Signal sampling method and device, electronic equipment and readable storage medium

Abstract

Embodiments of the present application provide a signal sampling method and device, electronic equipment and readable storage medium, the method comprises: obtaining a to-be-detected sampling signal, and quantizing the to-be-detected sampling signal according to a preset quantization model to obtain the sign information of the amplitude value of the to-be-detected sampling signal; generating a target identifier of the to-be-detected sampling signal according to the sign information and a preset generation model, and performing security verification on the target identifier according to a preset verification database to obtain a security verification result of the target identifier; in the case that the security verification result is that the target identifier is safe, performing signal reconstruction according to the target identifier and a preset signal reconstruction model to obtain a reconstructed signal corresponding to the to-be-detected sampling signal. Since the reconstructed signal is obtained through the preset signal reconstruction model in the case that the security verification result is that the target identifier is safe, the security of the reconstructed signal can be improved.

Description

Technical Field

[0001] This invention belongs to the field of communications, and in particular relates to a signal sampling method, apparatus, electronic device, and readable storage medium. Background Technology

[0002] In wireless communication technology, the Internet Protocol (IP) sends signals to the receiver based on the destination address in the signal information. The signal is transmitted in plaintext during transmission. Attackers can intercept the signal through eavesdropping and modify the source IP address or destination IP address in the signal information.

[0003] Single-bit compressed sensing technology can quantize a signal to a single bit, that is, use a single binary bit to represent the symbol information of the sampled signal, and then reconstruct the signal based on the symbol information to obtain a reconstructed signal with the same direction as the original signal.

[0004] In existing technologies, when sampling signals with traceable source IP addresses using single-bit compressed sensing technology, sampling is usually performed directly based on the source IP address of the signal. If the source IP address has been modified, the obtained signal sampling results will have a high security risk. Summary of the Invention

[0005] This invention provides a signal sampling method, apparatus, electronic device, and readable storage medium to solve the problem that if the source IP address of a signal is modified, the obtained signal sampling result has a high security risk.

[0006] To solve the above-mentioned technical problems, the present invention is implemented as follows:

[0007] In a first aspect, the present invention provides a signal sampling method, the method comprising:

[0008] Acquire the sampled signal to be detected, and quantize the sampled signal to be detected according to a preset quantization model to obtain the sign information of the amplitude value of the sampled signal to be detected;

[0009] Based on the symbol information and the preset generation model, a target identifier for the sampled signal to be detected is generated, and the target identifier is subjected to security verification according to the preset verification database to obtain the security verification result of the target identifier.

[0010] If the security verification result indicates that the target identifier is secure, signal reconstruction is performed based on the target identifier and a preset signal reconstruction model to obtain the reconstructed signal corresponding to the sampled signal to be detected.

[0011] Optionally, the step of performing security verification on the target identifier according to a preset verification database and obtaining the security verification result of the target identifier includes:

[0012] The system checks whether any identifier data identical to the target identifier exists in the verification database.

[0013] If the same identifier data as the target identifier exists in the verification database, obtain the security verification result of the target identifier, wherein the security verification result indicates that the target identifier is insecure;

[0014] If no identifier data identical to the target identifier exists in the verification database, the target identifier is encrypted and verified according to the verification database and a preset hash value encryption algorithm to obtain the security verification result of the target identifier.

[0015] Optionally, the step of performing encrypted verification on the target identifier based on the verification database and a preset hash value encryption algorithm to obtain the security verification result of the target identifier includes:

[0016] The target identifier is encrypted using the hash value encryption algorithm to obtain a hash value encrypted string;

[0017] The system detects whether there is any identifier data in the verification database that has a similarity to the hash value encrypted string that meets a preset similarity threshold, and obtains the security verification result of the target identifier.

[0018] Optionally, if there is identifier data in the verification database that has a similarity to the hash value encrypted string that meets a preset similarity threshold, the security verification result is that the target identifier is insecure; if there is no identifier data in the verification database that has a similarity to the hash value encrypted string that meets a preset similarity threshold, the security verification result is that the target identifier is secure.

[0019] Optionally, before performing signal reconstruction based on the target identifier and a preset signal reconstruction model to obtain the reconstructed signal corresponding to the sampled signal to be detected, the method further includes:

[0020] Establish an address mapping between the target representation and the symbol information, and store the symbol information in a preset symbol information database;

[0021] The step of reconstructing the signal based on the target identifier and a preset signal reconstruction model to obtain the reconstructed signal corresponding to the sampled signal to be detected includes:

[0022] Based on the address mapping between the target identifier and the symbol information, the symbol information of the sampled signal to be detected is obtained from the symbol information data;

[0023] The signal is reconstructed according to the preset signal reconstruction model and the symbol information of the sampled signal to be detected, and the reconstructed signal corresponding to the sampled signal to be detected is obtained.

[0024] Optionally, for multiple sampled signals to be detected, the method further includes:

[0025] For any of the aforementioned sampled signals to be detected, the thread weight of the sampled signal to be detected is determined based on the target identifier of the sampled signal to be detected;

[0026] The threads are sorted according to their respective thread weights to determine the thread order.

[0027] The step of reconstructing the signal based on the target identifier and a preset signal reconstruction model to obtain the reconstructed signal corresponding to the sampled signal to be detected includes:

[0028] According to the thread sequence, signal reconstruction is performed based on the target identifier and the preset signal reconstruction model to obtain the reconstructed signals corresponding to each of the multiple sampled signals to be detected.

[0029] Optionally, the sampled signal to be detected is a time-domain sampled signal. Before quantizing the sampled signal to be detected according to a preset quantization model to obtain the sign information of the amplitude value of the sampled signal to be detected, the method further includes:

[0030] The sampled signal to be detected is expanded in the frequency domain to obtain a frequency-domain sparse signal;

[0031] The step of quantizing the sampled signal to be detected according to a preset quantization model to obtain the sign information of the amplitude value of the sampled signal to be detected includes:

[0032] According to the preset random demodulation and quantization model, the frequency domain sparse signal is quantized to obtain the sign information of the amplitude value of the frequency domain sparse signal.

[0033] In a second aspect, the present invention provides a signal sampling device, the device comprising:

[0034] The first acquisition module is used to acquire the sampled signal to be detected, and to quantize the sampled signal to be detected according to a preset quantization model to obtain the sign information of the amplitude value of the sampled signal to be detected.

[0035] The security verification module is used to generate a target identifier of the sampled signal to be detected based on the symbol information and a preset generation model, and to perform security verification on the target identifier based on a preset verification database to obtain the security verification result of the target identifier;

[0036] The signal reconstruction module is used to reconstruct the signal based on the target identifier and a preset signal reconstruction model when the security verification result indicates that the target identifier is secure, and to obtain the reconstructed signal corresponding to the sampled signal to be detected.

[0037] Thirdly, the present invention provides an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-described signal sampling method when executing the program.

[0038] Fourthly, the present invention provides a readable storage medium that, when the instructions in the storage medium are executed by the processor of an electronic device, enables the electronic device to perform the above-described signal sampling method.

[0039] In this embodiment of the invention, the acquired sampled signal to be detected can be quantized into a symbolic representation using a preset quantization model. A target identifier of the sampled signal can be reconstructed using a preset generation model and the symbolic information. Security verification of the target identifier is performed using a preset verification database to verify the security of the sampled signal. If the security verification result indicates that the target identifier is secure, signal reconstruction is performed using a preset signal reconstruction model to obtain the reconstructed signal corresponding to the sampled signal. Since the reconstructed signal is obtained using a preset signal reconstruction model under the condition that the target identifier is secure, the security of the reconstructed signal can be improved. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is one of the flowcharts of a signal sampling method provided in an embodiment of the present invention;

[0042] Figure 2 This is the second step flowchart of a signal sampling method provided in an embodiment of the present invention;

[0043] Figure 3 This is a schematic diagram of a random demodulation and quantization system provided in an embodiment of the present invention;

[0044] Figure 4 This is the third step in the flowchart of a signal sampling method provided in this embodiment of the invention;

[0045] Figure 5This is a flowchart of another signal sampling method provided in an embodiment of the present invention;

[0046] Figure 6 This is a structural diagram of a signal sampling device provided in an embodiment of the present invention;

[0047] Figure 7 This is a structural diagram of an electronic device provided in an embodiment of the present invention;

[0048] Figure 8 This is a schematic diagram of the hardware structure of another electronic device provided in an embodiment of the present invention. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] Figure 1 This is a flowchart of the steps of a signal sampling method provided in an embodiment of the present invention, as follows: Figure 1 As shown, the method may include:

[0051] Step 101: Obtain the sampled signal to be detected, and quantize the sampled signal to be detected according to the preset quantization model to obtain the sign information of the amplitude value of the sampled signal to be detected.

[0052] In this embodiment of the invention, the sampled signal to be detected is a signal with a queryable source IP address. The source IP address may include the IP address of a website or a server; this is merely an example and is not intended to limit the scope of the invention. The preset quantization model can be a computational model that obtains the sign information of the amplitude value of the sampled signal to be detected based on the quantization matrix. For example, see the following formula:

[0053] y∶=sign(Φx)(1)

[0054] Where sign is the sign function, x represents the sampled signal to be detected, Φ represents the quantization matrix, and y is defined as the product of the quantization matrix and the sampled signal to be detected, i.e., Φx, to obtain the sign information.

[0055] In this embodiment of the invention, the acquired sampled signal to be detected can be quantized using a quantization matrix to obtain a quantized signal value. The quantized signal value is a discrete quantity that can represent the amplitude value of the sampled signal to be detected. Further, the sign information of the quantized signal value can be obtained using a sign function, and this sign information can be used as the sign information of the amplitude value of the sampled signal to be detected. The sign information of the amplitude value can include both positive and negative values.

[0056] Optional, such as Figure 2 As shown, the sampled signal to be detected is a time-domain sampled signal. Before step 101, the method further includes:

[0057] Step 104: Expand the sampled signal to be detected in the frequency domain to obtain a frequency-domain sparse signal.

[0058] In this embodiment of the invention, the sampled signal to be detected can be a continuous-time signal in the time domain. A frequency-domain sparse signal is a signal consisting of only K bounded single-frequency points, where K is a positive integer. For example, a frequency-domain sparse signal can be a broadcast signal in communication, a music signal in sound signals, or a sinusoidal signal whose frequency changes slowly over time in radar and geographic fields.

[0059] In this embodiment of the invention, the sampled signal to be detected can be expanded in the frequency domain according to a Fourier series, representing the sampled signal to be detected as a linear combination of multiple frequency components. See the following formula:

[0060]

[0061] Where, ψ n (t) is a Fourier transform basis, a n Let be the Fourier transform coefficient vector, and x(t) be the frequency-domain sparse signal. It should be noted that the maximum frequency of the frequency-domain sparse signal is finite; each individual frequency point is located at an integer frequency, and the number of individual frequency points is much smaller than the maximum frequency of the frequency-domain sparse signal. The fact that each individual frequency point is located at an integer frequency avoids the inability to distinguish individual frequency points at fractional frequencies when the frequency resolution is 1.

[0062] Optionally, step 101 may include:

[0063] According to the preset random demodulation and quantization model, the frequency domain sparse signal is quantized to obtain the sign information of the amplitude value of the frequency domain sparse signal.

[0064] In this embodiment of the invention, the random demodulation and quantization model can be a signal processing model that obtains the symbol information of the amplitude value of a frequency-domain sparse signal through the processes of signal mixing, low-pass filtering, sample-and-hold, and single-bit quantization.

[0065] In embodiments of the present invention, such as Figure 3 As shown, the sign information of the amplitude value of a frequency-domain sparse signal can be obtained through the stochastic demodulation and quantization system corresponding to the stochastic demodulation and quantization model. Specifically, the frequency-domain sparse signal x(t) can be input into the stochastic demodulation and quantization system, and the frequency-domain sparse signal x(t) and the pseudo-random sequence p(t) can be mixed by an analog multiplier, where p(t)∈(-1,1). Further, the mixed signal is input into an analog low-pass filter, which can filter out the high-frequency part of the mixed signal, so that the filtered signal contains only low-frequency components. The unit impulse response of the analog low-pass filter is h(t). Then, the filtered signal is input into a sample-and-hold circuit, which discretizes the filtered signal to obtain a discrete signal, where the amplitude of the discrete signal is determined by the sample-and-hold voltage of the sample-and-hold circuit. By comparing the sample-and-hold voltage of the sample-and-hold circuit with a fixed voltage, the sign information y[m] of the input frequency-domain sparse signal x(t) can be obtained when the fixed voltage is zero.

[0066] In this embodiment of the invention, when the sampled signal to be detected is a time-domain sampled signal, the sampled signal to be detected can be converted into a frequency-domain sparse signal. For the frequency-domain sparse signal, the frequency-domain sparse signal can be quantized according to a preset random demodulation quantization model to obtain the sign information of the amplitude value of the frequency-domain sparse signal corresponding to the sampled signal to be detected.

[0067] Step 102: Generate a target identifier for the sampled signal to be detected based on the symbol information and the preset generation model, and perform security verification on the target identifier based on the preset verification database to obtain the security verification result of the target identifier.

[0068] In this embodiment of the invention, the target identifier is used to characterize the source of the signal to be detected. For example, the target identifier can be the source IP address of the signal to be detected. The preset generation model can be a computational model that calculates the minimum value of the objective function of the target identifier by solving the symbol information corresponding to the target identifier.

[0069] In this embodiment of the invention, a diagonal matrix can be generated based on symbol information, wherein the diagonal elements of the diagonal matrix are symbol information, and the remaining matrix elements are all zero. The target identifier of the sampled signal to be detected can be generated based on the diagonal matrix corresponding to the symbol information and a preset generation model. Specifically, see the following formula:

[0070]

[0071] in, Let Y represent the target identifier obtained, x represent the sampled signal to be detected, Y represent the diagonal matrix corresponding to the symbol information, Φ represent the quantization matrix, ||x||1 represent the 1-norm of x, and ||X||2 represent the 1-norm of x. The formula means that, subject to the conditions YΦx≥0 and ||X||2=1, it calculates the minimum value of the 1-norm of x.

[0072] In this embodiment of the invention, the verification database can be a database generated based on pre-collected data of insecure IP addresses, or it can be an open-source IP address verification database. This is merely an example, and this embodiment does not impose any limitations. The security verification result is used to characterize whether the target identifier is secure. For example, if the target identifier is an IP address, the security verification result is used to characterize whether the IP address is secure.

[0073] In this embodiment of the invention, the target identifier can be compared with data in a preset verification database, and the comparison result can be used as the security verification result of the target identifier.

[0074] Optionally, step 102 may include:

[0075] The system checks whether any identifier data identical to the target identifier exists in the verification database.

[0076] If the same identifier data as the target identifier exists in the verification database, obtain the security verification result of the target identifier, wherein the security verification result indicates that the target identifier is insecure;

[0077] If no identifier data identical to the target identifier exists in the verification database, the target identifier is encrypted and verified according to the verification database and a preset hash value encryption algorithm to obtain the security verification result of the target identifier.

[0078] In this embodiment of the invention, key fields of the target identifier can be obtained, and these key fields can be matched with target fields in the verification database to detect whether there is identifier data in the verification database that is identical to the target identifier. If identifier data identical to the target identifier exists in the verification database, it indicates that the target identifier is identical to insecure identifier data in the verification database, and therefore the target identifier is also insecure.

[0079] In this embodiment of the invention, if no identifier data identical to the target identifier exists in the verification database, the target identifier can be further processed using a hash value encryption algorithm to obtain an encrypted identifier. This encrypted identifier is then encrypted and verified against the verification database to obtain the security verification result for the target identifier. The hash value encryption algorithm is a method of encrypting data using a hash function. In real-world scenarios, some source IP addresses are encrypted using hash functions. If an attacker intercepts the signal through eavesdropping, decrypts it using the hash function, modifies the source IP address, and then disguises the modified source IP address as data encrypted using the hash function.

[0080] In this embodiment of the invention, performing security verification on a target identifier based on a verification database may include directly detecting whether there is identifier data identical to the target identifier in the verification database, and, if no identifier data identical to the target identifier exists in the verification database, performing encrypted verification on the target identifier using a preset hash value encryption algorithm. In this way, if the target identifier itself is insecure, it can be easily and quickly detected directly in the verification database; if the target identifier itself is secure, it can also be encrypted and verified using a hash value encryption algorithm, thus improving the accuracy of the security verification results.

[0081] Optionally, the target identifier is encrypted and verified according to the verification database and a preset hash value encryption algorithm to obtain a security verification result of the target identifier, including:

[0082] The target identifier is encrypted using the hash value encryption algorithm to obtain a hash value encrypted string;

[0083] The system detects whether there is any identifier data in the verification database that has a similarity to the hash value encrypted string that meets a preset similarity threshold, and obtains the security verification result of the target identifier.

[0084] In this embodiment of the invention, the target identifier can be encrypted using a hash function to obtain a hash value encrypted string. For example, the hash function can be SHA-256. Specifically, the initial binary length of the target identifier can be obtained. If the initial binary length does not meet a preset length condition, the target identifier is padded with binary bits to obtain a first string, wherein the binary length of the first string meets the preset length condition. Based on the first string and the initial binary length, a second string is determined; the second string is divided into binary length blocks according to a preset block segmentation condition to obtain multiple substrings; and encryption processing is performed according to a preset encryption condition and the multiple substrings to obtain a hash value encrypted string.

[0085] For example, when using SHA-256 as the hash function, a preset length condition could be that the remainder after taking the binary length modulo 512 is 448. If the initial binary length does not meet the preset length condition, the target identifier must be padded to obtain the first string. After padding, the initial binary length is placed after the first string, and the binary data is converted to hexadecimal data to obtain the second string. A preset block segmentation condition could be that if the initial binary length exceeds 512 and the length of the second string is a multiple of 512, then the data is divided into blocks of 512 bits each; if the initial binary length does not exceed 512, then the data is divided according to the existing length of the second string. A preset encryption condition could be that each 512-bit data is divided into eight 64-bit binary data groups, and 32 bits of data are extracted from each binary data group. The extracted data is then concatenated to obtain a 256-bit hash value encrypted string.

[0086] In this embodiment of the invention, a hash-encrypted string can be matched with key strings in a verification database to detect whether there is any identifier data in the verification database whose similarity to the hash-encrypted string meets a preset similarity threshold. The detection result is then used as the security verification result of the target identifier. The preset similarity threshold can be a fixed value, such as 80%, or it can be determined based on the identifier data in the verification database. This embodiment of the invention does not impose any limitations on this.

[0087] In this embodiment of the invention, since the hash value encrypted string is obtained by encrypting the target identifier, the accuracy of the security verification result can be improved by detecting whether there is identifier data in the verification database that meets the preset similarity threshold with the hash value encrypted string.

[0088] Optionally, if there is identifier data in the verification database that has a similarity to the hash value encrypted string that meets a preset similarity threshold, the security verification result is that the target identifier is insecure; if there is no identifier data in the verification database that has a similarity to the hash value encrypted string that meets a preset similarity threshold, the security verification result is that the target identifier is secure.

[0089] Step 103: If the security verification result indicates that the target identifier is secure, perform signal reconstruction based on the target identifier and a preset signal reconstruction model to obtain the reconstructed signal corresponding to the sampled signal to be detected.

[0090] In this embodiment of the invention, if the security verification result indicates that the target identifier is secure, symbol information corresponding to the sampled signal to be detected can be obtained based on the target identifier. Then, signal reconstruction is performed based on the symbol information and a preset signal reconstruction model to obtain the reconstructed signal corresponding to the sampled signal to be detected. The signal reconstruction model can be a model that generates a signal reconstruction matrix based on the symbol information and reconstructs the sampled signal to be detected based on the signal reconstruction matrix. The signal reconstruction matrix includes a quantization matrix and a coefficient matrix corresponding to the sampled signal to be detected.

[0091] For example, the quantization process of the frequency domain sparse signal corresponding to the sampled signal to be detected can be written in the form of matrix multiplication, as shown in the following formula:

[0092] y = signθ × a](4)

[0093] Where y represents the symbol information of the frequency domain coefficient signal, θ represents the sensing matrix, and a represents the coefficient vector of the frequency domain sparse signal x(t) under the Fourier transform basis ψ. The sensing matrix θ consists of M×N elements and can be decomposed into the product of two matrices θ = ΦΨ, where Φ is the observation matrix. It can be understood that, given the observation matrix Φ and the sampled values ​​y, the sparse coefficient matrix a can be solved. Furthermore, signal reconstruction can be achieved according to the following formula:

[0094]

[0095] Where, ψ n (t) is a Fourier transform basis, a n Let be the Fourier transform coefficient vector, and x(t) be the sparse signal in the frequency domain. Optionally, for the sampled signal to be detected and quantized by a random demodulation quantization system, the observation matrix Φ can be decomposed into the product of two matrices Φ = P × H, where P represents a diagonal matrix composed of pseudo-random sequences, and H represents a matrix composed of the unit impulse response h(t) of the analog low-pass filter.

[0096] Optional, such as Figure 4 As shown, before step 103, the method further includes:

[0097] Step 105: Establish an address mapping between the target identifier and the symbol information, and store the symbol information in a preset symbol information database.

[0098] In this embodiment of the invention, the symbol information database is used to store symbol information obtained by quantizing the sampled signal to be detected. A mapping can be established between the target identifier and the storage address of the symbol information, so that the storage address of the symbol information can be found based on the target identifier and address mapping, and the symbol information can be obtained from that storage address.

[0099] Optionally, step 103 may also include:

[0100] Based on the address mapping between the target identifier and the symbol information, the symbol information of the sampled signal to be detected is obtained from the symbol information data;

[0101] The signal is reconstructed according to the preset signal reconstruction model and the symbol information of the sampled signal to be detected, and the reconstructed signal corresponding to the sampled signal to be detected is obtained.

[0102] In this embodiment of the invention, the storage address of the symbol information in the symbol information database can be obtained according to the address mapping of the target identifier and symbol information. The symbol information is then read from the symbol information database based on this storage address and used as the symbol information of the sampled signal to be detected. A signal reconstruction matrix can be generated based on the symbol information of the sampled signal to be detected, and signal reconstruction can be performed based on the signal reconstruction matrix and a preset signal reconstruction model to obtain the reconstructed signal corresponding to the sampled signal to be detected. The specific signal reconstruction process can be referred to the relevant description in step 103, and will not be repeated here.

[0103] In this embodiment of the invention, by establishing an address mapping between the target identifier and the symbol information, the symbol information corresponding to the address mapping can be easily obtained according to the target identifier, and the symbol information can be restored to the reconstructed signal corresponding to the sampled signal to be detected according to the preset signal reconstruction model.

[0104] In summary, a preset quantization model can quantize the acquired sampled signal to be detected into a symbolic representation. A preset generation model, based on the symbolic information, can reconstruct the target identifier of the sampled signal. A preset verification database is used to perform security verification on the target identifier, thus verifying the security of the sampled signal. If the security verification result indicates that the target identifier is secure, a preset signal reconstruction model can be used to reconstruct the signal, obtaining the reconstructed signal corresponding to the sampled signal. Since the reconstructed signal is obtained using the preset signal reconstruction model under the condition that the target identifier is secure, the security of the reconstructed signal can be improved.

[0105] Figure 5 This is a flowchart of another signal sampling method provided in an embodiment of the present invention, as shown below. Figure 5 As shown, for multiple sampled signals to be detected, the method may include:

[0106] Step 201: Obtain the sampled signal to be detected, and quantize the sampled signal to be detected according to the preset quantization model to obtain the sign information of the amplitude value of the sampled signal to be detected.

[0107] Specifically, the implementation method of this step can be referred to the relevant description of step 101 above, and will not be repeated here.

[0108] Step 202: Generate a target identifier for the sampled signal to be detected based on the symbol information and the preset generation model, and perform security verification on the target identifier based on the preset verification database to obtain the security verification result of the target identifier.

[0109] Specifically, the implementation method of this step can be referred to the relevant description of step 102 above, and will not be repeated here.

[0110] Step 203: For any of the sampling signals to be detected, determine the thread weight of the sampling signal to be detected based on the target identifier of the sampling signal to be detected.

[0111] In this embodiment of the invention, for any sampled signal to be detected, the sampling priority of the sampled signal to be detected can be determined according to the target identifier of the sampled signal to be detected, such as the source IP address of the sampled signal to be detected, and the thread weight corresponding to the sampled signal to be detected can be determined according to the sampling priority. For example, if the source of the sampled signal to be detected is determined to be a server according to the source IP address of the sampled signal to be detected, and the server has a higher sampling priority, then a higher thread weight can be assigned to the sampled signal to be detected.

[0112] Step 204: Sort the threads according to their respective thread weights to determine the thread order.

[0113] In this embodiment of the invention, the multiple sampled signals to be detected can be sorted according to the size of their respective thread weights to obtain a thread weight sequence, and the threads can be allocated according to the thread weight sequence to determine the thread order of the multiple sampled signals to be detected.

[0114] Step 205: If the security verification result indicates that the target identifier is secure, then according to the thread order, signal reconstruction is performed based on the target identifier and the preset signal reconstruction model to obtain the reconstructed signals corresponding to each of the multiple sampled signals to be detected.

[0115] In this embodiment of the invention, when the security verification result indicates that the target identifier is secure, signal reconstruction can be performed sequentially according to the thread order of multiple sampled signals to be detected, based on the target identifier and a preset signal reconstruction model. The process of reconstructing the signal based on the target identifier and the preset signal reconstruction model for any sampled signal to be detected can be referred to the relevant description in step 103, and will not be repeated here.

[0116] Optionally, the thread allocation for multiple sampling signals to be detected can be controlled based on the thread occupancy rate of the thread pool. The thread occupancy rate can be calculated using the following formula:

[0117]

[0118] Where N represents the number of worker threads in the thread pool at runtime, N max It is the maximum number of threads in the thread pool. T represents the saturation level of worker threads. cur T represents the number of tasks in the current data collection time window. pre This represents the number of tasks in the previous data collection window, and Q represents the size of the task buffer queue. Indicates the current task saturation level. ξ represents the growth rate of the task buffer queue, and ξ represents the weight coefficient.

[0119] Set the current thread occupancy rate ω ′ Compared with the preset thread pool load ω, if ω ′ If the value is greater than ω, the tasks in the current thread pool will be adjusted. For example, a task in the current thread pool can be stopped and returned to the task buffer queue to wait for thread rescheduling.

[0120] In this embodiment of the invention, when sampling multiple signals to be detected, threads can be allocated to the multiple signals to be detected according to the target identifier, and the signals to be detected can be reconstructed in an orderly manner according to the thread order of the multiple signals to be detected. In this way, the signal sampling efficiency for multiple signals to be detected can be improved.

[0121] Figure 6 This is a structural diagram of a signal sampling device provided in an embodiment of the present invention. The device 30 may include:

[0122] The first acquisition module 301 is used to acquire the sampled signal to be detected, and to quantize the sampled signal to be detected according to a preset quantization model to acquire the sign information of the amplitude value of the sampled signal to be detected.

[0123] The security verification module 302 is used to generate a target identifier of the sampled signal to be detected based on the symbol information and the preset generation model, and to perform security verification on the target identifier based on the preset verification database to obtain the security verification result of the target identifier;

[0124] The signal reconstruction module 303 is used to reconstruct the signal based on the target identifier and a preset signal reconstruction model when the security verification result indicates that the target identifier is safe, and to obtain the reconstructed signal corresponding to the sampled signal to be detected.

[0125] Optionally, the security verification module 302 is specifically used for:

[0126] The system checks whether any identifier data identical to the target identifier exists in the verification database.

[0127] If the same identifier data as the target identifier exists in the verification database, obtain the security verification result of the target identifier, wherein the security verification result indicates that the target identifier is insecure;

[0128] If no identifier data identical to the target identifier exists in the verification database, the target identifier is encrypted and verified according to the verification database and a preset hash value encryption algorithm to obtain the security verification result of the target identifier.

[0129] Optionally, the security verification module 302 is further configured to:

[0130] The target identifier is encrypted using the hash value encryption algorithm to obtain a hash value encrypted string;

[0131] The system detects whether there is any identifier data in the verification database that has a similarity to the hash value encrypted string that meets a preset similarity threshold, and obtains the security verification result of the target identifier.

[0132] Optionally, if there is identifier data in the verification database that has a similarity to the hash value encrypted string that meets a preset similarity threshold, the security verification result is that the target identifier is insecure; if there is no identifier data in the verification database that has a similarity to the hash value encrypted string that meets a preset similarity threshold, the security verification result is that the target identifier is secure.

[0133] Optionally, the device 30 further includes:

[0134] The mapping module is used by the signal reconstruction module 303 to reconstruct the signal according to the target identifier and the preset signal reconstruction model, and before obtaining the reconstructed signal corresponding to the sampled signal to be detected, to establish an address mapping between the target representation and the symbol information, and to store the symbol information in a preset symbol information database.

[0135] The signal reconstruction model 303 is specifically used for:

[0136] Based on the address mapping between the target identifier and the symbol information, the symbol information of the sampled signal to be detected is obtained from the symbol information data;

[0137] The signal is reconstructed according to the preset signal reconstruction model and the symbol information of the sampled signal to be detected, and the reconstructed signal corresponding to the sampled signal to be detected is obtained.

[0138] Optionally, for multiple sampled signals to be detected, the device 30 further includes:

[0139] The determination module is used to determine the thread weight of any of the sampled signals to be detected based on the target identifier of the sampled signal to be detected;

[0140] The sorting module is used to sort the threads according to their respective thread weights and determine the thread order.

[0141] The signal reconstruction model 303 is also specifically used for:

[0142] According to the thread sequence, signal reconstruction is performed based on the target identifier and the preset signal reconstruction model to obtain the reconstructed signals corresponding to each of the multiple sampled signals to be detected.

[0143] Optionally, the sampled signal to be detected is a time-domain sampled signal. Before quantizing the sampled signal to be detected according to a preset quantization model to obtain the sign information of the amplitude value of the sampled signal to be detected, the device 30 further includes:

[0144] The second acquisition module is used to expand the sampled signal to be detected in the frequency domain and obtain a frequency-domain sparse signal before the first acquisition module 301 quantizes the sampled signal to be detected according to a preset quantization model and obtains the sign information of the amplitude value of the sampled signal to be detected.

[0145] The first acquisition module 301 is specifically used for:

[0146] According to the preset random demodulation and quantization model, the frequency domain sparse signal is quantized to obtain the sign information of the amplitude value of the frequency domain sparse signal.

[0147] The signal sampling device and the signal sampling method described above have the same advantages over the prior art, and will not be repeated here.

[0148] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0149] The present invention also provides another electronic device 40, see [link to previous document]. Figure 7 The system includes: a processor 401, a memory 402, and a computer program stored in the memory 402 and executable on the processor 401. When the processor 401 executes the program, it implements the signal sampling method of the foregoing embodiments.

[0150] Figure 8 A schematic diagram of the hardware structure of another electronic device to implement an embodiment of this application.

[0151] The electronic device 50 includes, but is not limited to, components such as: radio frequency unit 501, network module 502, audio output unit 503, input unit 504, sensor 505, display unit 506, user input unit 507, interface unit 508, memory 509, and processor 510.

[0152] Those skilled in the art will understand that the electronic device 50 may also include a power supply (such as a battery) for supplying power to various components. The power supply may be logically connected to the processor 510 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. Figure 8 The electronic device structure shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0153] It should be understood that, in this embodiment, the input unit 504 may include a graphics processing unit (GPU) 5041 and a microphone 5042. The GPU 5041 processes image data of still images or videos obtained by an image capture device (such as a camera) in video capture mode or image capture mode. The display unit 506 may include a display panel 5061, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, or the like. The user input unit 507 includes at least one of a touch panel 5071 and other input devices 5072. The touch panel 5071 is also called a touch screen. The touch panel 5071 may include a touch detection device and a touch controller. Other input devices 5072 may include, but are not limited to, physical keyboards, function keys (such as volume control buttons, power buttons, etc.), trackballs, mice, and joysticks, which will not be described in detail here.

[0154] The memory 509 can be used to store software programs and various data. The memory 509 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback, image playback, etc.). Furthermore, the memory 509 may include volatile memory or non-volatile memory, or both. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 509 in this embodiment includes, but is not limited to, these and any other suitable types of memory.

[0155] Processor 510 may include one or more processing units; optionally, processor 510 integrates an application processor and a modem processor, wherein the application processor mainly handles operations involving the operating system, user interface, and applications, and the modem processor mainly handles wireless communication signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into processor 510.

[0156] The electronic device has the same advantages over the prior art as the signal sampling method described above, and will not be repeated here.

[0157] The present invention also provides a readable storage medium, wherein when the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is able to perform the signal sampling method of the foregoing embodiments.

[0158] The readable storage medium has the same advantages over the prior art as the signal sampling method described above, and will not be repeated here.

[0159] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other device. The structure required to construct such a system is readily apparent from the above description. Furthermore, this invention is not directed to any particular programming language. It should be understood that the contents of the invention described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best mode of implementation of the invention.

[0160] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0161] Similarly, it should be understood that, in order to simplify the invention and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof. However, this method of disclosure should not be construed as reflecting an intention that the claimed invention requires more features than expressly recited in each claim. Rather, as reflected in the following claims, inventive aspects lie in fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into this detailed description, wherein each claim itself is a separate embodiment of the invention.

[0162] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0163] The various component embodiments of the present invention can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components in the sorting device according to the present invention. The present invention can also be implemented as a device or apparatus program for performing part or all of the methods described herein. Such a program implementing the present invention can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0164] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0165] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0166] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0167] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0168] It should be noted that the various data-related processes in the embodiments of this application are carried out in compliance with the relevant data protection laws and policies of the country where the location is located, and with the authorization granted by the owner of the corresponding device.

Claims

1. A signal sampling method, characterized in that, The method includes: Acquire the sampled signal to be detected, and quantize the sampled signal to be detected according to a preset quantization model to obtain the sign information of the amplitude value of the sampled signal to be detected; Based on the diagonal matrix corresponding to the symbol information and a preset generation model, a target identifier for the sampled signal to be detected is generated. The target identifier is then subjected to security verification according to a preset verification database to obtain the security verification result. The target identifier is used to characterize the source of the sampled signal to be detected. The target identifier is determined by the following expression: in, The target identifier is represented by x, the sampled signal to be detected is represented by y, and the diagonal matrix corresponding to the symbol information is represented by y. Represents the quantization matrix. Denotes the 1-norm of x. Denote the 2-norm of x; If the security verification result indicates that the target identifier is secure, signal reconstruction is performed based on the target identifier and a preset signal reconstruction model to obtain the reconstructed signal corresponding to the sampled signal to be detected.

2. The method according to claim 1, characterized in that, The step of performing security verification on the target identifier according to a preset verification database and obtaining the security verification result of the target identifier includes: The system checks whether any identifier data identical to the target identifier exists in the verification database. If the same identifier data as the target identifier exists in the verification database, obtain the security verification result of the target identifier, wherein the security verification result indicates that the target identifier is insecure; If no identifier data identical to the target identifier exists in the verification database, the target identifier is encrypted and verified according to the verification database and a preset hash value encryption algorithm to obtain the security verification result of the target identifier.

3. The method according to claim 2, characterized in that, The step of encrypting and verifying the target identifier according to the verification database and a preset hash value encryption algorithm to obtain the security verification result of the target identifier includes: The target identifier is encrypted using the hash value encryption algorithm to obtain a hash value encrypted string; The system detects whether there is any identifier data in the verification database that has a similarity to the hash value encrypted string that meets a preset similarity threshold, and obtains the security verification result of the target identifier.

4. The method according to claim 3, characterized in that, If the verification database contains identifier data whose similarity to the hash value encrypted string meets a preset similarity threshold, the security verification result is that the target identifier is insecure. If no identifier data exists in the verification database that matches the preset similarity threshold of the hash value encrypted string, the security verification result indicates that the target identifier is secure.

5. The method according to any one of claims 1-4, characterized in that, Before reconstructing the signal based on the target identifier and a preset signal reconstruction model to obtain the reconstructed signal corresponding to the sampled signal to be detected, the method further includes: Establish an address mapping between the target identifier and the symbol information, and store the symbol information in a preset symbol information database; The step of reconstructing the signal based on the target identifier and a preset signal reconstruction model to obtain the reconstructed signal corresponding to the sampled signal to be detected includes: Based on the address mapping between the target identifier and the symbol information, the symbol information of the sampled signal to be detected is obtained from the symbol information data; The signal is reconstructed according to the preset signal reconstruction model and the symbol information of the sampled signal to be detected, and the reconstructed signal corresponding to the sampled signal to be detected is obtained.

6. The method according to any one of claims 1-4, characterized in that, For multiple sampled signals to be detected, the method further includes: For any of the aforementioned sampled signals to be detected, the thread weight of the sampled signal to be detected is determined based on the target identifier of the sampled signal to be detected; The threads are sorted according to their respective thread weights to determine the thread order. The step of reconstructing the signal based on the target identifier and a preset signal reconstruction model to obtain the reconstructed signal corresponding to the sampled signal to be detected includes: According to the thread sequence, signal reconstruction is performed based on the target identifier and the preset signal reconstruction model to obtain the reconstructed signals corresponding to each of the multiple sampled signals to be detected.

7. The method according to any one of claims 1-4, characterized in that, The sampled signal to be detected is a time-domain sampled signal. Before quantizing the sampled signal to be detected according to a preset quantization model to obtain the sign information of the amplitude value of the sampled signal to be detected, the method further includes: The sampled signal to be detected is expanded in the frequency domain to obtain a frequency-domain sparse signal; The step of quantizing the sampled signal to be detected according to a preset quantization model to obtain the sign information of the amplitude value of the sampled signal to be detected includes: According to the preset random demodulation and quantization model, the frequency domain sparse signal is quantized to obtain the sign information of the amplitude value of the frequency domain sparse signal.

8. A signal sampling device, characterized in that, The device includes: The first acquisition module is used to acquire the sampled signal to be detected, and to quantize the sampled signal to be detected according to a preset quantization model to obtain the sign information of the amplitude value of the sampled signal to be detected. A security verification module is used to generate a target identifier for the sampled signal to be detected based on the diagonal matrix corresponding to the symbol information and a preset generation model, and to perform security verification on the target identifier according to a preset verification database to obtain the security verification result of the target identifier; the target identifier is used to characterize the source of the sampled signal to be detected; the target identifier is determined by the following expression: in, The target identifier is represented by x, the sampled signal to be detected is represented by y, and the diagonal matrix corresponding to the symbol information is represented by y. Represents the quantization matrix. Denotes the 1-norm of x. Denote the 2-norm of x; The signal reconstruction module is used to reconstruct the signal based on the target identifier and a preset signal reconstruction model when the security verification result indicates that the target identifier is secure, and to obtain the reconstructed signal corresponding to the sampled signal to be detected.

9. An electronic device, characterized in that, include: A processor, a memory, and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the program, implements the signal sampling method as described in any one of claims 1-7.

10. A readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor of the electronic device, the electronic device is able to perform one or more of the signal sampling methods described in claims 1-7.

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