CN116527278A - Block chain hidden communication method based on generation type hidden network and image double hidden - Google Patents

Block chain hidden communication method based on generation type hidden network and image double hidden Download PDF

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CN116527278A
CN116527278A CN202310561034.7A CN202310561034A CN116527278A CN 116527278 A CN116527278 A CN 116527278A CN 202310561034 A CN202310561034 A CN 202310561034A CN 116527278 A CN116527278 A CN 116527278A
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picture
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steganography
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刘媛妮
赵宇洋
张建辉
蒙科知
张欣
魏国柱
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Chongqing University of Post and Telecommunications
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    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
    • H04L9/3247—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials involving digital signatures

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Abstract

The invention relates to a block chain hidden communication method based on a generation type hidden network and image double hidden, which comprises the following steps: the sending end generates a carrier picture by utilizing a WGAN countermeasure network and a convolution steganalysis network; the sender divides the secret information into two parts and sequentially embeds the secret information into carrier pictures by using an airspace steganography algorithm and a ciphertext domain reversible information hiding algorithm to obtain a second carrier picture, compresses and stores the second carrier picture into an IPFS file system, and returns a hash plaintext abstract; the sender encrypts the hash plaintext abstract based on a certificate-free public key cryptosystem to obtain a hash ciphertext abstract and signature information; the receiving party takes the hash plaintext abstract as input of an IPFS file system, and obtains a second encrypted picture embedded by the sending party; and the receiver decrypts the second encrypted picture by using a space domain steganography algorithm and a ciphertext domain reversible information hiding algorithm according to the encryption process of the sender on the private information to obtain the private information.

Description

Block chain hidden communication method based on generation type hidden network and image double hidden
Technical Field
The invention belongs to the technical field of artificial intelligence and data security, and particularly relates to a block chain hidden communication method based on a generation type hidden network and image double hidden.
Background
The hidden communication technology is a solution for secure transmission of secret information and hiding the communication process of both parties by protecting the communication channel from eavesdropping. Existing implementations of covert communication include anonymous communication, digital watermarking, steganography, and the like. Steganography, which is a specific implementation method of covert communication, generates non-suspected secret information by embedding secret information into carrier information, and is widely used for hiding information.
With the development of deep learning technology, aiming at the problem that an attacker can illegally acquire secret information by observing or enumerating a steganography algorithm, the hidden communication based on deep learning can generate carrier information through a generated countermeasure network, the generated carrier information is more similar to an original carrier after being embedded, then the embedded carrier information is classified through a convolutional neural network, and when the carrier information is detected to be not embedded, the carrier information is transmitted as final carrier information. Although the method can finally generate the secret information with higher similarity, the secret information must be used together with a steganography algorithm with low embedding rate, and when the transmitted secret information is large in quantity, an attacker can easily distinguish the carrier information and the secret information even though a convolution steganography analysis network is used. When an attacker uses a more accurate steganography detection network, then the carrier generated by the generation of the countering network cannot be used as a proper and effective carrier, steganalysis attacks are still difficult to resist, and the schemes always transmit information on a centralized untrusted network, so that the security of secret information is difficult to ensure.
The blockchain has the characteristics of decentralization, node anonymization, data non-falsification, transparency and the like. The blockchain hidden communication based on deep learning ensures the reliable decentralization network transmission of information and simultaneously ensures the anonymity of the identities of the two communication parties. However, when the blockchain technology is introduced, the process of generating the encrypted information still faces the problem of high storage overhead, and part of methods utilize IPFS to compress the encrypted information into character strings, so that the storage pressure of transmitting the character strings in a blockchain network is reduced. However, most schemes use LSB algorithm to embed the string, which can generate a large number of account transaction addresses, resulting in still high cost of transmitting the string. In addition, during the generation of the block, other non-receiving network node users can also acquire transaction information, thereby causing security threat.
Aiming at the problems of steganalysis attack, low embedding rate, unsafe information transmission, high transmission cost and the like faced by the prior steganography invention, the invention provides a block chain steganography scheme for generating a steganography analysis network and double steganography of images.
Disclosure of Invention
In order to solve the problems in the background art, the invention provides a block chain hidden communication method based on a generation type hidden network and image double hidden, which aims to ensure the safety of hidden information transmission and the integrity of hidden information, and comprises the following steps:
s1: the sender utilizes a generator in the WGAN countermeasure network to generate an image sample G (z), embeds a random value into the image sample through a airspace steganography algorithm to obtain a generated picture Steg (G (z)) as an input of a discriminator, and utilizes a real picture data set to train the WGAN countermeasure network;
s2: after the WGAN countermeasure network training is completed, a sender takes a generated picture Steg (G (z)) as input of a convolution steganography analysis network, trains the convolution steganography analysis network by utilizing a real picture data set, and screens out an un-embedded image from the generated picture Steg (G (z)) as a carrier picture through the trained convolution steganography analysis network;
s3: the sender divides the secret information into two parts and sequentially embeds the secret information of the two parts into a carrier picture by using a space domain steganography algorithm and a ciphertext domain reversible information hiding algorithm to obtain a second carrier picture; compressing and storing the second encrypted picture to an IPFS file system, returning the hash plaintext abstract, and setting access control authority;
s4: the sender encrypts the hash plaintext abstract based on a certificate-free public key cryptosystem to obtain a hash ciphertext abstract and signature information, encodes the hash ciphertext abstract and the signature information by using Base58 codes respectively, and adds a character string ' 0 ' between the encoded hash ciphertext abstract and the signature information to splice to obtain a signature information character string delta ';
s5: the sender removes repeated characters in the signature information character string delta ', and splices again to obtain an intermediate signature character string delta' with different characters, matches the transaction address of the node in the blockchain network with the intermediate signature character string delta ', records indexes of successfully matched characters in the delta' and the node transaction address, and sequentially fills the indexes into extraData fields of node transactions according to the sequence of the indexes; the node transactions are packed into blocks after being verified, and when all the transactions in the blocks are verified by other nodes, the blocks are transmitted through a block chain network;
s6: the receiver acquires index information filled into the node transaction extraData field from the block, acquires the hash ciphertext abstract and signature information by decoding the index information, verifies the signature information and decrypts the hash abstract ciphertext into a hash plaintext abstract by using a private key of the sender;
s7: the receiving party takes the hash plaintext abstract as input of an IPFS file system, and obtains a second encrypted picture embedded by the sending party;
s8: and the receiver decrypts the second encrypted picture by using a space domain steganography algorithm and a ciphertext domain reversible information hiding algorithm according to the encryption process of the sender on the private information to obtain the private information.
Further, the training of the WGAN countermeasure network includes:
calculating the distance between the data distribution of Steg (G (z)) and the data distribution of the real picture, so as to distinguish the real picture from the generated picture, and converting the solved Wasserstein distance into the following by Kantorovich-Rubinstein duality:
limiting the continuous function f w The variation width of (a) is that the gradient is w, and the value of w is [ -c, -c]The loss function converted into WGAN against the network is:
wherein,,the distribution of random noise is z-p z The lower discriminator discriminates the probability of Steg (G (z)),/->The distribution expressed in the real data set x is x-p r Judging the probability of the real image;
the purpose of the generator is to make the Wasserstein distance smaller, its loss function isThe purpose of the arbiter is to make the distance between the real data distribution and the generated data distribution larger, and its loss function isThe generator and the discriminator perform continuous iterative optimization of the gradient descent update parameters until the loss function converges.
Further, the carrier picture includes:
when the SRNet network judges that the generated Steg (G (z)) is a picture without embedding, taking the Steg (G (z)) picture as a carrier picture; otherwise, continuing to train the SRNet network until Steg (G (z)) is judged to be a picture without embedding.
Further, the step of embedding the two parts of secret information into the carrier picture to obtain the second carrier picture by using the airspace steganography algorithm and the ciphertext domain reversible information hiding algorithm sequentially includes:
s31: embedding first secret information into the carrier picture by using an airspace steganography algorithm to obtain a first carrier picture;
s32: embedding second secret information into the first secret-carrying picture by utilizing a reversible information hiding algorithm of the ciphertext domain to obtain a second secret-carrying picture;
the embedding the second secret information into the first secret image to obtain the second secret image comprises the following steps:
s321: taking a first row and a first column of a first encrypted picture as fixed pixels, wherein the predicted value of the fixed pixels is kept unchanged; other non-fixed pixels predict pixels through a median predictor MED to obtain a predicted image;
s322: comparing the binary representation of the pixel values of the non-fixed pixels in the first encrypted picture and the predicted image one by one from the highest bit to the lowest bit, taking the bit number of the same pixel value as a corresponding mark position value, setting the mark position value of the fixed pixel as-1, and converting the mark position value of the non-fixed pixel into an eight-bit binary representation;
s323: counting the occurrence probability of each marking position value, constructing Huffman tree data, solving Huffman codes corresponding to each marking position value according to a rule of left 0 and right 1, and recording position diagram information; the position diagram information consists of additional information and binary representation of a Huffman coding sequence, wherein the additional information comprises binary representation of the Huffman coding length corresponding to a mark position value, the corresponding relation between the Huffman coding sequence and the mark position value and the binary representation of the total length of the Huffman coding sequence;
s324: using a predetermined encryption key e 1 Generating a pseudo-random matrix R with the same size as the first secret-carrying picture, multiplying the pseudo-random matrix R by the corresponding pixel of the first secret-carrying picture to obtain an encrypted image, and representing the pixel value of the encrypted image by binary;
s325: selecting the first N rows and the first M columns of pixels in the encrypted image as encrypted fixed pixels, and sequentially embedding the recorded position map information into the encrypted fixed pixels from left to right from top to bottom; dividing non-fixed pixels of an encrypted image into a plurality of pixel blocks according to 2 x 2, embedding Huffman coding sequences corresponding to marking position values in four pixels in the pixel blocks into the pixel blocks, and embedding binary representation of the encrypted fixed pixels from left to right from top to bottom if the pixel blocks have an embedding space after the embedding is completed; if the embedding space is insufficient, embedding in the next pixel block until the binary representation value of all the encrypted fixed pixels is embedded;
s326: using a preset encryption key e 2 And encrypting the second secret information, and after the encrypted fixed pixels are embedded, the additional embedded space in the pixel block starts to be embedded with the encrypted second secret information, so that a second secret-carrying picture is obtained after the embedding is completed.
Further, the embedding the huffman coding sequence corresponding to the marked position values in the four non-fixed pixels in the pixel block into the pixel block comprises:
wherein t represents the mark position value of the non-fixed pixel, b s And representing the Huffman coding sequence corresponding to the mark position value, and when the mark position value t of the non-fixed pixel in the pixel block is less than or equal to 7, the embedding space size of the pixel in the pixel block is t+1 bits.
Further, encrypting the hashed plaintext digest includes:
s41: KGC generates a random number lambda, takes the random number lambda as a system private key s, multiplies the system private key s by a base point G on an elliptic curve to obtain a system public key P pub ＝s.G；
S42: the sender user identification is ID, KGC generates a random number r ID Calculating R ID ＝r ID G, wherein G represents a fixed base point on the elliptic curve, generating the partial private key D ID ＝r ID +s·H(ID,R ID ) And R is taken as ID And partial privacyKey D ID Returning to a sender, wherein H represents a hash function;
s43: sender authentication D ID ·G＝R ID +P pub ·H(ID,R ID ) Whether or not it is true, if so, D ID Valid, otherwise invalid;
s44: sender randomly selects secret number x ID Calculate X ID ＝x ID G, public sender public key PK ID ＝(R ID ,X ID ) And calculates the private key as SK ID ＝(D ID ,x ID )；
S45: the sender will private key SK ID Encrypted transmission to the receiver by negotiated session key and pkid= (R) using public key ID ,X ID ) Encrypting the hash plaintext abstract m to obtain a hash ciphertext abstract m';
s46: the sender selects a random number T and calculates t=t· G, v =h (m, T, R ID ,X ID ) U=t=x ID (H(ID,R ID )+v)+D ID Signature information δ= (u, v) is generated.
Further, the decoding the index information to obtain the hash ciphertext digest and the signature information includes:
s61: the receiver checks all transaction information related to the sender from the block, and filters index information contained in extraData fields of all transaction information; recombining and restoring the signature information character string delta' according to index information contained in extraData fields of all transaction information;
s62: the receiver separates the restored signature information character string delta' into the signature information coded by the Base58 and the hash ciphertext abstract through the character string 0; decoding by using Base58 to obtain signature information and hash ciphertext abstract of the sender;
s63: the receiver uses the public key of the sender to verify the signature information, if the verification is passed; and decrypting the hash ciphertext abstract by using the private key of the sender to obtain the hash plaintext abstract.
Further, the receiving side verifying the signature information using the public key of the transmitting side includes:
h＝H(ID,R ID ),T'＝u·G-X ID *(h+v)-R id -P pub *h,v'＝H(m,T',R ID ,X ID ) If v=v', the verification passes.
The invention has at least the following beneficial effects
(1) The WGAN is adopted to generate an countermeasure network and an SRNet steganalysis network, so that the problems of training of the traditional GAN and accurate detection of whether the load is high or not are solved, and a airspace steganography algorithm is used for processing the generated samples in the WGAN training process, so that the finally generated carrier picture is ensured not to be distorted and the capability of resisting steganalysis attack is achieved.
(2) The carrier information is divided into two parts, and the airspace steganography algorithm and the ciphertext domain reversible information hiding algorithm are sequentially utilized for mixed embedding, so that the problem that the neural network is difficult to train the algorithm with high embedding rate is solved, an attacker is prevented from extracting information through enumerating the airspace steganography algorithm, and the safety is improved.
(3) By storing the character string index, the storage cost is reduced, access control authority is set to prevent malicious internal nodes from acquiring secret information, and the security of the decentralised network is ensured.
Drawings
FIG. 1 is a general communication flow diagram of an embodiment of the present invention;
FIG. 2 is a flow chart of a generating steganography network according to an embodiment of the present invention;
FIG. 3 is a flow chart of image steganography embedding in accordance with an embodiment of the present invention;
FIG. 4 is a block chain data transmission flow chart according to an embodiment of the present invention.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the illustrations provided in the following embodiments merely illustrate the basic idea of the present invention by way of illustration, and the following embodiments and features in the embodiments may be combined with each other without conflict.
Wherein the drawings are for illustrative purposes only and are shown in schematic, non-physical, and not intended to limit the invention; for the purpose of better illustrating embodiments of the invention, certain elements of the drawings may be omitted, enlarged or reduced and do not represent the size of the actual product; it will be appreciated by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The same or similar reference numbers in the drawings of embodiments of the invention correspond to the same or similar components; in the description of the present invention, it should be understood that, if there are terms such as "upper", "lower", "left", "right", "front", "rear", etc., that indicate an azimuth or a positional relationship based on the azimuth or the positional relationship shown in the drawings, it is only for convenience of describing the present invention and simplifying the description, but not for indicating or suggesting that the referred device or element must have a specific azimuth, be constructed and operated in a specific azimuth, so that the terms describing the positional relationship in the drawings are merely for exemplary illustration and should not be construed as limiting the present invention, and that the specific meaning of the above terms may be understood by those of ordinary skill in the art according to the specific circumstances.
Referring to fig. 1, the present invention provides a blockchain hidden communication method based on a generation type hidden network and image double hidden, comprising:
referring to fig. 2, S1: the sender utilizes a generator in the WGAN countermeasure network to generate an image sample G (z), embeds a random value into the image sample through a airspace steganography algorithm to obtain a generated picture Steg (G (z)) as an input of a discriminator, and utilizes a real picture data set to train the WGAN countermeasure network;
the generating model G of the WGAN is a multi-layer perceptron and is mainly used for generating false picture samples, and the picture samples G (z) can be generated by inputting random noise z (z is a random variable obeying Gaussian distribution);
after the picture sample G (z) is generated, a proper amount of information, namely a random value, is embedded into the picture sample through an airspace self-adaptive steganography algorithm to obtain a loaded picture sample Steg (G (z)) which is used as an input of a discriminator.
The obtained Steg (G (z)) is input to the discrimination model D of WGAN, and the other part of the discrimination model is the real picture data set.
Calculating the distance between the data distribution of Steg (G (z)) and the data distribution of the real picture, so as to distinguish the real picture from the generated picture, and converting the solved Wasserstein distance into the following by Kantorovich-Rubinstein duality:
limiting the continuous function f w The variation width of (a) is that the gradient is w, and the value of w is [ -c, -c]The loss function converted into WGAN against the network is:
wherein,,the distribution of random noise is z-p z The lower discriminator discriminates the probability of Steg (G (z)),/->The distribution expressed in the real data set x is x-p r Judging the probability of the real image;
the purpose of the generator is to make the Wasserstein distance smaller, its loss function isThe purpose of the arbiter is to make the distance between the real data distribution and the generated data distribution larger, and its loss function isThe generator and the discriminator perform continuous iterative optimization of the gradient descent update parameters until the loss function converges.
S2: after the WGAN countermeasure network training is completed, a sender takes a generated picture Steg (G (z)) as input of a convolution steganography analysis network, trains the convolution steganography analysis network by utilizing a real picture data set, and screens out an un-embedded image from the generated picture Steg (G (z)) as a carrier picture through the trained convolution steganography analysis network;
preferably, the training the convolutional steganalysis network SRNet includes:
the input of the convolution steganography analysis network SRNet is Steg (G (z)), the other part of the input is a real picture data set, the first 7 layers of the SRNet network extract Steg (G (z)) steganographically embedded high-frequency noise through convolution operation, then 8-12 layers use convolution layers connected through residual errors and use average pooling operation for reducing the dimension of a feature map, and finally the full-connection layer is used as a classifier for classifying the picture; the perceptual loss function form of SRNet selection is as follows:
PerceptualLoss＝λ*ContentLoss+γ*StyleLossss
wherein λ and γ are parameters that trade-off content loss and style loss, controlling the weight of both losses in the total loss; content Loss is used for measuring similarity of a generated image and a real image on a feature level, and Style Loss is used for measuring Style difference, namely category difference, between the generated image and the real image.
The training process of the convolutional steganalysis network SRNet is as follows:
(a) The low resolution image is input into SRNet and the output image is calculated by forward propagation. The output image is then compared to the corresponding high resolution image, and the value of the loss function is calculated. Next, the network parameters are updated using a random gradient descent back-propagation algorithm, reducing the value of the loss function.
(b) In the training process, super parameters such as learning rate, regularization term, batch size and the like are adjusted so as to obtain better model performance.
(c) Iterative training: repeating steps a and b until a predetermined number of training rounds or model performance is reached.
(2) Obtaining a carrier picture: when the SRNet network judges that the generated Steg (G (z)) is a picture without embedding, taking the Steg (G (z)) picture as a carrier picture; otherwise, continuing to train the SRNet network until Steg (G (z)) is judged to be a picture without embedding.
As shown in fig. 3, S3: the sender divides the secret information into two parts and sequentially embeds the secret information of the two parts into a carrier picture by using a space domain steganography algorithm and a ciphertext domain reversible information hiding algorithm to obtain a second carrier picture; compressing and storing the second encrypted picture to an IPFS file system, returning the hash plaintext abstract, and setting access control authority;
preferably, the step of embedding the two parts of secret information into the carrier picture to obtain the second carrier picture by using the airspace steganography algorithm and the ciphertext domain reversible information hiding algorithm sequentially includes:
s31: embedding first secret information into the carrier picture by using an airspace steganography algorithm to obtain a first carrier picture;
s32: embedding second secret information into the first secret-carrying picture by utilizing a reversible information hiding algorithm of the ciphertext domain to obtain a second secret-carrying picture;
the embedding the second secret information into the first secret image (secret image 1) to obtain the second secret image includes:
s321: taking a first row and a first column of a first encrypted picture as fixed pixels, wherein the predicted value of the fixed pixels is kept unchanged; other non-fixed pixels predict pixels through a median predictor MED to obtain a predicted image;
preferably, the predicting the pixel by MED includes:
wherein the upper left-adjacent three pixels of the p pixel are c, b, a, respectively.
S322: comparing the binary representation of the pixel values of the non-fixed pixels in the first encrypted picture and the predicted image one by one from the highest bit to the lowest bit, taking the bit number of the same pixel value as a corresponding mark position value, setting the mark position value of the fixed pixel to be-1, and converting the mark position value of the non-fixed pixel into an eight-bit binary representation:
s323: counting the occurrence probability of each marking position value, constructing Huffman tree data, solving Huffman codes corresponding to each marking position value according to a rule of left 0 and right 1, and recording position diagram information; the position diagram information consists of additional information and binary representation of a Huffman coding sequence, wherein the additional information comprises binary representation of the Huffman coding length corresponding to a mark position value, the corresponding relation between the Huffman coding sequence and the mark position value and the binary representation of the total length of the Huffman coding sequence;
s324: using a predetermined encryption key e 1 Generating a pseudo-random matrix R with the same size as the first secret-carrying picture, multiplying the pseudo-random matrix R by the corresponding pixel of the first secret-carrying picture to obtain an encrypted image, and representing the pixel value of the encrypted image by binary;
wherein x is k (i, j) represents a pixel in the first encrypted picture,representing pixels in the encrypted image, k representing the number of binary bits of the pixel value, i and j representing the rows and columns of the image.
S325: selecting the first N rows and the first M columns of pixels in the encrypted image as encrypted fixed pixels, and sequentially embedding the recorded position map information into the encrypted fixed pixels from left to right from top to bottom; dividing non-fixed pixels of an encrypted image into a plurality of pixel blocks according to 2 x 2, embedding Huffman coding sequences corresponding to marking position values in four pixels in the pixel blocks into the pixel blocks, and embedding binary representation of the encrypted fixed pixels from left to right from top to bottom if the pixel blocks have an embedding space after the embedding is completed; if the embedding space is insufficient, embedding in the next pixel block until the binary representation value of all the encrypted fixed pixels is embedded;
s326: using a preset encryption key e 2 And encrypting the second secret information, and after the encrypted fixed pixels are embedded, the additional embedded space in the pixel block starts to be embedded with the encrypted second secret information, so that a second secret-carrying picture is obtained after the embedding is completed.
Preferably, the embedding the huffman coding sequence corresponding to the marked position values in four non-fixed pixels in the pixel block onto the pixel block comprises:
wherein t represents the mark position value of the non-fixed pixel, b s Representing a Huffman coding sequence corresponding to a marking position value, and when the marking position value t of a non-fixed pixel in a pixel block is less than or equal to 7, the embedding space size of the pixel in the pixel block is t+1 bits;
referring to fig. 4, S4: the sender encrypts the hash plaintext abstract based on a certificate-free public key cryptosystem to obtain a hash ciphertext abstract and signature information, encodes the hash ciphertext abstract and the signature information by using Base58 codes respectively, and adds a character string ' 0 ' between the encoded hash ciphertext abstract and the signature information to splice to obtain a signature information character string delta ';
s41: KGC generates a random number lambda, takes the random number lambda as a system private key s, multiplies the system private key s by a base point G on an elliptic curve to obtain a system public key P pub ＝s.G；
S42: the sender user identification is ID, KGC generates a random number r ID Calculating R ID ＝r ID G, wherein G represents a fixed base point on the elliptic curve, generating the partial private key D ID ＝r ID +s·H(ID,R ID ) And R is taken as ID And partial private key D ID Returning to a sender, wherein H represents a hash function;
s43: sender authentication D ID ·G＝R ID +P pub ·H(ID,R ID ) Whether or not it is true, if so, D ID Valid, otherwise invalid;
s44: sender randomly selects secret number x ID Calculate X ID ＝x ID G, public sender public key PK ID ＝(R ID ,X ID ) And calculates the private key as SK ID ＝(D ID ,x ID )；
S45: the sender will private key SK ID Encryption of session keys transmitted to a recipient by negotiation and use of public key PK ID ＝(R ID ,X ID ) Encrypting the hash plaintext abstract m to obtain a hash ciphertext abstract m';
s46: the sender selects a random number T and calculates t=t· G, v =h (m, T, R ID ,X ID ) U=t+x ID (H(ID,R ID )+v)+D ID Signature information δ= (u, v) is generated.
S5: the sender removes repeated characters in the signature information character string delta ', and splices again to obtain an intermediate signature character string delta' with different characters, matches the transaction address of the node in the blockchain network with the intermediate signature character string delta ', records indexes of successfully matched characters in the delta' and the node transaction address, and sequentially fills the indexes into extraData fields of node transactions according to the sequence of the indexes; the node transactions are packed into blocks after being verified, and when all the transactions in the blocks are verified by other nodes, the blocks are transmitted through a block chain network;
s6: the receiver acquires index information filled into the node transaction extraData field from the block, acquires the hash ciphertext abstract and signature information by decoding the index information, verifies the signature information and decrypts the hash abstract ciphertext into a hash plaintext abstract by using a private key of the sender;
preferably, the decoding the index information to obtain the hash ciphertext digest and the signature information includes
S61: the receiver checks all transaction information related to the sender from the block, and filters index information contained in extraData fields of all transaction information; recombining and restoring the signature information character string delta' according to index information contained in extraData fields of all transaction information;
in the case of recombination, since the index information includes the index of the character in δ ' and the node transaction address, the character is restored by the index information and the node transaction address included in the extraData field, and δ ' is restored by the index of the character in δ '.
S62: the receiver separates the restored signature information character string delta' into the signature information coded by the Base58 and the hash ciphertext abstract through the character string 0; decoding by using Base58 to obtain signature information and hash ciphertext abstract of the sender;
s63: the receiver uses the public key of the sender to verify the signature information, if the verification is passed; and decrypting the hash ciphertext abstract by using the private key of the sender to obtain the hash plaintext abstract.
Preferably, the receiving side verifying the signature information using the public key of the transmitting side includes:
h＝H(ID,R ID ),T'＝u·G-X ID *(h+v)R id -P pub *h,v'＝H(m,T',R ID ,X ID ) If v=v', the verification passes.
S7: the receiving party takes the hash plaintext abstract as input of an IPFS file system, and obtains a second encrypted picture embedded by the sending party;
s8: and the receiver decrypts the second encrypted picture (encrypted picture 2) by using an airspace steganography algorithm and a ciphertext domain reversible information hiding algorithm according to the encryption process of the sender on the private information to obtain the private information.
Preferably, the decrypting the second encrypted picture to obtain the secret information includes:
(1) Extracting position map information from the first N rows and the first M columns of pixels;
(2) Obtaining the position mark values of all non-fixed pixels according to the corresponding relation between the Huffman coding sequence and the position mark values and the total length of the Huffman coding sequence;
(3) Extracting pixel values of all fixed pixels; the fixed pixels are put back in the first N rows and the first M columns to obtain an image I' e ；
(4) After extracting the Huffman coding sequence and the pixel value of the fixed pixel from the non-fixed pixel, the receiver acquires the encryption key e 2 Corresponding decryption key e' 2 And uses the decryption key e' 2 Extracting a part of the second secret information to obtain an image I' e ；
(5) The receiving party obtains the encryption key e 1 Corresponding decryption key e 1 ' use of decryption key e 1 'generating a pseudo-random matrix R vs. I' e Performing an exclusive OR operation to obtain decrypted I ', wherein the first t bits or t+1 bits of each non-fixed pixel binary system in the image I' are combined with the I 'of the image non-fixed pixel binary system' e If t is not greater than 7, the image I' e The t+1 bit of (2) is opposite to the predicted value of the pixel of the image I', and each non-fixed pixel is recovered in turn according to the sequence of the preceding column and the following column; the recovery process is as follows: the non-stationary pixels p 'are sequentially found from row to column according to the stationary pixels restored by image I'. e1 Predicted value of (x, y)If the pixel position mark value t is less than or equal to 7, then the image I' e T bits before the pixel value of (1) and non-fixed pixel prediction value +.>Identical, image I' e T+1th bit of pixel value of (2) and non-fixed pixel prediction value->In contrast, image I' e The (t+2) th to (8) th bit of the pixel value of (a) and (b) the non-fixed pixel>And after the pixel values of the unfixed pixels are restored, replacing the pixel values of the decrypted image I' with the restored pixel values, and sequentially recovering each unfixed pixel from left to right from top to bottom to obtain a first secret-carrying picture, wherein the image recovery formula is as follows:
wherein,,a value representing the high t bit of the predicted pixel, for example>A value representing the t +1 bit of the predicted pixel,representation pair->And performing exclusive or inversion operation.
(6) And obtaining residual first secret information from the first secret image by using a decoding mode of a space domain steganography algorithm, and finally obtaining the secret information from the two parts of secret information.
In the method provided by the invention, the steganography analysis detection based on deep learning is effectively avoided through the countermeasure network and steganography analysis, and the utilization of the airspace steganography algorithm and the ciphertext domain reversible information hiding algorithm realizes larger embedding rate and lossless restoration of the original image and simultaneously avoids the feature detection based on probability. In addition, the number of transactions required is reduced in the blockchain network by recording index transmission in an extraData field, and the signature is encrypted by using a certificate-free public key system, so that the identity privacy of a sender is protected.
It should be noted that, it will be understood by those skilled in the art that all or part of the flow of the above method embodiments may be implemented by a computer program to instruct related software and hardware, where the program may be stored in a computer readable storage medium, and the program may include the flow of each method embodiment when executed. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random-access Memory (RandomAccess Memory, RAM), or the like.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Finally, it is noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the present invention, which is intended to be covered by the claims of the present invention.

Claims (8)

1. A blockchain covert communication method based on a generational steganography network and image double steganography, comprising:
s1: the sender utilizes a generator in the WGAN countermeasure network to generate an image sample G (z), embeds a random value into the image sample through a airspace steganography algorithm to obtain a generated picture Steg (G (z)) as an input of a discriminator, and utilizes a real picture data set to train the WGAN countermeasure network;
s2: after the WGAN countermeasure network training is completed, a sender takes a generated picture Steg (G (z)) as input of a convolution steganography analysis network, trains the convolution steganography analysis network by utilizing a real picture data set, and screens out an un-embedded image from the generated picture Steg (G (z)) as a carrier picture through the trained convolution steganography analysis network;
s3: the sender divides the secret information into two parts and sequentially embeds the secret information of the two parts into a carrier picture by using a space domain steganography algorithm and a ciphertext domain reversible information hiding algorithm to obtain a second carrier picture; compressing and storing the second encrypted picture to an IPFS file system, returning the hash plaintext abstract, and setting access control authority;
s4: the sender encrypts the hash plaintext abstract based on a certificate-free public key cryptosystem to obtain a hash ciphertext abstract and signature information, encodes the hash ciphertext abstract and the signature information by using Base58 codes respectively, and adds a character string ' 0 ' between the encoded hash ciphertext abstract and the signature information to splice to obtain a signature information character string delta ';
s5: the sender removes repeated characters in the signature information character string delta ', and splices again to obtain an intermediate signature character string delta' with different characters, matches the transaction address of the node in the blockchain network with the intermediate signature character string delta ', records indexes of successfully matched characters in the delta' and the node transaction address, and sequentially fills the indexes into extraData fields of node transactions according to the sequence of the indexes; the node transactions are packed into blocks after being verified, and when all the transactions in the blocks are verified by other nodes, the blocks are transmitted through a block chain network;
s6: the receiver acquires index information filled into the node transaction extraData field from the block, acquires the hash ciphertext abstract and signature information by decoding the index information, verifies the signature information and decrypts the hash abstract ciphertext into a hash plaintext abstract by using a private key of the sender;
s7: the receiving party takes the hash plaintext abstract as input of an IPFS file system, and obtains a second encrypted picture embedded by the sending party;
s8: and the receiver decrypts the second encrypted picture by using a space domain steganography algorithm and a ciphertext domain reversible information hiding algorithm according to the encryption process of the sender on the private information to obtain the private information.
2. The method of blockchain covert communication based on a generative steganography network and image double steganography of claim 1, wherein training the WGAN countermeasure network comprises:
calculating the distance between the data distribution of Steg (G (z)) and the data distribution of the real picture, so as to distinguish the real picture from the generated picture, and converting the solved Wasserstein distance into the following by Kantorovich-Rubinstein duality:
limiting the continuous function f w The variation width of (a) is that the gradient is w, and the value of w is [ -c, -c]The loss function converted into WGAN against the network is:
wherein,,the distribution of random noise is z-p z The lower discriminator discriminates the probability of Steg (G (z)),the distribution expressed in the real data set x is x-p r Judging the probability of the real image;
the purpose of the generator is to make the Wasserstein distance smaller, its loss function isThe purpose of the arbiter is to make the distance between the real data distribution and the generated data distribution larger, and its loss function isThe generator and the discriminator perform continuous iterative optimization of the gradient descent update parameters until the loss function converges.
3. The block chain covert communication method based on a generational steganography network and image double steganography of claim 1, wherein the carrier picture comprises:
when the SRNet network judges that the generated Steg (G (z)) is a picture without embedding, taking the Steg (G (z)) picture as a carrier picture; otherwise, continuing to train the SRNet network until Steg (G (z)) is judged to be a picture without embedding.
4. The blockchain hidden communication method based on the generation type steganography network and the image double steganography according to claim 1, wherein the step of embedding two parts of secret information into a carrier picture to obtain a second carrier picture by using a airspace steganography algorithm and a ciphertext domain reversible information hiding algorithm sequentially comprises the following steps:
s31: embedding the first secret information into the carrier picture by using an airspace steganography algorithm to obtain a first carrier picture;
s32: embedding second secret information into the first secret-carrying picture by utilizing a reversible information hiding algorithm of the ciphertext domain to obtain a second secret-carrying picture;
the embedding the second secret information into the first secret image to obtain the second secret image comprises the following steps:
s321: taking a first row and a first column of a first encrypted picture as fixed pixels, wherein the predicted value of the fixed pixels is kept unchanged; other non-fixed pixels predict pixels through a median predictor MED to obtain a predicted image;
s322: comparing the binary representation of the pixel values of the non-fixed pixels in the first encrypted picture and the predicted image one by one from the highest bit to the lowest bit, taking the bit number of the same pixel value as a corresponding mark position value, setting the mark position value of the fixed pixel as-1, and converting the mark position value of the non-fixed pixel into an eight-bit binary representation;
s323: counting the occurrence probability of each marking position value, constructing Huffman tree data, solving Huffman codes corresponding to each marking position value according to a rule of left 0 and right 1, and recording position diagram information; the position diagram information consists of additional information and binary representation of a Huffman coding sequence, wherein the additional information comprises binary representation of the Huffman coding length corresponding to a mark position value, the corresponding relation between the Huffman coding sequence and the mark position value and the binary representation of the total length of the Huffman coding sequence;
s324: using a predetermined encryption key e 1 Generating a pseudo-random matrix R with the same size as the first secret-carrying picture, multiplying the pseudo-random matrix R by the corresponding pixel of the first secret-carrying picture to obtain an encrypted image, and representing the pixel value of the encrypted image by binary;
s325: selecting the first N rows and the first M columns of pixels in the encrypted image as encrypted fixed pixels, and sequentially embedding the recorded position map information into the encrypted fixed pixels from left to right from top to bottom; dividing non-fixed pixels of an encrypted image into a plurality of pixel blocks according to 2 x 2, embedding Huffman coding sequences corresponding to marking position values in four pixels in the pixel blocks into the pixel blocks, and embedding binary representation of the encrypted fixed pixels from left to right from top to bottom if the pixel blocks have an embedding space after the embedding is completed; if the embedding space is insufficient, embedding in the next pixel block until the binary representation value of all the encrypted fixed pixels is embedded;
s326: using a preset encryption key e 2 And encrypting the second secret information, and after the encrypted fixed pixels are embedded, the additional embedded space in the pixel block starts to be embedded with the encrypted second secret information, so that a second secret-carrying picture is obtained after the embedding is completed.
5. The method for block chain concealment communication based on a generative steganography network and image double steganography according to claim 4, wherein said embedding huffman coding sequences corresponding to marker position values in four non-stationary pixels in a pixel block onto a pixel block comprises:
wherein t represents the mark position value of the non-fixed pixel, b s And representing the Huffman coding sequence corresponding to the mark position value, and when the mark position value t of the non-fixed pixel in the pixel block is less than or equal to 7, the embedding space size of the pixel in the pixel block is t+1 bits.
6. The blockchain covert communication method based on a generational steganography network and image double steganography of claim 5, wherein encrypting the hashed plaintext digest comprises:
s41: KGC generates a random number lambda, takes the random number lambda as a system private key s, multiplies the system private key s by a base point G on an elliptic curve to obtain a system public key P pub ＝s.G；
S42: the sender user identification is ID, KGC generates a random number r ID Calculating R ID ＝r ID G, wherein G represents a fixed base point on the elliptic curve, generating the partial private key D ID ＝r ID +s·H(ID,R ID ) And R is taken as ID And partial private key D ID Returning to a sender, wherein H represents a hash function;
s43: sender authentication D ID ·G＝R ID +P pub ·H(ID,R ID ) Whether or not it is true, if so, D ID Valid, otherwise invalid;
s44: sender randomly selects secret number x ID Calculate X ID ＝x ID G, public sender public key PK ID ＝(R ID ,X ID ) And calculates the private key as SK ID ＝(D ID ,x ID )；
S45: the sender will private key SK ID Encryption of session keys transmitted to a recipient by negotiation and use of public key PK ID ＝(R ID ,X ID ) Encrypting the hash plaintext abstract m to obtain a hash ciphertext abstract m';
s46: the sender selects a random number T and calculates t=t· G, v =h (m, T, R ID ,X ID ) U=t+x ID (H(ID,R ID )+v)+D ID Signature information δ= (u, v) is generated.
7. The method for generating a block chain hidden communication based on a hidden network and an image dual hidden method of claim 6, wherein decoding the index information to obtain the hash ciphertext digest and the signature information comprises:
s61: the receiver checks all transaction information related to the sender from the block, and filters index information contained in extraData fields of all transaction information; recombining and restoring the signature information character string delta' according to index information contained in extraData fields of all transaction information;
s62: the receiver separates the restored signature information character string delta' into the signature information coded by the Base58 and the hash ciphertext abstract through the character string 0; decoding by using Base58 to obtain signature information and hash ciphertext abstract of the sender;
s63: the receiver uses the public key of the sender to verify the signature information, if the verification is passed; and decrypting the hash ciphertext abstract by using the private key of the sender to obtain the hash plaintext abstract.
8. The method of block chain covert communication based on a generational steganographic network and image double steganographic of claim 7, wherein the receiving party verifying the signature information using the public key of the transmitting party comprises:
h＝H(ID,R ID ),T'＝u·G-X ID *(h+v)-R id -P pub *h,v'＝H(m,T',R ID ,X ID ) If v=v', the verification passes.
CN202310561034.7A 2023-05-18 2023-05-18 Block chain hidden communication method based on generation type hidden network and image double hidden Pending CN116527278A (en)

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117278986A (en) * 2023-11-23 2023-12-22 浙江小遛信息科技有限公司 Data processing method and data processing equipment for sharing travel
CN117278986B (en) * 2023-11-23 2024-03-15 浙江小遛信息科技有限公司 Data processing method and data processing equipment for sharing travel

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