CN116405201A - Electrocardiosignal dynamic steganography method and system based on CEEMD and convolution error correction code - Google Patents
Electrocardiosignal dynamic steganography method and system based on CEEMD and convolution error correction code Download PDFInfo
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Abstract
The invention discloses an electrocardiosignal dynamic steganography method based on CEEMD and convolution error correction codes, which comprises the following steps of: s1, carrying out identity authentication and generating a shared secret key SK through a secret key distribution module; s2, preprocessing an original electrocardiosignal through a CEEMD model by an electrocardiosignal preprocessing module, and decomposing the original electrocardiosignal into a plurality of IMF components; s3, embedding the confidential information into each IMF component in the step S2 by adopting a convolution error correction code through a confidential information dynamic embedding module to generate an electrocardiosignal with the confidential information hidden; s4, decrypting and extracting the stored electrocardiosignals with the confidential information hidden by the decryption and recovery module. The invention also discloses an electrocardiosignal dynamic steganography system based on CEEMD and convolution error correction codes. The invention can increase the steganography capacity and enhance the security of the steganography transmission of electrocardiosignals.
Description
Technical Field
The invention relates to the technical field of information hiding, in particular to an electrocardiosignal dynamic steganography method and system based on CEEMD and convolution error correction codes.
Background
The electrocardiosignals are vulnerable to attack by malicious adversaries in the transmission process, so that steganography transmission of the electrocardiosignals is needed. However, the existing electrocardiographic signal steganography transmission has the following defects:
steganography embedding capacity is limited: the embedding capacity of the existing electrocardiosignal steganography scheme is usually smaller, because the electrocardiosignal is used as a physiological signal, the influence on the original information of the electrocardiosignal needs to be ensured to be minimized after the confidential information is embedded, and the electrocardiosignal has high complexity and randomness, so that the capacity capable of embedding the confidential information is limited.
The security of electrocardiosignal steganography is not high: in the existing electrocardiosignal steganography model, a secret key used for encrypting private information and a secret key used for determining the embedding position of the private information are mostly unchanged, so that the existing scheme cannot meet forward safety, once a sharing secret key is obtained by an adversary, the adversary can acquire confidential information steganographically in the electrocardiosignal before the secret key is obtained, and therefore private information of a user is revealed.
Therefore, a new electrocardiographic signal steganography scheme is urgently needed.
Disclosure of Invention
The invention aims to provide an electrocardiosignal dynamic steganography method and system based on CEEMD and convolution error correction codes, which can increase steganography capacity and enhance security of electrocardiosignal steganography transmission.
The technical scheme adopted by the invention is as follows:
an electrocardiosignal dynamic steganography method based on CEEMD and convolution error correction codes comprises the following steps:
s1, carrying out identity authentication and generating a shared secret key SK through a secret key distribution module; the method comprises the following steps: the user and the server perform identity authentication, and key negotiation is completed after authentication so as to generate a shared key SK;
s2, preprocessing an original electrocardiosignal through a CEEMD model by an electrocardiosignal preprocessing module, and decomposing the original electrocardiosignal into a plurality of IMF components;
s3, embedding the confidential information into each IMF component in the step S2 by adopting a convolution error correction code through a confidential information dynamic embedding module to generate an electrocardiosignal with the confidential information hidden;
and S4, decrypting and extracting the electrocardiosignals with the confidential information hidden by the decryption and recovery module.
According to the above scheme, in step S3, the step of embedding the confidential information into each IMF component in step S2 by using the convolutional error correction code through the confidential information dynamic embedding module, and generating the electrocardiograph signal with the confidential information hidden includes the steps of:
s31, generating a random sequence S by the shared secret key SK and Chebyshev chaotic mapping in the step S1, and storing a series of random numbers in the random sequence S;
s32, acquiring IMF coefficients to be embedded with errors in each IMF component in the step S2 through a random sequence S, converting the coefficients into integers and converting the integers into binary bit strings;
s33, encoding the bit string in the step S32 by using a (15,11,9) convolutional code to obtain check code words, and embedding the check code words into corresponding bit strings;
s34, adding two random errors to each bit string in step S33, which will be chosen completely randomly, recording the errors to generate a random bit string S 1 And S is 2 The method comprises the steps of carrying out a first treatment on the surface of the Random bit string S 1 As a key for encryption of confidential information at step S35, a random bit string S 2 The random embedding position is generated in an auxiliary mode to realize dynamic change of the embedding position of the confidential information;
s35, adopting AES encryption technology and random bit string S 12 Encrypting the confidential information and converting the obtained ciphertext into a binary bit string; embedding the binary bit strings into IMF coefficients; the embedding position of the confidential information will be in the random bit string S 2 Is assisted by (a)Dynamically generating the following steps;
s36, reconstructing the encrypted electrocardiosignals to generate electrocardiosignals with confidential information being hidden, and carrying out various evaluations on the signals;
s37, using random bit string S 2 The shared key is updated to obtain a new shared key SK'.
Secret information embedding is a key step in the proposal, and a series of complex operations are required to ensure the robustness and security of secret information embedding.
According to the scheme, in the step S33, the length of the check code word is 4 bits; (15,11,9) the convolutional code implements error correction of the encoded bit string by a maximum likelihood decoding algorithm.
In the above scheme, in step S2, hilbert transformation is performed on each IMF component.
According to the scheme, the electrocardiosignals with confidential information which are hidden in the step S3 are compressed by a Huffman coding-based compression algorithm before being stored.
According to the above scheme, the steps of compressing by the Huffman coding based compression algorithm before storing the electrocardiosignal with confidential information hidden in the step S3 are as follows:
1) Counting the occurrence frequency of characters:
traversing a file to be compressed, and recording the occurrence frequency of each character;
2) Constructing a Huffman tree:
taking the occurrence frequency of all characters as weight values, constructing a Huffman tree, wherein the characters with high occurrence frequency are taken as bottom nodes of the tree, and the characters with low occurrence frequency are taken as high-level nodes of the tree;
3) Constructing a coding table:
according to the construction of the Huffman tree, generating Huffman codes corresponding to each character; for example, a path from the root node to the leaf node has a left branch of 0 and a right branch of 1, thereby obtaining a coding table corresponding to each character;
4) Compression is carried out:
according to the generated coding table, converting each character in the file into corresponding Huffman codes, and outputting the coding sequences into a compressed file;
5) Writing compressed information:
the character occurrence frequency and the coding table information are written into the compressed file together so as to be decoded in the subsequent decompression.
According to the above scheme, the step of decrypting and extracting the electrocardiosignal with the confidential information hidden by the decryption and recovery module in the step S4 includes the steps of:
s41, obtaining an IMF coefficient embedded with confidential information;
s42, generating a random sequence S:
to determine the location of the embedding of the confidential information, a valid random sequence S needs to be generated; the random sequence S is generated by adopting a shared secret key SK and a chaotic mapping algorithm, so that the random sequence S adopted in the embedding process and the extracting process is identical;
obtaining a random number sequence using a random sequence S and a convolutional error correction code technique: generating a random bit string S using the obtained random sequence S and a convolutional error correction code 1 And S is 2 ；
S43, determining an embedding position:
using the generated random bit string S 2 The dynamic embedding position calculation algorithm determines the embedding position of the confidential information, and completes the operation of extracting the embedded confidential information from the IMF coefficient, and the process is similar to the dynamic selecting process of the confidential information embedding position in the embedding process;
s44, decrypting the embedded confidential information:
since the confidential information is encrypted by AES during the embedding process, a random bit string S is required during the extraction process 1 Decrypting the data as a secret key, and recombining the decrypted bit sequences to obtain confidential information; the process is the reverse operation process of encrypting, dividing and converting the confidential information into bit sequences in the embedding process;
s45 using random bit string S 2 The shared key SK is updated to ensure that the embedding position of the confidential information dynamically changes in each steganography process.
According to the above scheme, in step S41, when the received electrocardiosignal steganographic file is a compressed electrocardiosignal steganographic file, a Huffman coding decoding algorithm is used to decompress the compressed coefficient; and then obtaining the IMF coefficient embedded with the confidential information. The above operation is the reverse of the encoding table construction and compression in the compression process.
The invention also provides an electrocardiosignal dynamic steganography system based on CEEMD and convolution error correction code, which adopts the electrocardiosignal dynamic steganography method based on CEEMD and convolution error correction code, and comprises the following steps of
The key distribution module is used for carrying out identity authentication and generating a shared key SK;
the electrocardiosignal preprocessing module is used for preprocessing an original electrocardiosignal through a CEEMD model and decomposing the original electrocardiosignal into a plurality of IMF components;
the secret information dynamic embedding module is used for receiving the data transmitted by the secret key distribution module and the electrocardiosignal preprocessing module, embedding the secret information into each IMF component by adopting a convolution error correction code, and generating an electrocardiosignal with secret information hidden;
and the decryption and recovery module is used for receiving the data transmitted by the confidential information dynamic embedding module and decrypting and extracting the electrocardiosignal with the confidential information hidden.
According to the scheme, the steganography system further comprises a compression algorithm module, wherein the compression algorithm module is used for receiving data transmitted by the confidential information dynamic embedding module and performing compression algorithm compression based on Huffman coding on electrocardiosignals with steganography of the confidential information.
The invention has the beneficial effects that:
steganographic capacity increases: according to the invention, more secret information is embedded in one CEIMF coefficient, so that better invisibility is achieved. Meanwhile, the CEEMD is adopted to decompose the electrocardiosignal into a plurality of IMF components, so that the secret information is embedded in the components, and the steganography capacity is increased.
And (3) signal quality improvement: the CEEMD method is adopted to decompose the signals, so that effective noise reduction is realized, and the signal quality is improved. The CEEMD method is more suitable for processing non-stationary and non-linear signals than the conventional method, so that more signal details and local features can be preserved.
Concealment enhancement: the convolution error correcting code is adopted to generate random numbers for updating the secret key, so that the embedding position of secret information is changed each time, and the hidden property of steganography is effectively enhanced.
The calculated amount is reduced: the maximum likelihood decoding algorithm is adopted to carry out the decoding operation of the convolution error correction code, so that the calculation cost is effectively reduced, and the operation efficiency of the algorithm is improved.
The adaptability is strong: the invention can be applied to electrocardiosignals of different types, including electrocardiosignals of different lengths, sampling rates and amplitude ranges. Meanwhile, the method can also be applied to the steganography of other biomedical signals.
Has dynamic encryption capability: random numbers are generated through a convolutional code algorithm so as to realize dynamic encryption of confidential information, thereby further enhancing the security of steganography.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a schematic block diagram of an electrocardiosignal dynamic steganography method based on CEEMD and a convolution error correction code according to an embodiment of the invention.
FIG. 2 is a flow chart of an electrocardiosignal dynamic steganography method based on CEEMD and a convolution error correction code according to an embodiment of the invention.
Fig. 3 is a specific flowchart of step S3 in fig. 2.
Fig. 4 is a specific flowchart of step S4 in fig. 2.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The electrocardiosignal dynamic steganography method based on CEEMD and convolution error correction codes has strong adaptability, and can be applied to electrocardiosignals of different types, including electrocardiosignals with different lengths, sampling rates and amplitude ranges. Meanwhile, the method can also be applied to the steganography of other biomedical signals.
Example 1
Referring to fig. 1 and 2, the electrocardiosignal dynamic steganography method based on CEEMD and convolution error correction code of the present invention includes the following steps:
s1, carrying out identity authentication and generating a shared secret key SK through a secret key distribution module;
s2, preprocessing an original electrocardiosignal through a CEEMD model by an electrocardiosignal preprocessing module, and decomposing the original electrocardiosignal into a plurality of IMF components; performing Hilbert transform on each IMF component;
s3, embedding the confidential information into each IMF component in the step S2 by adopting a convolution error correction code through a confidential information dynamic embedding module to generate an electrocardiosignal with the confidential information hidden;
and S4, decrypting and extracting the electrocardiosignals with the confidential information hidden by the decryption and recovery module.
The invention adopts the CEEMD model to decompose the electrocardiosignal into a plurality of IMF components, thereby effectively reducing noise and improving signal quality. The CEEMD method is more suitable for processing non-stationary and non-linear signals than the conventional method, so that more signal details and local features can be preserved. The confidential information is embedded in the decomposed plurality of IMF components, further increasing the steganographic capacity. In addition, a convolution error correction code is adopted to generate a random number for updating the secret key, so that the embedding position of secret information can be changed each time, and the concealment of steganography is effectively enhanced.
As shown in fig. 3, step S3 may further include the steps of:
s31, generating a random sequence S by the shared secret key SK and Chebyshev chaotic mapping in the step S1, and storing a series of random numbers in the random sequence S;
s32, acquiring IMF coefficients to be embedded with errors in each IMF component in the step S2 through a random sequence S, converting the coefficients into integers and converting the integers into binary bit strings;
s33, encoding the bit string in the step S32 by using a (15,11,9) convolutional code to obtain check code words, wherein the length of each check code word is 4 bits, and embedding the check code words into the corresponding bit strings; (15,11,9) the convolutional code implements error correction of the encoded bit string by a maximum likelihood decoding algorithm; the present invention prefers (15,11,9) convolutional codes because the selection of this shorter check codeword provides 3 error correction capabilities.
S34, adding two random errors to each bit string in the step S33, and recording the errors to generate a random bit string S 1 And S is 2 The method comprises the steps of carrying out a first treatment on the surface of the Random bit string S 12 As a key for encryption of confidential information at step S35, a random bit string S 2 The random embedding position is generated in an auxiliary mode to realize dynamic change of the embedding position of the confidential information;
s35, adopting AES encryption technology and random bit string S 1 Encrypting the confidential information and converting the obtained ciphertext into a binary bit string; embedding the binary bit strings into IMF coefficients; the embedding position of the confidential information will be in the random bit string S 2 Is dynamically generated with the aid of the (a);
s36, reconstructing the encrypted electrocardiosignals to generate electrocardiosignals with confidential information being hidden; and various evaluations may be made of the signal. Such as by calculating evaluation indexes such as PRD (percentage of root-mean-square difference), PSNR (Peak Signal-to-Noise Ratio), BER (Bit Error Rate), etc.
S37, using random bit string S 2 The shared key is updated to obtain a new shared key SK'.
The maximum likelihood decoding mainly comprises a Viterbi algorithm, a BCJR algorithm, a Fano algorithm and the like, and the Viterbi algorithm is preferred in the invention. The Viterbi algorithm is a standard algorithm for maximum likelihood decoding, and can effectively reduce the error rate of code words. However, the computational complexity is high, and a large amount of computational resources are required to be consumed. The BCJR algorithm is also a decoding algorithm based on the maximum likelihood criterion, and has lower computational complexity compared to the Viterbi algorithm. However, it requires more memory space to store the decoding statuses. The Fano algorithm is an approximate maximum likelihood decoding algorithm with lower computational complexity relative to the Viterbi algorithm. However, the decoding performance is poor, and misinterpretation may occur.
The method enables the patent to have dynamic encryption capability, namely, random numbers are generated through a convolution code algorithm, so that dynamic encryption of confidential information is realized, and therefore, the security of steganography is further enhanced. In addition, the maximum likelihood decoding algorithm (such as Viterbi algorithm) is adopted to carry out the decoding operation of the convolution error correcting code, so that the calculation cost can be effectively reduced, and the operation efficiency of the algorithm can be improved.
Step S4 is the inverse operation of the embedding process, firstly, after receiving the compressed electrocardiosignal steganography file, decompressing the compressed coefficient by using a decoding algorithm of Huffman coding to obtain an EMD coefficient embedded with confidential information, generating a random sequence S according to a sharing secret key and a chaotic mapping algorithm, and determining the position of the EMD coefficient embedded with errors through the S. After obtaining EMD coefficients of the embedded errors, the embedded errors are obtained by using convolution error correction codes, and S is generated 1 And S is 2 For extraction and decryption. And finally, decrypting the embedded bit value so as to extract the confidential information. As shown in fig. 4, step S4 may further include:
s41, when the received electrocardiosignal steganography file is a compressed electrocardiosignal steganography file, firstly decompressing the compressed coefficient by using a decoding algorithm of Huffman coding; then obtaining the IMF coefficient embedded with the confidential information; this operation is the inverse of the encoding table construction and compression in the compression process.
S42, generating a random sequence S:
in order to determine the location of the embedding of the confidential information, a valid random sequence S needs to be generated. The random sequence S is generated by adopting a shared secret key SK and a chaotic mapping algorithm, so that the random sequence S adopted in the embedding process and the extracting process is identical;
acquiring a random number sequence by using S and convolution error correction code technology: generating a random bit string S using the obtained random sequence S and a convolutional error correction code 1 And S is 2 ；
S43, determining an embedding position:
using the generated random bit string S 2 And dynamic embedded position calculationDetermining the embedding position of the confidential information, and completing the operation of extracting the embedded confidential information from the IMF coefficient; this process is similar to the confidential information embedded bit dynamic selection process in the embedding process.
S44, decrypting the embedded confidential information:
in the extraction process, a random bit string S is required to be adopted 1 Decrypting the data as a secret key, and recombining the decrypted bit sequences to obtain confidential information; this process is the reverse of the encryption, segmentation and conversion of confidential information into a bit sequence during embedding.
S45 using random bit string S 2 The shared key SK is updated to ensure that the embedding position of the confidential information dynamically changes in each steganography process.
In this embodiment, further, in order to improve transmission efficiency and reduce storage overhead, the electrocardiographic signal may be subjected to compression processing before the confidential information is hidden from the electrocardiograph. If a compression algorithm based on Huffman coding is adopted, the occurrence frequency of each character in the file to be compressed is counted. Then, a Huffman tree is constructed based on the frequency of occurrence, wherein the character with the high frequency of occurrence is taken as the bottom node of the tree, and the character with the low frequency of occurrence is taken as the high-level node of the tree. Based on the above, huffman codes corresponding to each character are generated, the left branch of the path from the root node to the leaf node is 0, and the right branch is 1, so that the coding table of each character is obtained. Next, each character in the file to be compressed is converted into corresponding Huffman codes according to the generated code table, and these code sequences are output into the compressed file. And finally, writing the character occurrence frequency and the coding table information into the compressed file together so as to decode in the subsequent decompression. Thus, the files are successfully compressed, and the aim of reducing the storage space of the files is fulfilled. Compression algorithm compression based on Huffman coding specifically comprises the following steps:
1) Counting the occurrence frequency of characters:
traversing a file to be compressed, and recording the occurrence frequency of each character;
2) Constructing a Huffman tree:
taking the occurrence frequency of all characters as weight values, constructing a Huffman tree, wherein the characters with high occurrence frequency are taken as bottom nodes of the tree, and the characters with low occurrence frequency are taken as high-level nodes of the tree;
3) Constructing a coding table:
according to the construction of the Huffman tree, generating Huffman codes corresponding to each character; for example, the path from the root node to the leaf node branches to 0 on the left and 1 on the right, resulting in a coding table corresponding to each character.
4) Compression is carried out:
according to the generated coding table, converting each character in the file into corresponding Huffman codes, and outputting the coding sequences into a compressed file;
5) Writing compressed information:
the character occurrence frequency and the coding table information are written into the compressed file together so as to be decoded in the subsequent decompression.
Example 2
The electrocardiosignal dynamic steganography system based on the CEEMD and the convolution error correction code adopts the electrocardiosignal dynamic steganography method based on the CEEMD and the convolution error correction code, and comprises a key distribution module, an electrocardiosignal preprocessing module, a confidential information dynamic embedding module and a decryption and recovery module.
The key distribution module is used for the user to carry out secure communication with the server, and the process comprises two parts: identity authentication and shared secret key generation; through identity authentication, key negotiation is performed after legal identities of both sides are confirmed, a shared security key SK is obtained, and a user and a server use the key to assist in completing the secure embedding of confidential information in electrocardiosignals, and the method comprises the following steps: secret information encryption, embedded bit selection and the like, thereby enhancing the security of electrocardiosignal steganography.
The electrocardiosignal preprocessing module is used for preprocessing an original electrocardiosignal through a CEEMD model and decomposing the original electrocardiosignal into a plurality of IMF components; the electrocardiosignal preprocessing is an important step in the electrocardiosignal steganography process, and aims to remove noise and interference in the electrocardiosignal and improve the robustness and reliability of an embedding algorithm; for electrocardiosignals, the electrocardiosignals contain abundant physiological information, but are also easily affected by various noises, such as the electrocardiosignals, electromagnetic interference of acquisition equipment and the like; therefore, preprocessing of the electrocardiosignal is required before embedding of the confidential information to ensure that the embedded information is not interfered; CEEMD is a signal decomposition method that decomposes a signal into a plurality of eigenmode function (EMD) components and performs a hilbert transform on each component; the process can filter noise and interference in the signal, so that a purer signal is obtained; in this embodiment, the original electrocardiosignal is input into the CEEMD model, and is subjected to denoising processing, so that noise and interference in the electrocardiosignal are removed, and a group of smoother signal components are obtained, so that the robustness and reliability of embedded information can be improved, the influence on the characteristic value of the electrocardiosignal after the information is embedded is reduced, and the accuracy of the embedded and extracted information is improved.
The confidential information dynamic embedding module is used for receiving the data transmitted by the key distribution module and the electrocardiosignal preprocessing module, embedding the confidential information into each IMF component by adopting a convolution error correction code, and generating an electrocardiosignal with the confidential information hidden; first, a random sequence S is generated using a shared key SK and chebyshev chaotic map, before embedding the secret information, and a series of random numbers are stored in the random sequence S. The random sequence S is used to determine which IMF components to embed in error and to determine the location of IMF coefficients in each IMF component that need to be embedded in error. The random sequence generation method based on chaos can improve the safety of an embedding algorithm, so that the embedded confidential information is more difficult to detect and crack by an attacker. In addition, after each successful steganography, the shared secret key adopted by the round is updated, so that the dynamic change of steganography bits of confidential information in each steganography process is realized. Next, the IMF coefficients selected in the random sequence S are encoded with (15,11,9) convolutional codes, obtaining a check codeword of length 4 bits. Wherein (15,11,9) the convolutional code is a convolutional error correction code defined over the Galois field GF (2) which allows error correction of the encoded bit string by a maximum likelihood decoding algorithm. The coding length of the coding scheme is 15 bits, and the number of information bits is 11 bits2bit errors can be corrected. When the error smaller than or equal to 2bit appears in the encoded information, lossless restoration of the original information can be realized by using the check code word. Thus, 2bit error data are randomly embedded in the selected IMF coefficients and recorded as random bit strings S, respectively 1 And S is 2 . Wherein the random bit string S 1 As a key for the next secret information encryption, and using AES symmetric encryption technique to complete the encryption operation, a random bit string S 2 The random embedding position is generated in an auxiliary mode to realize dynamic change of the embedding position of the confidential information. Finally, the encrypted ciphertext is converted into binary bit strings, and the bit strings are embedded into the decomposed IMF coefficients. In order to improve the concealment of electrocardiosignal steganography, a random embedding strategy is adopted in the confidential information embedding process, so that illegal extraction of adversaries is effectively resisted. And finally, reconstructing the decomposed electrocardiosignals to obtain electrocardiosignals embedded with secret information, and evaluating the electrocardiosignals to verify the reliability and the practicability of the steganography scheme.
The decryption and recovery module is used for receiving the data transmitted by the confidential information dynamic embedding module and decrypting and extracting the electrocardiosignal with the confidential information hidden. The decryption and recovery process is the inverse operation of the embedding process, firstly, the IMF coefficient embedded with the confidential information is obtained, then a random sequence S is generated according to the shared secret key and the chaotic mapping algorithm, and the position of the IMF coefficient embedded with the error is determined through the random sequence S. After obtaining the IMF coefficients embedded with errors, the embedded errors are obtained using a convolutional error correction code, and a random bit string S is generated 1 And S is 2 For extraction and decryption. And finally, decrypting the embedded bit value so as to extract the confidential information.
Example 3
Unlike example 2, the following is: the steganography system also comprises a compression algorithm module, wherein the compression algorithm module is used for receiving data transmitted by the confidential information dynamic embedding module and carrying out compression algorithm compression based on Huffman coding on electrocardiosignals with steganography of the confidential information. In order to improve transmission efficiency and reduce storage cost, the electrocardiosignals are compressed. The compression adopts a compression algorithm based on Huffman coding, and the occurrence frequency of each character in the file to be compressed is counted. Then, a Huffman tree is constructed based on the frequency of occurrence, wherein the character with the high frequency of occurrence is taken as the bottom node of the tree, and the character with the low frequency of occurrence is taken as the high-level node of the tree. Based on the above, huffman codes corresponding to each character are generated, the left branch of the path from the root node to the leaf node is 0, and the right branch is 1, so that the coding table of each character is obtained. Next, each character in the file to be compressed is converted into corresponding Huffman codes according to the generated code table, and these code sequences are output into the compressed file. And finally, writing the character occurrence frequency and the coding table information into the compressed file together so as to decode in the subsequent decompression. Thus, the files are successfully compressed, and the aim of reducing the storage space of the files is fulfilled.
Example 4
The present invention also provides a computer readable storage medium such as a flash memory, a hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application store, etc., on which a computer program is stored that when executed by a processor performs a corresponding function. The computer readable storage medium of the present embodiment is for implementing the electrocardiosignal dynamic steganography method of the method embodiment based on CEEMD and convolutional error correction code when executed by a processor.
The invention designs an electrocardiosignal steganography scheme meeting forward safety by using a complete empirical mode decomposition (CEEMD) and convolution error correction code technology, thereby increasing steganography capacity, effectively enhancing steganography safety and improving transmission efficiency; by adopting the compression algorithm of Huffman coding, the occupation of storage space is effectively reduced, and the waste of resources is avoided.
The invention enhances the security of the electrocardiosignal steganography transmission, improves the stability and the efficiency of the transmission, has the advantages of large steganography capacity, high signal quality, strong concealment, small calculated amount, strong expandability and the like, and is suitable for application scenes of the electrocardiosignal steganography.
It will be understood that modifications and variations will be apparent to those skilled in the art from the foregoing description, and it is intended that all such modifications and variations be included within the scope of the following claims.
Claims (10)
1. An electrocardiosignal dynamic steganography method based on CEEMD and convolution error correction codes is characterized in that: the method comprises the following steps:
s1, carrying out identity authentication and generating a shared secret key SK through a secret key distribution module;
s2, preprocessing an original electrocardiosignal through a CEEMD model by an electrocardiosignal preprocessing module, and decomposing the original electrocardiosignal into a plurality of IMF components;
s3, embedding the confidential information into each IMF component in the step S2 by adopting a convolution error correction code through a confidential information dynamic embedding module to generate an electrocardiosignal with the confidential information hidden;
and S4, decrypting and extracting the electrocardiosignals with the confidential information hidden by the decryption and recovery module.
2. The method for dynamically steganographically recording electrocardiosignals based on CEEMD and convolutional error correction codes as claimed in claim 1, wherein: the step S3 specifically comprises the following steps:
s31, generating a random sequence S by the shared secret key SK and Chebyshev chaotic mapping in the step S1, and storing a series of random numbers in the random sequence S;
s32, acquiring IMF coefficients to be embedded with errors in each IMF component in the step S2 through a random sequence S, converting the coefficients into integers and converting the integers into binary bit strings;
s33, encoding the bit string in the step S32 by using a (15,11,9) convolutional code to obtain check code words, and embedding the check code words into corresponding bit strings;
s34, adding two random errors to each bit string in the step S33, and recording the errors to generate a random bit string S 1 And S is 2 The method comprises the steps of carrying out a first treatment on the surface of the Along with itBit string S 1 As a key for encryption of confidential information at step S35, a random bit string S 1 The random embedding position is generated in an auxiliary mode to realize dynamic change of the embedding position of the confidential information;
s35, adopting AES encryption technology and random bit string S 1 Encrypting the confidential information and converting the obtained ciphertext into a binary bit string; embedding the binary bit strings into IMF coefficients; the embedding position of the confidential information will be in the random bit string S 2 Is dynamically generated with the aid of the (a);
s36, reconstructing the encrypted electrocardiosignals to generate electrocardiosignals with confidential information being hidden;
s37, using random bit string S 2 The shared key is updated to obtain a new shared key SK'.
3. The electrocardiosignal dynamic steganography method based on CEEMD and a convolution error correction code as claimed in claim 2, wherein: in step S33, the length of the check code word is 4 bits; (15,11,9) the convolutional code implements error correction of the encoded bit string by a maximum likelihood decoding algorithm.
4. The method for dynamically steganographically recording electrocardiosignals based on CEEMD and convolutional error correction codes as claimed in claim 1, wherein:
in step S2, hilbert transform is performed on each IMF component.
5. The method for dynamically steganographically recording electrocardiosignals based on CEEMD and convolutional error correction codes as claimed in claim 1, wherein:
and (3) compressing by a compression algorithm based on Huffman coding before storing the electrocardiosignal with confidential information hidden in the step S3.
6. The method for dynamically steganographically recording electrocardiosignals based on CEEMD and convolutional error correction codes as claimed in claim 5, wherein: the compression algorithm based on Huffman coding comprises the following steps:
1) Counting the occurrence frequency of characters:
traversing a file to be compressed, and recording the occurrence frequency of each character;
2) Constructing a Huffman tree:
taking the occurrence frequency of all characters as weight values, constructing a Huffman tree, wherein the characters with high occurrence frequency are taken as bottom nodes of the tree, and the characters with low occurrence frequency are taken as high-level nodes of the tree;
3) Constructing a coding table:
according to the construction of the Huffman tree, generating Huffman codes corresponding to each character;
4) Compression is carried out:
according to the generated coding table, converting each character in the file into corresponding Huffman codes, and outputting the coding sequences into a compressed file;
5) Writing compressed information:
the character occurrence frequency and the coding table information are written into the compressed file together so as to be decoded in the subsequent decompression.
7. The method for dynamically steganographically recording electrocardiosignals based on CEEMD and convolutional error correction codes as claimed in claim 1, wherein:
the step S4 specifically comprises the following steps:
s41, obtaining an IMF coefficient embedded with confidential information;
s42, generating a random sequence S:
the random sequence S is generated by adopting a shared secret key SK and a chaotic mapping algorithm, so that the random sequence S adopted in the embedding process and the extracting process is identical;
acquiring a random number sequence by using S and convolution error correction code technology: generating a random bit string S using the obtained random sequence S and a convolutional error correction code 1 And S is 2 ；
S43, determining an embedding position:
using the generated random bit string S 2 The dynamic embedding position calculation algorithm determines the embedding position of the confidential information and finishes the operation of extracting the embedded confidential information from the IMF coefficient;
s44, decrypting the embedded confidential information:
in the extraction process, a random bit string S is required to be adopted 1 Decrypting the data as a secret key, and recombining the decrypted bit sequences to obtain confidential information;
s45 using random bit string S 2 The shared key SK is updated to ensure that the embedding position of the confidential information dynamically changes in each steganography process.
8. The method for dynamically steganographically recording electrocardiographic signals based on CEEMD and convolutional error correction codes of claim 7, wherein: in step S41, when the received electrocardiosignal steganographic file is a compressed electrocardiosignal steganographic file, firstly decompressing the compressed coefficient by using a Huffman coding decoding algorithm; and then obtaining the IMF coefficient embedded with the confidential information.
9. An electrocardiosignal dynamic steganography system based on CEEMD and convolution error correction codes is characterized in that: the system adopts the electrocardiosignal dynamic steganography method based on CEEMD and convolution error correction code as in any one of claims 1-8, which comprises a key distribution module for identity authentication and shared secret key SK generation;
the electrocardiosignal preprocessing module is used for preprocessing an original electrocardiosignal through a CEEMD model and decomposing the original electrocardiosignal into a plurality of IMF components;
the secret information dynamic embedding module is used for receiving the data transmitted by the secret key distribution module and the electrocardiosignal preprocessing module, embedding the secret information into each IMF component by adopting a convolution error correction code, and generating an electrocardiosignal with secret information hidden;
and the decryption and recovery module is used for receiving the data transmitted by the confidential information dynamic embedding module and decrypting and extracting the electrocardiosignal with the confidential information hidden.
10. The electrocardiosignal dynamic steganography system based on CEEMD and a convolutional error correction code as recited in claim 9, wherein:
the steganography system also comprises a compression algorithm module, wherein the compression algorithm module is used for receiving data transmitted by the confidential information dynamic embedding module and carrying out compression algorithm compression based on Huffman coding on electrocardiosignals with steganography of the confidential information.
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