means that implements the functions specified in the Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0258] These processor-executable instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operational steps are performed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in the Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0259] Obviously, those skilled in the art can make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalent technologies, this application is also intended to include these changes and modifications.

Claims

1. An authentication method, characterized in that, Including: Measuring the result of multiplying a first frequency-domain response vector by a second reference signal vector and the result of multiplying a second frequency-domain response vector by a first reference signal vector to obtain a first measurement result; Judging whether the first measurement result exceeds a threshold and completing authentication; Wherein, the first frequency-domain response vector is the frequency-domain response vector corresponding to a first signal, the second frequency-domain response vector is the frequency-domain response vector corresponding to a second signal, the first signal and the second signal are obtained based on two different signals in a first device signal, the first device signal is the signal received from a first device, the first reference signal vector is the reference signal vector of the first frequency-domain response vector, and the second reference signal vector is the reference signal vector of the second frequency-domain response vector.

2. The authentication method according to claim 1, wherein The method further includes: Obtaining a first device number sent by a first device and a first device signal sent by the first device; Obtaining a first frequency-domain response vector of the first device and a second frequency-domain response vector of the first device based on the first device signal.

3. The authentication method according to claim 2, wherein Obtaining a first frequency-domain response vector of the first device and a second frequency-domain response vector of the first device based on the first device signal includes: Obtaining a first signal and a second signal based on the first device signal; Performing Fourier transform on the first signal and the second signal respectively to obtain the first frequency-domain response vector and the second frequency-domain response vector.

4. The authentication method according to claim 1, wherein The method further includes: Obtaining a first reference signal vector corresponding to the first device number from a fingerprint database; Obtaining a second reference signal vector corresponding to the first device number from a fingerprint database.

5. The authentication method according to claim 4, characterized in that, The first reference signal vector includes one or more of the following vectors: The first-order frequency-domain response vector of the signal corresponding to the first device number; or, The average vector of the multi-order frequency-domain response vectors of the signal corresponding to the first device number; The second reference signal vector includes one or more of the following vectors: The first-order frequency-domain response vector of the signal corresponding to the first device number; or, The average vector of the multi-order frequency-domain response vectors of the signal corresponding to the first device number.

6. The authentication method according to claim 1, characterized in that, Judging whether the first measurement result exceeds a threshold and completing authentication includes: Judging whether the first measurement result exceeds a threshold; If the first measurement result exceeds the threshold, the authentication is passed, and it is confirmed that the first device signal is sent by the first device registered in the fingerprint database; If the first measurement result does not exceed the threshold, the authentication fails, and it is confirmed that the first device signal is sent by a device outside the database.

7. The authentication method according to claim 1, characterized in that, The method of the measurement includes one or more of the following methods: Correlation coefficient measurement; Vector inner product measurement; Euclidean distance measurement; Mahalanobis distance measurement; or, Similarity measurement.

8. An authentication device, characterized in that, Including: A first operation module: configured to measure the result of multiplying a first frequency-domain response vector by a second reference signal vector and the result of multiplying a second frequency-domain response vector by a first reference signal vector to obtain a first measurement result; A first measurement module: configured to judge whether the first measurement result exceeds a threshold and complete authentication; Among them, the first frequency-domain response vector is the frequency-domain response vector corresponding to the first signal, the second frequency-domain response vector is the frequency-domain response vector corresponding to the second signal, the first signal and the second signal are obtained based on two different segments of signals in the first device signal, the first device signal is the signal received from the first device, the first reference signal vector is the reference signal vector of the first frequency-domain response vector, and the second reference signal vector is the reference signal vector of the second frequency-domain response vector.

9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the authentication method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the authentication method according to any one of claims 1 to 7.

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