Social information collection method and system based on image robust steganography

Abstract

The application discloses a social surface information collection method and system based on image robust steganography. The method comprises the following steps: collecting an original image from a collection end; embedding secret information in the original image to obtain a stego image; transmitting the stego image from the collection end to a verification end; extracting the secret information from the stego image; and judging whether the original image corresponding to the stego image is an image collected by the specified collection end according to the extracted secret information. The technical scheme can prevent an image provider from forging an image and improve the authenticity of the collected image.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of information security, and particularly relates to a social surface information collection method and system based on image robust steganography. BACKGROUND

[0002] When information needs to be collected from the social surface, using a digital image is a convenient means, which can facilitate the recording of on-site information at a certain time. The organizers hope that these digital images are real images collected on site, and carry the time and location of their collection, which can reflect the specific time and location of the event. WeChat, as a public network platform popular among the public, is a social platform commonly used by organizers and providers, which provides convenience for communication between organizers and providers, but at the same time there are some problems to be overcome: (1) how do organizers determine that the received image is a real image collected on site, rather than a false image made by the provider for some reason; (2) the image data may be modified during image transmission; (3) the collection time and location information of the image may be lost during image transmission.

[0003] Based on this, the present application provides an image collection scheme, which is generated from the present case. SUMMARY

[0004] The purpose of the present application is to provide a social surface information collection method and system based on image robust steganography, which can prevent image providers from forging images and improve the authenticity of collected images.

[0005] In order to achieve the above purpose, the solution of the present application is:

[0006] A social surface information collection method based on image robust steganography, comprising the following steps:

[0007] Collecting an original image from a collection end;

[0008] Embedding secret information in the original image to obtain a stego image;

[0009] The stego image is transmitted from the collection end to a verification end;

[0010] Extracting secret information from the stego image;

[0011] Determining whether the original image corresponding to the stego image is an image collected by the specified collection end according to the extracted secret information.

[0012] The secret information includes the collection time, location and identification information of the collection system of the original image, and the identification information of the collection system is shared by the collection end and the verification end in advance;

[0013] Extracting secret information from the stego image includes extracting the collection time, location and identification information of the collection system of the original image from the stego image.

[0014] Determining whether the original image corresponding to the secret image is an image collected by the designated collection end based on the extracted secret information includes: first determining the correctness based on the extracted identification information; after verification, determining that the original image corresponding to the secret image is an image collected by the designated collection end; and saving the collection time and location information of the secret image and its original image.

[0015] Among them, the secret information is embedded in the original image to obtain the secret image, including:

[0016] Convert the secret information msg into binary data M={m1,m2,…,m L}, where m i ∈{0,1}, i=1,2,…,L, L is the length of the binary data M;

[0017] Taking the original image as a carrier image, converting it into N non-overlapping sub-blocks, where N ≥ L;

[0018] The singular value decomposition transformation method is used to embed the binary data M into L sub-blocks, and the encrypted image is obtained by conversion.

[0019] Among them, the secret information msg is converted into binary data M, including,

[0020] Get the length of the secret message msg: len = strlen(msg), where strlen(·) is a function that calculates the length of a string in bytes.

[0021] Perform RS error correction coding on len and msg respectively and concatenate them together;

[0022] Convert the concatenated string into binary data M={m1,m2,…,m L}, where m i ∈{0,1}, i=1,2,…,L, L is the length of the binary data M.

[0023] The original image is used as the carrier image, and N non-overlapping sub-blocks are obtained by conversion, including:

[0024] The original image is taken as the carrier image, which is in JPEG format, with the width and height marked as W and H respectively;

[0025] Read the RGB data of the carrier image and obtain its Y component data;

[0026] Perform interval mapping on the Y component data so that its value is mapped from the original [0,255] to [a,b], where a and b are positive integers, a∈[10,20], b∈[210,245];

[0027] Y data is divided into N non-overlapping n x n sub-blocks, wherein, denotes rounding down, n≥8 and is a power of 2.

[0028] wherein the binary data M is embedded in L sub-blocks by using a singular value decomposition transformation method to obtain a stego image, comprising,

[0029] The first L sub-blocks in the N sub-blocks are selected, and discrete wavelet transform is performed on the i-th sub-block to obtain four sub-bands of LL i , LH i , HL i and HH i , wherein i = 1, 2, …, L;

[0030] The singular value decomposition transform is performed on the LL i sub-band to obtain the maximum singular value λ i,0 ;

[0031] The maximum singular value λ i,0 of the i-th sub-block is modified to embed information m i , m i ∈{0, 1} is the information embedded in the i-th sub-block;

[0032] After embedding information in the i-th sub-block, inverse singular value decomposition is performed to obtain the modified sub-band LL' i , and LH i , HL i and HH i are obtained by inverse discrete wavelet transform to obtain the i-th sub-block after embedding information.

[0033] The Y data after embedding information and the corresponding Cr and Cb data are converted into RGB data, and a JPEG image is generated, which is the stego image.

[0034] Further comprising: after judging that the original image corresponding to the stego image is an image collected by a specified collection end, saving the collection time and location information of the stego image and the original image.

[0035] A social surface information collection system based on image robust steganography, comprising,

[0036] An image collection module located at a collection end and configured to collect an original image;

[0037] An information steganography module located at the collection end and configured to embed secret information in the original image to obtain a stego image;

[0038] An image extraction module located at a verification end and configured to extract secret information from the stego image; and

[0039] An information verification module is located at the verification end and is configured to determine whether the original image corresponding to the steganographic image is an image collected by the designated collection end according to the extracted secret information.

[0040] The steganographic image is transmitted to the verification end by the collection end through wireless or wired communication.

[0041] After the above scheme is adopted, the present application has the following beneficial effects:

[0042] (1) The method for binding the time and position information of image collection with the image can avoid being modified artificially and can also avoid being lost during image transmission.

[0043] (2) The interval mapping method for processing data of the carrier image proposed by the present application can ensure that the embedded information can be correctly extracted after the steganographic image is transmitted through WeChat.

[0044] (3) The system provided by the present application can prevent the provider from forging images through P images, avoid the provider from cheating, and improve the authenticity of the collected images. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 is a principle flowchart of embedding secret information in the present application;

[0046] Figure 2 is a principle flowchart of extracting secret information in the present application;

[0047] Figure 3 is a structure diagram of the overall scheme of the present application. DETAILED DESCRIPTION

[0048] The technical scheme and beneficial effects of the present application will be described in detail below with reference to the accompanying drawings.

[0049] The present application provides a social surface information collection system based on image robust steganography, which comprises an image collection module, an information steganography module, an image extraction module and an information verification module, wherein the image collection module is configured to collect an original image and send the collected original image to the information steganography module; the information steganography module embeds secret information in the original image to obtain a steganographic image and sends the steganographic image to the image extraction module; the image extraction module extracts information from the received steganographic image to extract secret information; and the information verification module determines whether the image is the original image according to the extracted secret information.

[0050] In specific practice, the image collection module and the information steganography module can be set as one body (collection end) and operated by the provider, the image extraction module and the information verification module are set at the organization side (verification end), the collection end and the verification end transmit images through wireless or wired communication, for example, instant messaging, and the organization side uses the verification end to verify the authenticity of the images.

[0051] The secret information includes the acquisition time, position and identification information of the acquisition system of the original image, and the acquisition end and the verification end share the identification information in advance; the information steganography module embeds the secret information including the acquisition time, position and identification information in the original image to obtain a stego image, the image extraction module extracts the acquisition time, position and identification information of the acquisition system of the original image from the stego image, and the information verification module first judges the correctness of the identification information, and after verification, judges that the original image corresponding to the received stego image is the image collected by the specified acquisition end, and simultaneously saves the acquisition time and position information of the stego image and the original image.

[0052] The application further provides a social surface information collection method based on image robust steganography, including the following steps:

[0053] Collecting an original image;

[0054] Embedding secret information in the original image to obtain a stego image;

[0055] Extracting secret information from the stego image;

[0056] Judging whether the original image corresponding to the stego image is the image collected by the specified acquisition end according to the extracted secret information.

[0057] The secret information includes the acquisition time, position and identification information of the acquisition system of the original image; the secret information is embedded in the original image to obtain a stego image;

[0058] The secret information is extracted from the stego image, including extracting the acquisition time, position and identification information of the acquisition system of the original image from the stego image;

[0059] Judging whether the original image corresponding to the stego image is the image collected by the specified acquisition end according to the extracted secret information, including first judging the correctness according to the extracted identification information, and after verification, judging that the original image corresponding to the stego image is the image collected by the specified acquisition end, and simultaneously saving the acquisition time and position information of the stego image and the original image.

[0060] A specific embodiment of embedding secret information in an original image to obtain a stego image will be provided below to describe the technical scheme of the application in detail.

[0061] The embodiment proposes an image robust steganography method based on DWT (discrete wavelet transform) and SVD, which cooperates with Figure 1 , including the following steps:

[0062] (1) Secret information preprocessing

[0063] 1) Input secret information msg.

[0064] 2) Obtain the length of secret information len = strlen(msg), where strlen(·) is a function for obtaining the length of a string in bytes.

[0065] 3) Perform RS error correction coding on len and msg respectively, and splice them together.

[0066] 4) Convert the spliced string into binary data M = {m1, m2, …, mL}, where mi∈{0, 1}, i = 1, 2, …, L, L is the length of binary data M. L i

[0067] (2) Carrier image preprocessing

[0068] 1) Take the original image collected as the carrier image, which is in JPEG format, and the width and height are marked as W and H respectively.

[0069] 2) Read the RGB data of the carrier image and obtain its Y component data, which is calculated as follows:

[0070] Y = 0.299R + 0.587G + 0.114B

[0071] Cb = -0.1687R - 0.3313G + 0.5B + 128

[0072] Cr = 0.5R - 0.418G - 0.0813B + 128

[0073] 3) Perform interval mapping on the Y component data, so that its value is mapped from the original [0, 255] to [a, b], where a and b are positive integers, a ∈ [10, 20], and b ∈ [210, 245]. Assuming that the Y data before and after mapping are y and y' respectively, the linear mapping relationship is as follows:

[0074]

[0075] 4) Divide the Y data into N non-overlapping sub-blocks of n x n, where , n ≥ 8 and is a power of 2, and only when N ≥ L can the embedding be successful, L is the length of the binary data to be embedded.

[0076] (3) Information embedding

[0077] 1) Select the first L sub-blocks in the N sub-blocks to embed information.

[0078] 2) Perform discrete wavelet transform (DWT) on the ith sub-block to obtain LL i , LH​​i , HL i , and HH i , where i = 1, 2, …, L.

[0079] 3) Perform subband singular value decomposition (SVD) transform on LL i to obtain the maximum singular value λ i,0 .

[0080] 4) Modify the maximum singular value λ i,0 of the i-th subblock by a quantization modulation method to embed information m i . Assuming that the maximum singular value of the i-th subblock after embedding information is λ' i,0 , then:

[0081]

[0082] where i = 1, 2, …, L, m i ∈ {0, 1} is the information embedded in the i-th subblock, and Δ is the quantization step, an integer.

[0083] 5) After embedding information in the i-th subblock, perform inverse singular value decomposition to obtain the modified subband LL' i , and then perform inverse discrete wavelet transform on LH i , HL i , and HH i to obtain the i-th subblock after embedding information.

[0084] 6) Convert the Y data after embedding information and the corresponding Cr and Cb data into RGB data, and generate a JPEG image, which is the stego image.

[0085] R = Y' + 1.402(Cr - 128)

[0086] G = Y' - 0.34414(Cb - 128) - 0.71414(Cr - 128)

[0087] B = Y' + 1.772(Cb - 128)

[0088] where Y' is the Y component data after embedding information.

[0089] In conjunction Figure 2 , at the verification end, information extraction is the inverse process of information embedding, and the formula for extracting information using quantization modulation is as follows:

[0090]

[0091] where i = 1, 2, …, L, m' i ∈ {0, 1} is the information embedded in the i-th subblock of the stego image; λ'i,0 is the maximum singular value of the i-th sub-block; and Δ is the quantization step size adopted by the information embedding.

[0092] In use, as Figure 3 , the provider carries the acquisition terminal to acquire the original image, and the original image is processed by information embedding to obtain a steganographic image, which can be transmitted to the organization party through various communication modes, such as WeChat transmission, and then verified by the verification terminal. If the verification is passed, the image and the corresponding acquisition time and location information can be saved.

[0093] Those skilled in the art will appreciate that embodiments of the application can be supplied as a method, a system, or a computer program product. Accordingly, the application can be embodied in the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the application can be embodied in the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk memory, CD-ROMs, optical memory, etc.) having computer usable program code embodied thereon. The solutions in the embodiments of the application can be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0094] The application is described with reference to flowcharts and / or block diagrams of the method, device (system), and computer program product according to the embodiments of the application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus that carries out the functions specified in one or more flows and / or blocks.

[0095] These computer program instructions can also be stored in a computer-readable memory that can direct the computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including instruction apparatus, which implements the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus that carries out the functions specified in one or more flows and / or blocks.

[0096] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are performed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide a function for implementing the functions specified in the flowcharts and / or block diagrams.Figure 1 one or more processes and / or functions specified in one or more blocks Figure 1 one or more blocks or steps of the functions specified in one or more blocks.

[0097] While the preferred embodiments of the application have been described, additional variations and modifications can be made to the preferred embodiments by those of skill in the art once they have the benefit of the present disclosure. Therefore, the appended claims are intended to encompass within their scope all possible variations and modifications of the preferred embodiments. 1

[0098] It is apparent that a person skilled in the art can make a variety of changes and modifications to the application without departing from the spirit and scope thereof. Thus, if these modifications and changes fall within the scope of the claims and their equivalents, it is intended to include them in the application.

Claims

1. A social information collection method based on image robust steganography, characterized by The steps include: Collect original images from the acquisition end; Embed the secret information into the original image to obtain the secret image; The secret image is transmitted from the collection end to the verification end; Extract secret information from the contained secret image; Determining whether the original image corresponding to the secret image is an image captured by a designated capture terminal according to the extracted secret information; The method of embedding secret information into the original image to obtain a secret image includes: Convert the secret information msg into binary data M={m1,m2,…,m L }, where m i ∈{0,1}, i=1,2,…,L, L is the length of the binary data M; Taking the original image as a carrier image, converting it into N non-overlapping sub-blocks, where N ≥ L; The binary data M is embedded into L sub-blocks by using the singular value decomposition transformation method, and the encrypted image is obtained by conversion; Convert the secret message msg into binary data M, including, Get the length of the secret message msg: len = strlen(msg), where strlen(·) is a function that calculates the length of a string in bytes. Perform RS error correction coding on len and msg respectively and concatenate them together; Convert the concatenated string into binary data M={m1,m2,…,m L }; Using the original image as the carrier image, N non-overlapping sub-blocks are obtained by conversion, including: The original image is taken as the carrier image, which is in JPEG format, with the width and height marked as W and H respectively; Read the RGB data of the carrier image and obtain its Y component data; Perform interval mapping on the Y component data so that its value is mapped from the original [0,255] to [a,b], where a and b are positive integers, a∈[10,20], b∈[210,245]; The Y component data is divided into N n×n non-overlapping sub-blocks, where Indicates floor operation, where n ≥ 8 and is a power of 2.

2. The method according to claim 1, wherein: The secret information includes the acquisition time and location of the original image and the identification information of the acquisition system, and the identification information of the acquisition system is shared in advance by the acquisition end and the verification end; Extracting secret information from the self-contained secret image, including extracting the acquisition time, location and identification information of the acquisition system of the original image from the self-contained secret image; Determining whether the original image corresponding to the secret image is an image collected by the designated collection end based on the extracted secret information includes: first determining the correctness based on the extracted identification information; after verification, determining that the original image corresponding to the secret image is an image collected by the designated collection end; and saving the collection time and location information of the secret image and its original image.

3. The method according to claim 1, wherein: The singular value decomposition transformation method is used to embed the binary data M into L sub-blocks, and the converted encrypted image is obtained, including: Select the first L sub-blocks from the N sub-blocks, perform discrete wavelet transform on the i-th sub-block, and obtain LL i , LH i HL i and HH i Four sub-bands, where i = 1, 2, ..., L; To LL i The subband is transformed by singular value decomposition to obtain the maximum singular value λ i,0 ; Modify the maximum singular value λ of the i-th sub-block i,0 To embed information m i , m i ∈{0,1} is the information embedded in the i-th sub-block; After embedding information in the i-th sub-block, the inverse singular value decomposition transform is performed to obtain the modified sub-band LL' i , and then with LH i HL i and HH i Through the inverse discrete wavelet transform, the i-th sub-block after embedding information is obtained; The Y component data after embedding the information and the corresponding Cr and Cb data are converted into RGB data, and a JPEG image is generated, which is the encrypted image.

4. The method according to claim 1, wherein: The method further includes, after determining that the original image corresponding to the secret image is the image acquired by the designated acquisition terminal, saving the acquisition time and location information of the secret image and its original image.

5. A social information collection system based on image robust steganography, characterized by: include, The image acquisition module is located at the acquisition end and is used to acquire the original image; The information steganography module is located at the acquisition end and is used to embed secret information into the original image to obtain a secret image; An image extraction module, located at the verification end, is used to extract secret information from the secret image; and An information verification module, located at the verification end, is used to determine whether the original image corresponding to the secret image is the image captured by the designated acquisition end based on the extracted secret information; The information steganography module is further used to: Convert the secret information msg into binary data M={m1,m2,…,m L }, where m i ∈{0,1}, i=1,2,…,L, L is the length of the binary data M; Taking the original image as a carrier image, converting it into N non-overlapping sub-blocks, where N ≥ L; The binary data M is embedded into L sub-blocks by using the singular value decomposition transformation method, and the encrypted image is obtained by conversion; Convert the secret message msg into binary data M, including, Get the length of the secret message msg: len = strlen(msg), where strlen(·) is a function that calculates the length of a string in bytes. Perform RS error correction coding on len and msg respectively and concatenate them together; Convert the concatenated string into binary data M={m1,m2,…,m L }; Using the original image as the carrier image, N non-overlapping sub-blocks are obtained by conversion, including: The original image is taken as the carrier image, which is in JPEG format, with the width and height marked as W and H respectively; Read the RGB data of the carrier image and obtain its Y component data; Perform interval mapping on the Y component data so that its value is mapped from the original [0,255] to [a,b], where a and b are positive integers, a∈[10,20], b∈[210,245]; The Y component data is divided into N n×n non-overlapping sub-blocks, where Indicates floor operation, where n ≥ 8 and is a power of 2.

6. The system according to claim 5, wherein: The encrypted image is transmitted from the collection end to the verification end through wireless or wired communication.

Images