Network friend system based on audio information hiding and audio information hiding method

Abstract

The application provides a network friend system based on audio information hiding and an audio information hiding method, and belongs to the field of audio information hiding, and comprises a safe chat module configured to encrypt to-be-embedded data into original digital audio by using a reversible data hiding algorithm to form first audio data and to communicate by using the first audio data; a hidden help-seeking module configured to set hidden alarm information in the to-be-embedded data, and to alarm after monitoring the hidden alarm information in real time; a sensitive word detection and automatic alarm module configured to monitor the to-be-embedded data in real time, and to automatically trigger an alarm mechanism after monitoring that the to-be-embedded data contains sensitive words; and a multi-channel audio processing module configured to provide additional information hiding capacity for the network friend system. The application realizes safe hiding and accurate extraction of user information without impairing the quality of audio.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of audio information hiding technology, and in particular to a network friend-making system scheme based on audio information hiding. BACKGROUND

[0002] With the rapid development of Internet technology, network friend-making has become an important part of modern social life. However, traditional network friend-making platforms have many challenges in user privacy protection and information security. Existing audio data hiding technologies (such as digital watermarking, information steganography, etc.) can embed information in audio, but often affect audio quality or have security risks. At the same time, with the frequent occurrence of network fraud and personal information leakage, users' demand for safe and reliable friend-making platforms is increasingly urgent.

[0003] In the prior art, audio hiding technology is easy to be cracked or tampered with, leading to easy leakage of personal privacy information, limited information hiding capacity, inability to support multi-channel processing and multiple audio formats, and audio quality being easily affected when noise occurs in the use environment.

[0004] Therefore, finding a method that can securely hide data while ensuring audio quality and adapting to different use scenarios is a technical problem that needs to be solved by those skilled in the art. SUMMARY

[0005] The present application provides a network friend-making system scheme based on audio information hiding, which solves the problem of data being unable to be securely hidden and the audio quality of hidden information being easily affected in the prior art, and realizes the secure hiding and accurate extraction of user information without damaging the audio quality, while supporting multiple audio formats and multi-channel processing.

[0006] The present application provides a network friend-making system based on audio information hiding, comprising:

[0007] A secure chat module configured to encrypt the to-be-embedded data to the original digital audio using a reversible data hiding algorithm to form first audio data, and use the first audio data for communication;

[0008] A hidden help-seeking module configured to set hidden alarm information in the to-be-embedded data, and the network friend-making system monitors the to-be-embedded information in real time and alarms when the hidden alarm information is detected;

[0009] A sensitive word detection and automatic alarm module configured to monitor the to-be-embedded data in real time, and automatically trigger the alarm mechanism when the to-be-embedded data contains sensitive words is detected;

[0010] A multi-channel audio processing module is configured to provide additional information hiding capacity for the network friend-making system.

[0011] According to the network friend-making system based on audio information hiding provided by the application, the secure chat module specifically comprises:

[0012] An audio signal processing unit is configured to perform audio signal analysis on the original digital audio, and determine the time point to be embedded, the frequency position to be embedded, and the channel to be embedded in the original digital audio; wherein the audio signal analysis comprises timestamp marker analysis, multi-channel analysis, time domain analysis, and frequency domain analysis.

[0013] An information encryption unit is configured to convert the data to be embedded into binary, and form an encrypted information matrix.

[0014] An information hiding unit is configured to generate a spectrogram from the original digital audio, and embed the encrypted information matrix into the original digital audio based on the time point to be embedded, the frequency position to be embedded, and the channel to be embedded of the original digital audio, to obtain first audio data; the first audio data comprises original digital audio data and encrypted data.

[0015] An information decryption unit is configured to receive the first audio data at the receiving end, extract the encrypted data based on linear code theory, and post-process the encrypted audio data to obtain the data to be embedded.

[0016] According to the network friend-making system based on audio information hiding provided by the application, the steps of the information hiding unit are as follows:

[0017] A spectrogram is generated from the original digital audio, and the energy value of each time-frequency unit in the spectrogram is calculated according to a noise threshold.

[0018] The environmental noise intensity is detected, the information embedding parameters of different scenes are dynamically adjusted according to the noise level, and the embedding energy threshold of different scenes is calculated based on the information embedding parameters of different scenes.

[0019] Based on the energy value of each time-frequency unit and the embedding energy threshold of different scenes, the energy area to be embedded is determined.

[0020] The encrypted information matrix is subjected to secret permutation processing to generate a carrier matrix, and the carrier matrix is subjected to information encoding to obtain an encoded matrix.

[0021] Based on the time point to be embedded, the frequency position to be embedded, the embeddable channel, and the energy area to be embedded, the encoded matrix is embedded into the energy area to be embedded using a reversible data hiding algorithm, and audio format packaging is performed to obtain first audio data.

[0022] According to the application, a network friend system based on audio information hiding is provided, wherein the information embedding parameter based on different scenes is used to calculate the embedding energy threshold value of different scenes, and the calculation formula is:

[0023] ;

[0024] ;

[0025] ;

[0026] wherein, represents the information embedding parameter in the chatting scene, represents the information embedding parameter in the emergency alarm scene, represents the information embedding parameter in the supervision scene, represents a constant, represents the chatting sensitivity level, represents a constant, represents the emergency level, represents a constant, represents the privacy protection level, represents the monitoring sensitivity level.

[0027] According to the application, a network friend system based on audio information hiding is provided, wherein the time domain analysis specifically includes:

[0028] calculating the average energy of the audio signal in the original digital audio;

[0029] dividing the audio signal of the original data audio into a plurality of time windows with a length of t, and calculating the energy of each time window;

[0030] identifying the current scene, setting the energy adjustment factor according to different scenes, and calculating the energy threshold value based on the energy adjustment factor;

[0031] determining the position and range of the low energy section and the position and range of the mute section according to the energy of each time window and the energy threshold value, and recording the low energy section as the embedding time point.

[0032] According to the application, a network friend system based on audio information hiding is provided, wherein the energy threshold value is calculated based on the energy adjustment factor, and specifically includes:

[0033] ;

[0034] ;

[0035] ;

[0036] wherein, represents an energy threshold in a chatting scenario, represents an energy threshold in an alarm scenario, represents an energy threshold in a supervision scenario, represents an average energy of an audio signal, represents an adjustment factor, represents an enhancement factor, represents a real-time adjustment factor, represents a monitoring sensitivity level.

[0037] According to the network friend system based on audio information hiding provided by the application, the steps of the information encryption unit are as follows:

[0038] The data to be embedded is converted into ASCII code, and the ASCII code is converted into 8-bit binary to obtain binary data of the data to be embedded;

[0039] An initial matrix is set, the binary data is serially connected in order, and the binary data serially connected in order is filled into the initial matrix to obtain an encryption information matrix;

[0040] Or,

[0041] The RGB value of each pixel of the data to be embedded is extracted, and the RGB value of each pixel is converted into 8-bit binary to obtain binary data of the data to be embedded;

[0042] An initial matrix is set, the binary data is serially connected in order, and the binary data is filled into the initial matrix to obtain an encryption information matrix.

[0043] The application further provides an audio information hiding method applied to the network friend system, and the method comprises the following steps:

[0044] S1, time stamp marking analysis is performed on an original audio signal, a feature vocabulary is selected according to different security requirements to perform time stamp marking, and a keyword time stamp is obtained;

[0045] S2, multi-channel analysis is performed on the original audio signal, and a embeddable channel is determined according to the total channel quantity in the original digital audio and the amount of hidden data;

[0046] S3, time domain analysis is performed on the original audio data, the energy of the original audio data is calculated according to an energy adjustment factor, and an energy area to be embedded is determined;

[0047] S4, frequency domain analysis is performed on the original audio data, and a frequency position to be embedded is determined according to an information embedding parameter;

[0048] S5, the data to be embedded is converted into binary, and an encryption information matrix is formed;

[0049] S6, based on the keyword timestamp, the embeddable sound channel, the energy area to be embedded, and the frequency position to be embedded, an encrypted information matrix is added to the energy area to be embedded by using a reversible data hiding algorithm, to obtain first audio data.

[0050] The application further provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the audio information hiding method according to any one of the above when executing the program.

[0051] The application further provides a non-transitory computer readable storage medium, which stores a computer program, and the computer program is executable on a processor to implement the audio information hiding method according to any one of the above.

[0052] The application provides an audio information hiding-based network friend system scheme, which combines reversible audio data hiding technology with a network friend system, realizes safe hiding and accurate extraction of user information without damaging audio quality, supports multiple audio formats and multi-channel processing, provides a safe and reliable new type of solution for network friendship, protects user privacy, and improves the safety and interest of social interaction. BRIEF DESCRIPTION OF DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the application or prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0054] Figure 1 is a flowchart of the network friend system provided by the application;

[0055] Figure 2 is a flowchart of the data embedding and extraction steps of the network friend system provided by the application;

[0056] Figure 3 is a spectrogram of an embodiment of the network friend system provided by the application;

[0057] Figure 4 is a function diagram of the network friend system provided by the application;

[0058] Figure 5 is one of the flowcharts of the audio information hiding method provided by the application;

[0059] Figure 6 is another flowchart of the audio information hiding method provided by the application;

[0060] Figure 7 is a structural schematic diagram of an electronic device provided by the present application. DETAILED DESCRIPTION

[0061] To make the objectives, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be described clearly and completely below in combination with the drawings and embodiments in the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0062] As shown in Figure 1 , an embodiment of the present application provides a network friend-making system based on audio information hiding, comprising:

[0063] a secure chat module configured to encrypt the to-be-embedded data into the original digital audio by using a reversible data hiding algorithm to form first audio data, and to use the first audio data for communication;

[0064] a hidden help-seeking module configured to set hidden alarm information in the to-be-embedded data, and to alarm after monitoring the hidden alarm information in real time;

[0065] a sensitive word detection and automatic alarm module configured to monitor the to-be-embedded data in real time, and to automatically trigger an alarm mechanism after monitoring that the to-be-embedded data contains sensitive words;

[0066] a multi-channel audio processing module configured to provide additional information hiding capacity for the network friend-making system.

[0067] As shown in Figure 2 , in an embodiment of the present application, the secure chat module specifically comprises:

[0068] an audio signal processing unit configured to perform audio signal analysis on the original digital audio to determine a to-be-embedded time point, a to-be-embedded frequency position and a to-be-embedded channel in the original digital audio; wherein the audio signal analysis includes timestamp marker analysis, multi-channel analysis, time domain analysis and frequency domain analysis;

[0069] an information encryption unit configured to convert the to-be-embedded data into binary and form an encrypted information matrix;

[0070] an information hiding unit configured to generate a spectrogram based on the original digital audio, and to embed the encrypted information matrix into the original digital audio based on the to-be-embedded time point, the to-be-embedded frequency position and the to-be-embedded channel of the original digital audio, to obtain first audio data; the first audio data includes original digital audio data and encrypted data;

[0071] The information decryption unit is configured to receive the first audio data by the receiving end, extract the encrypted data based on the linear code theory, post-process the encrypted audio data, and obtain the data to be embedded.

[0072] It can be understood that the secure chat module is first modulated by separating the original audio from the wav audio, finds the low-energy section or the silent section of the audio, determines the data point position and range based on the frequency domain analysis, the time domain analysis and the spectrogram, finds the corresponding binary idle code;

[0073] The secret information is reserved key binary coding, the binary coding of the secret information is combined with the binary idle coding in the original audio, and the wav audio carrying the secret information, i.e. the first audio data, is decompiled;

[0074] The first audio data is decoded to separate different coding information, the original audio coding and the secret information coding can be obtained, the secret information coding can be extracted based on the linear code theory, and the secret information can be obtained.

[0075] The reversible audio data hiding technology is combined with the network friend system, the secure hiding and accurate extraction of the user information are realized without damaging the audio quality, a variety of audio formats and multi-channel processing are supported, a safe and reliable new type solution is provided for the network friend, the user privacy is protected, and the security and interest of the social interaction are improved.

[0076] Specifically, in an embodiment of the present application, the audio signal analysis specifically includes:

[0077] The original audio signal is analyzed by time stamp marking, the characteristic words are selected for time stamp marking according to different security requirements, and the keyword time stamp is obtained.

[0078] The original audio signal is analyzed by multi-channel analysis, the embeddable channel is determined according to the total channel number and the amount of hidden data in the original digital audio.

[0079] The original audio data is analyzed by time domain analysis, the energy of the original audio data is calculated according to the energy adjustment factor, and the energy area to be embedded is determined.

[0080] The original audio data is analyzed by frequency domain analysis, and the frequency position to be embedded is determined according to the information embedding parameter.

[0081] In the embodiment of the present application, the customization requirement for different scene audio carriers is marked with characteristic words according to different security requirements. For daily chat, the Chinese audio takes "de" "you" "I" as the mark, and the appearance of these words is not easy to attract attention, while ensuring sufficient mark density. For the fast alarm encryption scene (119, 120, 110), the timestamp mark word selects the words that may appear in emergency situations, such as "save", "fire", "danger", etc. These words do not often appear in normal situations, but their use in emergency situations will not arouse suspicion. For the background real-time supervision, the words that may appear in the supervision scene are selected, such as "monitor", "manage", "review", etc. These words do not often appear in normal communication, but their use in the supervision environment is consistent with the context.

[0082] The present application adopts a timestamp marking method based on scene customization, selects corresponding mark words for different scenes (such as daily chat, alarm encryption, and background supervision), so that information hiding is more natural and less likely to be detected, while ensuring sufficient mark density, improving the concealment and practicality of information hiding.

[0083] In an embodiment of the present application, when the audio file is hidden with information using a timestamp, the precision of the timestamp is not less than 50 milliseconds.

[0084] In an embodiment of the present application, after analyzing the original audio signal with timestamp marking, information is hidden using the timestamp, which specifically includes:

[0085] Select a suitable audio file as a carrier, for example, a WAV format file;

[0086] Ensure that the precision of the timestamp is not less than 50 milliseconds to facilitate data hiding and extraction;

[0087] According to different scenes, select appropriate keywords for marking, for example, use common words such as "de", "you", "I" in daily chat; use words such as "save", "fire", "danger" in emergency situations; use words such as "monitor", "manage", "review" in the supervision scene;

[0088] Time block the original audio data, and perform audio information hiding. For example, if the timestamps are T1 and T2, the word "save" can be inserted between T1 and T2. By adjusting the interval of the timestamp, it is ensured that the appearance of each keyword will not attract attention, while maintaining sufficient mark density. Facilitate the extraction of the embedded data, parse the audio file, read the timestamp and identify the keywords. According to the order and position of the keywords, the hidden information is recovered.

[0089] Further, the time domain analysis specifically includes:

[0090] The average energy of the audio signal in the original digital audio is calculated, and the calculation formula is:

[0091] ;

[0092] wherein, represents the average energy of the audio signal, represents the total number of samples in the audio signal, represents the sample index, represents the audio signal, and N is a non-zero natural number;

[0093] The audio signal of the original data audio is divided into a plurality of time windows with a length of t, and the energy of each time window is calculated, and the calculation formula is:

[0094] ;

[0095] wherein, represents the energy of the i-th time window, represents the time window index, represents the length of the time window; i is the time window index, and is counted from zero, so the first sample of the i-th window is at index , and because the length of the window is t, the index of the last sample is +t-1=it-1;

[0096] identifying the current scene, setting an energy adjustment factor according to different scenes, and calculating an energy threshold based on the energy adjustment factor;

[0097] wherein, the energy threshold is calculated based on the energy adjustment factor, specifically including:

[0098] ;

[0099] ;

[0100] ;

[0101] wherein, represents the energy threshold in the chat scene, represents the energy threshold in the alarm scene, represents the energy threshold in the supervision scene, represents the average energy of the audio signal, represents the adjustment factor, represents the enhancement factor, represents the real-time adjustment factor, represents the monitoring sensitivity level;

[0102] According to the energy of each time window and the energy threshold, the position and range of the low energy segment and the position and range of the mute segment are determined, and the low energy segment is recorded as the time point to be embedded.

[0103] The sensitivity of the chat is set by the background of the network dating system, and the sensitivity is 0.3 when discussing daily chat, and the sensitivity of military and political chat is set according to the actual use. According to the expected attack type and the interference level, the value of S can be set, such as the attacker tries to destroy the hidden information by increasing the background noise, the value of S can be increased to ensure that the information can still be extracted under higher noise level.

[0104] According to the actual environmental monitoring data, the value of S can be set, such as if abnormal sound or known sensitive words are detected, the network dating system can increase the value of S to improve the detection probability of these events. S can be set according to various factors, such as the type, volume, frequency content of the sound or the known threat level, if the environmental sound contains known sensitive words or abnormal patterns, the value of S can be increased accordingly.

[0105] It can be understood that in the low energy segment of the audio signal, the mute segment is the ideal position for embedding data, because the embedded data is less likely to be detected. Set the threshold θ as 1% of the average energy, then for each time window, if its energy E is less than or equal to 0.01

[0106] , it can be considered that the time segment is a mute segment, the formula is as follows:

[0107]

[0108] , where represents the energy segment of the original digital audio, when , it means that the energy segment corresponding to the current time window is a mute segment, when , it means that the energy segment corresponding to the current time window is not a mute segment, and is not suitable for being embedded as a time point to be embedded.

[0109] Further, the frequency domain analysis specifically includes:

[0110] The Fourier transform is performed on the audio signal in the original digital audio to obtain the frequency domain representation of the original digital audio, and the calculation formula is as follows:

[0111] ;

[0112] , where represents the frequency domain representation, represents the frequency index, ​​denotes imaginary unit;

[0113] The energy of each frequency component is calculated according to the frequency domain representation, and the energy distribution of each frequency component is obtained; the calculation formula is:

[0114] ;

[0115] wherein, denotes the energy of the kth frequency;

[0116] The key frequency component and the non-key frequency component are determined according to the energy distribution of each frequency component, and the non-key frequency component is recorded as the frequency position to be embedded.

[0117] Specifically, an embedding threshold θ is set, which is based on the hearing sensitivity of the human ear and the characteristics of the audio signal. If is less than θ, it is considered that the frequency component is non-key and suitable for embedding data. If there is no non-key frequency in the audio, data can be embedded in part of the key frequency component.

[0118] In an embodiment of the present application, by using a phase embedding method, data is embedded by changing the phase of the signal, and the calculation formula is:

[0119] ;

[0120] wherein, denotes the phase change according to the data to be embedded;

[0121] The modified frequency domain representation is subjected to inverse Fourier transform to obtain the time domain signal after embedding data , and the calculation formula is:

[0122] .

[0123] It can be understood that the formula of the optimal embedding strategy is: .

[0124] In an embodiment of the present application, the multi-channel analysis specifically includes:

[0125] Analyzing the frequency characteristics and volume characteristics of each channel in the original digital audio;

[0126] Calculating the total number of channels and the amount of hidden data in the original digital audio, and determining the embeddable channel based on the frequency characteristics and volume characteristics.

[0127] wherein, the total number of channels = the number of audio tracks * the number of channels, and the bit position of the amount of all hidden data = the number of information points * the number of channels * the number of audio tracks.

[0128] The present application utilizes multi-channel audio processing technology, expands the information hiding capacity through the mode of total channel number=track number*channel number, and realizes larger capacity information hiding by combining frequency domain analysis and energy region selection, while ensuring audio quality and information extraction reliability.

[0129] In a specific embodiment, the present application is described as follows:

[0130] Sampling once per 4 seconds, a half-hour music file is a 4-track 2-channel file, and the data amount that can be hidden by the audio file 2-channel information hiding method is 30*4*2=240 bits.

[0131] As shown in the figure, in an embodiment of the present application, the steps of the information hiding unit are as follows: Figure 3

[0132] The original digital audio is generated into a spectrogram, and the energy value of each time-frequency unit in the spectrogram is calculated according to the noise threshold; the calculation formula is:

[0133]

[0134] Among them, E(t,f) represents the energy value of the time-frequency unit (t,f), T represents the time of the original digital audio, F represents the frequency of the original digital audio, Wt represents the size of the time window, Wf represents the size of the frequency window, E(t,f) represents the spectrogram energy value at time t and frequency f, (t,f) represents the time-frequency unit at time t and frequency f;

[0135] The environmental noise intensity is detected, the information embedding parameters of different scenes are dynamically adjusted according to the noise level, and the embedding energy threshold values of different scenes are calculated based on the information embedding parameters of different scenes;

[0136] Specifically, the embedding energy threshold values of different scenes are calculated based on the information embedding parameters of different scenes, and the calculation formula is:

[0137] ;

[0138] ;

[0139] ;

[0140] Among them, E1 represents the information embedding parameter in the chat scene, E2 represents the information embedding parameter in the emergency alarm scene, ​representing information embedding parameters in a regulatory scenario, representing a constant, representing a chat sensitivity level, representing a constant, representing an emergency level, representing a constant, representing a privacy protection level, representing a monitoring sensitivity level,

[0141] Based on the energy value of each time frequency unit and the different scene embedding energy threshold, a to-be-embedded energy area is determined;

[0142] The encrypted information matrix is subjected to secret permutation processing to generate a carrier matrix, and the carrier matrix is subjected to information encoding to obtain an encoded matrix;

[0143] Based on the to-be-embedded time point, the to-be-embedded frequency position, the embeddable channel and the to-be-embedded energy area, the encoded matrix is embedded into the to-be-embedded energy area using a reversible data hiding algorithm, and audio format packaging is performed to obtain first audio data.

[0144] The present application adjusts the energy threshold value dynamically, and adaptively adjusts the parameter (0.2-0.7) according to different environmental noise intensities (quiet environment, general environment, high noise environment), so as to ensure the effectiveness and robustness of information hiding in various complex environments, and improve the environmental adaptability of the system.

[0145] In the embodiment of the present application, dynamic information embedding parameters are set for different scenes , by analyzing the characteristics of the audio signal, dynamically setting different scene embedding energy threshold T, to adapt to different types of audio content and environment, thereby improving the robustness and concealment of steganography, and the calculation formula is:

[0146] ;

[0147] wherein, represents a different scene embedding energy threshold, represents an information embedding parameter in scene i, i represents different scenes, represents a proportion of the average energy of the spectrogram;

[0148] In the case of large environmental noise, in the environment where background noise (such as traffic noise, human voice, wind noise, etc.) and other interference sound exist, if the energy of the to-be-embedded information is set too low, the information may be completely lost in the subsequent signal processing (such as compression or noise reduction) process. According to the detected environmental noise intensity, the information embedding parameter is adaptively adjusted.

[0149] In a preferred embodiment of the present application, generally, Take 0.5; in a quiet environment, Suitably reduced to 0.2.

[0150] In the embodiments of the present application, the information embedding parameter The maximum value is 0.7.

[0151] In an embodiment of the present application, the information encryption unit is as follows:

[0152] Convert the data to be embedded into ASCII code, and convert the ASCII code into 8-bit binary to obtain the binary data of the data to be embedded;

[0153] Set the initial matrix, concatenate the binary data in order, and fill the binary data after concatenation in order into the initial matrix to obtain the encrypted information matrix;

[0154] Or,

[0155] Extract the RGB value of each pixel of the data to be embedded, and convert the RGB value of each pixel into 8-bit binary to obtain the binary data of the data to be embedded;

[0156] Set the initial matrix, concatenate the binary data in order, and fill the binary data into the initial matrix to obtain the encrypted information matrix.

[0157] Specifically, a specific embodiment is described:

[0158] If the secret data is already in binary form, use the text "miyou" as an example to show how to convert the secret data into binary form and organize it into a matrix for embedding into other media. Specifically:

[0159] Convert the text "miyou" into ASCII code:'m' -> 109, 'i' -> 105, 'y' -> 121, 'o' -> 111, 'u' -> 117;

[0160] Convert each ASCII code into 8-bit binary form:

[0161] 109 -> 01101101, 105 -> 01101001, 121 -> 01111001, 111 -> 01101111, 117 -> 01110101;

[0162] Concatenate the binary data in order to organize it into a matrix form:

[0163] Binary_Text = 01101101 01101001 01111001 01101111 01110101

[0164] A 3x5 matrix Q is selected to organize these data (because 3x5 = 15, and we have 5 characters, each of which is 8 bits, a total of 40 bits, which can be divided by 3x5), where the matrix Q is an MxN matrix, MxN≥L, M represents the number of rows of the matrix Q, N represents the number of columns of the matrix Q, and L represents the length of the binary data, i.e.:

[0165] Q = [011011010110100101111001011011110111010];

[0166] The binary data S is divided into MxN data blocks, each containing b bits (where b is the number of data bits per row or column), and if L cannot be divided by MxN, padding bits (such as 0) are used to pad S to a length of MxN, and the divided data blocks are organized into matrix Q in row or column mode, the formula is:

[0167]

[0168] wherein, represents the element in the ith row and jth column of the matrix Q, represents the index position calculated by row i and column j, represents the number of rows in the matrix Q, represents the number of columns in the matrix Q, represents the corresponding in the binary data S.

[0169] If the secret data is not binary data but an image, then for each color value of the RGB image, it is converted to 8-bit binary form, where each pixel is composed of three color values (R, G, B):

[0170]

[0171] wherein, represents the pixel point in the ath row and bth column of the image, represents the row coordinate of the image pixel, represents the column coordinate of the image pixel, represents the conversion of the decimal value (0-255) of the red component R to 8-bit binary, represents the conversion of the decimal value (0-255) of the green component G to 8-bit binary, represents the conversion of the decimal value (0-255) of the blue component B to 8-bit binary, represents the image red component value, represents the image green component value, represents the image blue component value, ​represents XOR operation.

[0172] With a specific embodiment for illustration:

[0173] A 3x3 RGB image, the RGB value of each pixel is as follows:

[0174]

[0175] Convert each color value into 8-bit binary form and concatenate them by row:

[0176]

[0177] wherein, represents the converted binary sequence,

[0178] Organize the encoded binary data into a matrix form for embedding.

[0179] In an embodiment of the present application, the binary form of the secret data is T, with a length of W bits, which is organized into a matrix P of RxY, wherein RxY≥W; R represents the number of rows of the matrix P, Y represents the number of columns of the matrix P, and W represents the length of the binary data T;

[0180] Divide the binary data T into R×Y data blocks, each data block containing bits (wherein is the number of data bits in each row or column). If W cannot be divided by R×Y, padding bits (such as 0) are needed to pad T to make its length R×Y. The divided data blocks are organized into a matrix P in a row or column manner, and the calculation formula is as follows:

[0181]

[0182] wherein, represents the element in the i'th row and j'th column of the matrix P, if represents the element in the i'th row and j'th column of the matrix P is the element in the i'th row and j'th column of the binary data T, if then represents the element in the i'th row and j'th column of the matrix P exceeds the length of the binary data T, and is padded with padding bits 0.

[0183] If R=4, Y=5, and W=17, the matrix P can be organized as follows:

[0184]

[0185] wherein, represents the first bit of the binary data T, represents the second bit of the binary data T, the third bit of the binary data T, the fourth bit of the binary data T, the fifth bit of the binary data T, the sixth bit of the binary data T, the seventh bit of the binary data T, the eighth bit of the binary data T, the ninth bit of the binary data T, the tenth bit of the binary data T, the eleventh bit of the binary data T, the twelfth bit of the binary data T, the thirteenth bit of the binary data T, the fourteenth bit of the binary data T, the fifteenth bit of the binary data T, the sixteenth bit of the binary data T, the seventeenth bit of the binary data T,

[0186] The audio binary data is organized into a matrix form suitable for embedding by using a drawing matrix.

[0187] As can be understood by those skilled in the art, data embedding and data extraction are inverse processes of encryption and decryption, and thus have the same principle and technology.

[0188] In an embodiment of the present application, the information decryption unit has the following steps:

[0189] The first audio data is received, a plurality of homogeneous matrices are selected as transmission carriers of the data to be embedded, the binary sequence of the data to be embedded is received, and the secret information is recovered based on linear code theory.

[0190] It can be understood that after numericalization, sampling, quantization and encoding, the digital audio generates a set of binary data, which is the secret information to be hidden.

[0191] An embodiment is described as follows:

[0192] The long binary information is divided into sub-information segments with equal length and small length, and then the sub-information segments are equally cut to generate a matrix with equal rows and columns. Taking "miyou" as an example,

[0193]

[0194] The matrix is shuffled to improve its encryption security, and a quasi-affine transformation over the integer field is introduced, which multiplies each element of the matrix V with e. Since Q is a binary matrix, this operation is actually a bitwise multiplication, but here we treat it as multiplication modulo 256 to handle possible overflow. The parameters e and f are chosen here to ensure the security and randomness of the transformation. The parameters e and f should satisfy the following conditions:

[0195] e should be an integer and coprime with the field size of the transformation (usually 256, because a byte has 256 possible values). This ensures that the multiplication operation is reversible modulo 256. f should be a random integer. The role of f is to add an offset to each element, increasing the complexity and security of the transformation. The quasi-affine transformation formula is as follows:

[0196]

[0197] where, represents the quasi-affine transformation matrix, represents the matrix with equal determinant, represents the coprime parameter, represents the offset parameter, represents bitwise multiplication, represents modulo 256;

[0198] After quasi-affine transformation, the matrix V is transformed to an integer promotion transformation, and e, f are rounded to integers, which completes the bijective transformation over the integer field , the calculation formula is as follows:

[0199]

[0200] where, represents the result matrix after bijective transformation, represents the x-coordinate value of the result matrix, represents the y-coordinate value of the result matrix, represents the quasi-affine transformation matrix, represents the element of the first row and first column of the quasi-affine transformation matrix, represents the element of the first row and second column of the quasi-affine transformation matrix, represents the element of the second row and first column of the quasi-affine transformation matrix, represents the element of the second row and second column of the quasi-affine transformation matrix, represents the original matrix V, represents the x-coordinate value of the original matrix V, represents the y-coordinate value of the original matrix V, represents the translation vector;

[0201] If e = 3, f = 5, then the first element of V (0*3+5) mod 256 = 5;

[0202] The second element of V (1*3+5) mod 256 = 8, and so on:

[0203]

[0204] Generate n N*M size matrix Ki, which will be used as the carrier of the information to be transmitted, and generate N*M size generator matrix G according to linear coding theory, wherein G h，g ∈Z, wherein h represents the number of rows of the matrix G, and g represents the number of columns of the matrix G. For each matrix Operation is performed to obtain the encoded matrix :

[0205]

[0206] Each row of the matrix can be regarded as a linearly coded code word, and the result is subjected to XOR operation to obtain the encoded matrix .

[0207] Generate Ci matrices of the same size as Ki on Z2. And define the sequence: S1, S2, …, Sm, C1, C2, …, C , D0, D1, …, D + , wherein Di is generated by summing the previous + matrices and taking modulo 2:

[0208]

[0209] , wherein represents the last D value in the sequence, represents the first D value in the sequence, represents the second D value in the sequence, represents the second last D value in the sequence;

[0210] Di is the cumulative sum of all previous D values and S values and values, which is equivalent to adding all the matrices bit by bit, if the result is odd, then Di = 1; if it is even, then Di = 0;

[0211] We randomly select a number r ∈ Z and a bivariate one-way function f(r, β). For each Ki, we compute its matrix Ki' = f(r, β) mod 2 of the same size, and compute Ti = Di - Ki' mod 2. Finally, we generate a matrix G, a random number r, a one-way function f(r, β), and a sequence T1, T2, ..., T D +1,D +2,…,D + Output;

[0212] The receiving end received Each carrier Ki (i = 1, 2, 3…) After that, based on the random number r and f(r, k), Ti (i=1, 2, 3… ), Di ( i= +1, +2… + ), calculate Ki' (i=1,2,3… Di (i=1, 2, 3… Combining this with the coefficient matrix, we can then solve for S1, ..., S. C1, ..., C This yields the encrypted message "miyou".

[0213]

[0214] in, Represents an encryption matrix. This represents the element in the first row and first column of the encryption matrix. This represents the element in the second row and first column of the encryption matrix. Indicates the encryption matrix number 1 + The element in the first column of the row, This represents the element in the first row and second column of the encryption matrix. This represents the element in the second row and second column of the encryption matrix. Indicates the encryption matrix number 1 + The element in the second column of the row, This represents the first row of the encryption matrix. + Column elements, This indicates the second row of the encryption matrix. + elements, Indicates the encryption matrix number 1 + Line number + Elements of a column;

[0215] In the embodiment of the application, the python code is reasonably merged and then decompiled into a wav audio with secret information. Different encoded information is decoded and separated to obtain secret information and retain binary encoding. The audio signal embedded with data is packaged into a proper file format for transmission. That is, the technology is implemented by code after packaging, only leaving the interface part. The user runs the encode file code, selects the secret file, selects the audio carrier file for encryption, and obtains the encrypted audio file. Running the decode file code, uploading the encrypted audio file, and obtaining the secret information.

[0216] Among them, the decode file has two functions, the first function is to read the hidden data bytes from the wav file, starting from the lowest two bits of each text, and the second function is to extract the hidden data from the wav file and save it as an image file or a text file. Read all bytes of the wav file, parse the wav structure, get the wav data part, and then read the hidden data size. Finally, save the corresponding format file and output the data memory size.

[0217] The encode is an encryption file, which contains three functions, the first function changes the signed integer to unsigned integer, the second function hides a byte of data into the pcm data of the wav file, and the third function calculates the space available for hiding in the wav file by reading all bytes of the wav, image file and text file. If it can, convert the image to four-byte binary data, put the file size and data into the wav, and then write the prepared wav into a new file.

[0218] These two files are the core files of the technology implementation, and calling the code of these two files in the network friend system can realize encryption and decryption.

[0219] As shown in Figure 4 The network friend system of the application is described in a specific embodiment:

[0220] Login and registration are performed through "personal user registration and login", if the password is forgotten, the password can be reset;

[0221] After successful login, friend management is performed through "personal information and management", such as recommending friends, adding friends, deleting friends, etc.; friend management can also be performed through "search and matching";

[0222] When chatting with friends, text chat can be used, and voice chat can also be used, and in the voice chat, sound information is hidden, when the sound hidden information contains hidden help-seeking information or sensitive words are detected, a help-seeking signal is automatically sent, or a warning or prompt is given;

[0223] After the user logs in the "quiet friend", security and privacy protection is performed, when sensitive words appear in the use process, a help-seeking signal is automatically sent, or a warning or prompt is given.

[0224] As shown in Figure 5 The application further provides an audio information hiding method applied to the network friend system, and the method comprises the following steps:

[0225] S1, time stamp marking analysis is performed on the original audio signal, feature words are selected according to different security requirements to perform time stamp marking, and a keyword time stamp is obtained;

[0226] S2, multi-channel analysis is performed on the original audio signal, and the embeddable channel is determined according to the total channel quantity and the amount of hidden data in the original digital audio;

[0227] S3, time domain analysis is performed on the original audio data, the energy of the original audio data is calculated according to an energy adjustment factor, and a to-be-embedded energy area is determined;

[0228] S4, frequency domain analysis is performed on the original audio data, and a to-be-embedded frequency position is determined according to an information embedding parameter;

[0229] S5, the to-be-embedded data is converted into binary, and an encrypted information matrix is formed;

[0230] S6, based on the keyword time stamp, the embeddable channel, the to-be-embedded energy area and the to-be-embedded frequency position, a reversible data hiding algorithm is used to add the encrypted information matrix to the to-be-embedded energy area, and first audio data is obtained.

[0231] As shown in Figure 6 Specifically, at the sending end, secret data H is embedded into original carrier audio I by using a data embedding method, and then the audio W after embedding the secret data is sent to the receiver. At the receiving end, the embedded secret data H is extracted by using a data extraction and audio recovery method, and the original carrier audio I is recovered.

[0232] The network friend device provided by the application is described below, and the network friend device described below can be correspondingly referred to the audio information hiding method described above.

[0233] Figure 7 An example of an entity structure schematic diagram of an electronic device is shown in Figure 7As shown, the electronic device can include a processor 710, a communications interface 720, a memory 730, and a communications bus 740, wherein the processor 710, the communications interface 720, and the memory 730 complete mutual communication through the communications bus 740. The processor 710 can invoke a logical instruction in the memory 730 to execute an audio information hiding method, which includes: performing timestamp marker analysis on an original audio signal, selecting a feature vocabulary for timestamp marking according to different security requirements, and obtaining a keyword timestamp; performing multi-channel analysis on the original audio signal, determining an embeddable channel according to the total channel quantity in the original digital audio and the amount of hidden data; performing time domain analysis on the original audio data, calculating the energy of the original audio data according to an energy adjustment factor, and determining an energy region to be embedded; performing frequency domain analysis on the original audio data, determining a frequency position to be embedded according to an information embedding parameter; converting the data to be embedded into binary, and forming an encrypted information matrix; based on the keyword timestamp, the embeddable channel, the energy region to be embedded, and the frequency position to be embedded, adding the encrypted information matrix to the energy region to be embedded by using a reversible data hiding algorithm, and obtaining first audio data.

[0234] In addition, the logical instructions in the memory 730 described above can be implemented in the form of a software functional unit and sold or used as an independent product, and can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the part of the technical solutions that essentially contribute to the prior art or the part of the technical solutions can be embodied in the form of a software product, which is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various program code storage media.

[0235] In another aspect, the present application also provides a computer program product comprising a computer program, which can be stored on a non-transitory computer readable storage medium, and the computer program can be executed by a processor to enable a computer to perform the audio information hiding method provided by the above-mentioned methods, which comprises: performing timestamp marking analysis on the original audio signal, selecting a feature vocabulary for timestamp marking according to different security requirements, and obtaining a keyword timestamp; performing multi-channel analysis on the original audio signal, determining an embeddable channel according to the total number of channels in the original digital audio and the amount of hidden data; performing time domain analysis on the original audio data, calculating the energy of the original audio data according to an energy adjustment factor, and determining an energy region to be embedded; performing frequency domain analysis on the original audio data, determining a frequency position to be embedded according to an information embedding parameter; converting the data to be embedded into binary and forming an encrypted information matrix; and based on the keyword timestamp, the embeddable channel, the energy region to be embedded, and the frequency position to be embedded, adding the encrypted information matrix to the energy region to be embedded using a reversible data hiding algorithm to obtain first audio data.

[0236] In another aspect, the present application also provides a non-transitory computer readable storage medium having a computer program stored thereon, and the computer program can be executed by a processor to implement the audio information hiding method provided by the above-mentioned methods, which comprises: performing timestamp marking analysis on the original audio signal, selecting a feature vocabulary for timestamp marking according to different security requirements, and obtaining a keyword timestamp; performing multi-channel analysis on the original audio signal, determining an embeddable channel according to the total number of channels in the original digital audio and the amount of hidden data; performing time domain analysis on the original audio data, calculating the energy of the original audio data according to an energy adjustment factor, and determining an energy region to be embedded; performing frequency domain analysis on the original audio data, determining a frequency position to be embedded according to an information embedding parameter; converting the data to be embedded into binary and forming an encrypted information matrix; and based on the keyword timestamp, the embeddable channel, the energy region to be embedded, and the frequency position to be embedded, adding the encrypted information matrix to the energy region to be embedded using a reversible data hiding algorithm to obtain first audio data.

[0237] The device embodiments described above are merely illustrative, wherein the units described as separate components can or can not be physically separated, and the components displayed as units can or can not be physical units, i.e., they can be located in one place or distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the present embodiment scheme according to actual needs. Those skilled in the art can understand and implement it without creative labor.

[0238] Those skilled in the art can clearly understand the technical solutions of the various embodiments from the above description of the embodiments, and the various embodiments can be implemented by means of software with the necessary general hardware platforms, and of course, can also be implemented by hardware. Based on such understanding, the above technical solutions, essentially or in other words, the part of the prior art that makes a contribution, can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, and the like, and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0239] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for some technical features therein; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A network dating system based on hidden audio information, characterized in that, include: The secure chat module is configured to encrypt the data to be embedded into the original digital audio using a reversible data hiding algorithm to form first audio data, and use the first audio data for communication. The concealed distress module is configured to set concealed alarm information in the data to be embedded. The online dating system monitors the data to be embedded in real time and issues an alarm when the concealed alarm information is detected. The sensitive word detection and automatic alarm module is configured to monitor the data to be embedded in the online dating system in real time, and automatically trigger an alarm mechanism when sensitive words are detected in the data to be embedded. A multi-channel audio processing module, configured to provide additional information hiding capacity for online dating systems; The process of encrypting the data to be embedded into the original digital audio using a reversible data hiding algorithm to form first audio data and using the first audio data for communication includes: determining the time point to be embedded, the frequency position to be embedded, and the channel to be embedded in the original digital audio; converting the data to be embedded into binary and forming an encrypted information matrix; and embedding the encrypted information matrix into the original digital audio based on the time point to be embedded, the frequency position to be embedded, and the channel to be embedded in the original digital audio to obtain the first audio data.

2. The online dating system based on hidden audio information according to claim 1, characterized in that, The secure chat module specifically includes: An audio signal processing unit is configured to perform audio signal analysis on raw digital audio to determine the time point to be embedded, the frequency position to be embedded, and the channel to be embedded in the raw digital audio; wherein the audio signal analysis includes timestamp analysis, multi-channel analysis, time domain analysis, and frequency domain analysis. An information encryption unit is configured to convert the data to be embedded into binary and form an encrypted information matrix; The information hiding unit is configured to generate a spectrogram from the original digital audio, and using the spectrogram as a reference, embed an encrypted information matrix into the original digital audio based on the embedding time point, embedding frequency position, and embedding channel of the original digital audio to obtain first audio data; the first audio data includes original digital audio data and encrypted data. The information decryption unit is configured to receive the first audio data at the receiving end, extract encrypted data based on linear code theory, and perform post-processing on the encrypted audio data to obtain the data to be embedded.

3. The online dating system based on hidden audio information according to claim 2, characterized in that, The steps of the information hiding unit are as follows: The original digital audio is used to generate a spectrogram, and the energy value of each time frequency unit in the spectrogram is calculated based on the noise threshold. The system detects ambient noise intensity, dynamically adjusts information embedding parameters for different scenarios based on noise levels, and calculates embedding energy thresholds for different scenarios based on these parameters. Based on the energy value of each time frequency unit and the embedding energy threshold for different scenarios, the energy region to be embedded is determined. The encrypted information matrix is ​​secretly scrambled to generate a carrier matrix, and the carrier matrix is ​​then encoded to obtain an encoding matrix. Based on the time point to be embedded, the frequency position to be embedded, the embeddable channel, and the energy region to be embedded, the encoding matrix is ​​embedded into the energy region to be embedded using a reversible data hiding algorithm, and then encapsulated in an audio format to obtain the first audio data.

4. The online dating system based on hidden audio information according to claim 3, characterized in that, The embedding energy threshold for different scenarios is calculated based on the information embedding parameters for different scenarios, and the calculation formula is as follows: ； ； ； in, This represents the information embedding parameters in a chat scenario. This indicates the information embedding parameters in emergency alarm scenarios. This indicates the information embedding parameters in a regulatory scenario. Represents a constant. Indicates the level of sensitivity in the chat. Represents a constant. Indicates the level of urgency. Represents a constant. Indicates the level of privacy protection. This indicates the level of sensitivity to surveillance.

5. A network dating system based on hidden audio information according to claim 2, characterized in that, The time-domain analysis specifically includes: Calculate the average energy of the audio signal in the original digital audio; The original audio data is divided into multiple time windows of length t, and the energy of each time window is calculated. Identify the current scene, set energy adjustment factors according to different scenes, and calculate the energy threshold based on the energy adjustment factors; Based on the energy and energy threshold of each time window, determine the location and range of the low-energy segment and the location and range of the silent segment, and record the low-energy segment as the time point to be embedded.

6. A network dating system based on hidden audio information according to claim 5, characterized in that, The calculation of the energy threshold based on the energy adjustment factor specifically includes: ； ； ； in, This represents the energy threshold in a chat scenario. This indicates the energy threshold under alarm scenarios. This indicates the energy threshold under regulatory scenarios. This represents the average energy of the audio signal. Indicates the adjustment factor. Indicates the enhancing factor. This indicates a real-time adjustment factor. This indicates the level of sensitivity to surveillance.

7. A network dating system based on hidden audio information according to claim 2, characterized in that, The steps of the information encryption unit are as follows: The data to be embedded is converted into ASCII code, and the ASCII code is converted into 8-bit binary code to obtain the binary data of the data to be embedded. Set an initial matrix, concatenate binary data in order, and fill the initial matrix with the concatenated binary data to obtain the encrypted information matrix. or, Extract the RGB value of each pixel in the data to be embedded, and convert the RGB value of each pixel into 8-bit binary data to obtain the binary data of the data to be embedded. Set an initial matrix, concatenate binary data in sequence, and fill the initial matrix with the binary data to obtain the encrypted information matrix.

8. A method for hiding audio information, characterized in that, The method applied to the online dating system as described in any one of claims 1-7 includes the following steps: S1. Perform timestamp analysis on the original audio signal, select feature words for timestamp marking according to different security requirements, and obtain keyword timestamps; S2. Perform multi-channel analysis on the original audio signal and determine the embeddable channels based on the total number of channels and the amount of data that can be hidden in the original digital audio. S3. Perform time-domain analysis on the raw audio data, calculate the energy of the raw audio data based on the energy adjustment factor, and determine the energy region to be embedded. S4. Perform frequency domain analysis on the original audio data and determine the position of the frequency to be embedded based on the information embedding parameters; S5. Convert the data to be embedded into binary and form an encrypted information matrix; S6. Based on the keyword timestamp, embeddable channel, energy region to be embedded, and frequency position to be embedded, a reversible data hiding algorithm is used to add the encrypted information matrix to the energy region to be embedded to obtain the first audio data.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the audio information hiding method as described in claim 8.

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 audio information hiding method as described in claim 8.

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