Data transmission method and related equipment

Abstract

The invention provides a data transmission method and related equipment, and relates to the technical field of Internet of Things data communication. The method comprises the steps that a server receives a sampling data ciphertext and a chaos parameter ciphertext sent by a sensor; decrypting the chaos parameter ciphertext by using a private key to obtain a chaos parameter, and generating a measurement chaos matrix according to the chaos parameter; decrypting the sampling data ciphertext based on the measurement chaos matrix to obtain a measurement result; and performing compressed sensing signal recovery on a measurement result through the measurement chaos matrix to obtain an initial signal. According to the compressed sensing mode disclosed by the invention, data acquisition and compressed encryption can be realized, and encryption and decryption operations are executed based on the measurement chaos matrix, so that the encryption and decryption effects of signals can be further improved, and the security of data transmission is improved.

Description

Background Art

[0002] Based on the Internet, the Internet of Things realizes intelligent connections between things and things, and between things and people, thus providing unprecedented efficiency, convenience and automation. Compared with the progress of communication technology, the progress of energy technology is relatively slow. For scenarios where long-term stable energy supply cannot be guaranteed, energy becomes a key factor restricting sensor nodes in the Internet of Things, among which signal transmission accounts for most of the energy consumption of the Internet of Things.

[0003] In related technologies, compression is mainly used to reduce the amount of data transmission. However, the existing compression algorithm is highly complex and computationally intensive at the compression end, but simple at the decoding end, and the energy consumption of the sensor remains high. On the other hand, the information collection and transmission of the Internet of Things is mostly open, which is prone to information leakage and has low security.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] The present disclosure provides a data transmission method and related equipment, which at least to a certain extent overcome the problems of high sensor energy consumption and low data transmission security in the existing data transmission methods.

[0006] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by the practice of the present disclosure.

[0007] According to one aspect of the present disclosure, a data transmission method is provided, which is applied to a server, and the method includes: receiving sampling data ciphertext and chaos parameter ciphertext sent by a sensor; decrypting the chaos parameter ciphertext using a private key to obtain chaos parameters, and generating a measurement chaos matrix according to the chaos parameters; decrypting the sampling data ciphertext based on the measurement chaos matrix to obtain a measurement result; and performing compressed sensing signal recovery on the measurement result through the measurement chaos matrix to obtain an initial signal.

[0008] In one embodiment of the present disclosure, generating a measurement chaotic matrix according to the chaotic parameters includes: generating a chaotic sequence according to the chaotic parameters; sampling the chaotic sequence using a preset step size to obtain the measurement chaotic matrix, and the measurement chaotic matrix satisfies a restricted equidistance condition.

[0009] In one embodiment of the present disclosure, before performing compressed sensing signal recovery on the measurement result through the measurement chaotic matrix to obtain the initial signal, the method also includes: when the initial signal is a one-dimensional signal, extracting the first column of the measurement chaotic matrix to obtain a one-dimensional measurement chaotic matrix, and the dimension of the measurement result remains unchanged; when the initial signal is a two-dimensional signal, merging the measurement chaotic matrix into a one-dimensional series by column to obtain a one-dimensional measurement chaotic matrix, and merging the measurement results into one-dimensional data by column to obtain a one-dimensional measurement result.

[0010] In one embodiment of the present disclosure, the compressed sensing signal recovery is performed on the measurement result through the measurement chaotic matrix to obtain the initial signal, including: using an iterative reweighted least squares algorithm to perform compressed sensing signal recovery, wherein when the initial signal is a one-dimensional signal, the recovery is performed directly, and when the initial signal is a two-dimensional signal, the signal recovery is performed column by column.

[0011] In one embodiment of the present disclosure, the decryption processing includes a reverse diffusion operation; wherein, the decryption processing of the sampled data ciphertext to obtain a measurement result includes: performing the reverse diffusion operation on the sampled data ciphertext through the measurement chaotic matrix to obtain reverse diffusion information, wherein the reverse diffusion operation is a bidirectional XOR reverse diffusion operation.

[0012] In one embodiment of the present disclosure, the decryption process also includes an inverse scrambling operation; wherein, the decryption process of the sampled data ciphertext to obtain a measurement result includes: using the same method as the memory side to generate a scrambling index according to the measurement chaotic matrix; and performing an inverse scrambling operation on the reverse diffusion information according to the scrambling index to obtain the measurement result.

[0013] In one embodiment of the present disclosure, before receiving the sampled data ciphertext and the chaotic parameter ciphertext sent by the sensor, the method further includes: using an asymmetric encryption algorithm to generate a public-private key pair; and sending or presetting the public key in the sensor.

[0014] According to another aspect of the present disclosure, a data transmission method is provided, which is applied to a sensor end, and the method includes: randomly generating chaotic parameters, and encrypting the chaotic parameters using a public key to obtain a chaotic parameter ciphertext; generating a measurement chaotic matrix according to the chaotic parameters; performing compressed sensing sampling on an initial signal based on the measurement chaotic matrix to obtain a measurement result; encrypting the measurement result based on the measurement chaotic matrix to obtain a sampling data ciphertext; and sending the chaotic parameter ciphertext and the sampling data ciphertext to a server.

[0015] In one embodiment of the present disclosure, generating a measurement chaotic matrix according to the chaotic parameters includes: using the chaotic parameters to generate a chaotic sequence; decimating and sampling the chaotic sequence using a preset step size to obtain the measurement chaotic matrix, and the measurement chaotic matrix satisfies a restricted equidistance condition.

[0016] In one embodiment of the present disclosure, the compressed sensing sampling of the initial signal based on the measurement chaotic matrix to obtain the measurement result includes: when the initial signal is a one-dimensional signal, extracting the first column of the measurement chaotic matrix to obtain a one-dimensional measurement chaotic matrix, and the dimension of the measurement result remains unchanged; when the initial signal is a two-dimensional signal, merging the measurement chaotic matrix into one-dimensional data by columns to obtain a one-dimensional measurement chaotic matrix, and merging the measurement results into one-dimensional data by columns to obtain a one-dimensional measurement result.

[0017] In one embodiment of the present disclosure, the encryption processing includes a scrambling operation; wherein, the encryption processing of the measurement result based on the measurement chaotic matrix to obtain the sampled data ciphertext includes: using the measurement chaotic matrix to generate a scrambling index, and performing the scrambling operation on the measurement result according to the scrambling index to generate a scrambled signal.

[0018] In one embodiment of the present disclosure, the encryption processing also includes a diffusion operation; wherein, the encryption processing of the measurement result based on the measurement chaotic matrix to obtain the sampled data ciphertext also includes: performing the diffusion operation on the scrambled signal based on the measurement chaotic matrix to obtain the sampled data ciphertext, wherein the diffusion operation includes a bidirectional XOR diffusion operation.

[0019] According to another aspect of the present disclosure, a data transmission device is provided, which is applied to a server, and the device includes: a data receiving module, which is used to receive sampling data ciphertext and chaos parameter ciphertext sent by a sensor; a first generating module, which is used to decrypt the chaos parameter ciphertext using a private key to obtain chaos parameters, and generate a measurement chaos matrix according to the chaos parameters; a data decryption module, which is used to decrypt the sampling data ciphertext to obtain a measurement result; and a signal recovery module, which is used to perform compressed sensing signal recovery on the measurement result through the measurement chaos matrix to obtain an initial signal.

[0020] According to another aspect of the present disclosure, a data transmission device is provided, which is applied to a sensor, and the device includes: a parameter encryption module, which is used to randomly generate chaotic parameters, and use public key encryption to obtain chaotic parameter ciphertext; a second generation module, which is used to generate a measurement chaotic matrix according to the chaotic parameters; a signal sampling module, which is used to perform compressed sensing sampling on an initial signal based on the measurement chaotic matrix to obtain a measurement result; a data encryption module, which is used to encrypt the measurement result based on the measurement chaotic matrix to obtain a sampled data ciphertext; and a data sending module, which is used to send the chaotic parameter ciphertext and the sampled data ciphertext to a server.

[0021] According to another aspect of the present disclosure, a data transmission system is provided, including a server and a sensor, wherein: the server is used to receive sampling data ciphertext and chaos parameter ciphertext sent by the sensor; the chaos parameter ciphertext is decrypted using a private key to obtain chaos parameters, and a measurement chaos matrix is ​​generated based on the chaos parameters; the sampling data ciphertext is decrypted to obtain a measurement result; the measurement result is compressed sensing signal recovered by using the measurement chaos matrix to obtain an initial signal; the sensor is used to randomly generate chaos parameters, and encrypt the chaos parameters using a public key to obtain chaos parameter ciphertext; a measurement chaos matrix is ​​generated based on the chaos parameters; the initial signal is compressed sensing sampled based on the measurement chaos matrix to obtain a measurement result; the measurement result is encrypted based on the measurement chaos matrix to obtain sampling data ciphertext; the chaos parameter ciphertext and the sampling data ciphertext are sent to the server.

[0022] According to another aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the above-mentioned data transmission method by executing the executable instructions.

[0023] According to another aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned data transmission method is implemented.

[0024] According to another aspect of the present disclosure, a computer program product is provided, including a computer program or computer instructions, wherein the computer program or the computer instructions are loaded and executed by a processor so that a computer implements any of the above-mentioned data transmission methods.

[0025] In the embodiments of the present disclosure, the sampling data ciphertext and the chaos parameter ciphertext sent by the sensor are received; the chaos parameter ciphertext is decrypted using a private key to obtain the chaos parameter, and a measurement chaos matrix is ​​generated according to the chaos parameter; based on the measurement chaos matrix, the sampling data ciphertext is decrypted to obtain the measurement result; the measurement result is subjected to compressed sensing signal recovery by measuring the chaos matrix to obtain the initial signal. On the one hand, the present disclosure generates a measurement chaos matrix by using the chaos parameter, and uses the measurement chaos matrix to perform encryption operation after the data is measured, which can reduce the parameter generation overhead, improve the signal encryption effect, and provide better security. On the other hand, the measurement result is encrypted and decrypted using a dynamic measurement chaos matrix, which can effectively improve the security of data transmission and resist plaintext attacks.

[0026] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0028] Figure 1 A schematic diagram of a communication system architecture provided by an embodiment of the present disclosure is shown.

[0029] Figure 2 A flow chart of a data transmission method provided by an embodiment of the present disclosure is shown.

[0030] Figure 3 A flow chart of a measurement chaos matrix generation method provided by an embodiment of the present disclosure is shown.

[0031] Figure 4 A flow chart of another data transmission method provided by an embodiment of the present disclosure is shown.

[0032] Figure 5 A flow chart of another data transmission method provided by an embodiment of the present disclosure is shown.

[0033] Figure 6 A flow chart of a data transmission method applied to a sensor provided by an embodiment of the present disclosure is shown.

[0034] Figure 7 A flow chart of another data transmission method applied to a sensor provided by an embodiment of the present disclosure is shown.

[0035] Figure 8An example flow chart of a data transmission method provided by an embodiment of the present disclosure is shown.

[0036] Fig. 9 A schematic diagram of the structure of a data transmission device provided by an embodiment of the present disclosure is shown.

[0037] Fig.10 A schematic diagram of the structure of another data transmission device provided by an embodiment of the present disclosure is shown.

[0038] Fig.11 A structural block diagram of an electronic device provided by an embodiment of the present disclosure is shown.

[0039] Fig.12 A schematic diagram of a computer-readable storage medium provided in an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0040] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the disclosure will be more comprehensive and complete and to fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0041] In addition, the accompanying drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0042] The specific implementation of the embodiment of the present disclosure is described in detail below with reference to the accompanying drawings.

[0043] Figure 1 FIG. 1 is a schematic diagram showing an exemplary communication system architecture that can be applied to the data transmission method of the embodiment of the present disclosure. Figure 1 As shown, the system architecture may include a terminal device 101, a network 102 and a server 103. The network 102 is used to provide a medium for a communication link between the terminal device 101 and the server 103, and may be a wired network or a wireless network.

[0044] Optionally, the wireless network or wired network described above uses standard communication technology and / or protocols. The network is typically the Internet, but may also be any network, including but not limited to a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a mobile, wired or wireless network, a private network or any combination of a virtual private network). In some embodiments, technologies and / or formats including Hyper Text Mark-up Language (HTML), Extensible Markup Language (XML), etc. are used to represent data exchanged over the network. In addition, conventional encryption technologies such as Secure Socket Layer (SSL), Transport Layer Security (TLS), Virtual Private Network (VPN), Internet Protocol Security (IPSec), etc. may be used to encrypt all or some links. In other embodiments, customized and / or dedicated data communication technologies may also be used to replace or supplement the above data communication technologies.

[0045] The terminal device 101 can be various electronic devices, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, smart speakers, smart watches, wearable devices, augmented reality devices, virtual reality devices, etc.

[0046] Optionally, the client of the application installed in different terminal devices 101 is the same, or the client of the same type of application based on different operating systems. Based on the different terminal platforms, the specific form of the client of the application can also be different, for example, the application client can be a mobile client, a PC client, etc.

[0047] The server 103 may be a server that provides various services, such as a background management server that provides support for the device operated by the user using the terminal device 101. The background management server may analyze and process the received request and other data, and feed back the processing results to the terminal device.

[0048] Optionally, server 103 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0049] Those skilled in the art will know that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration, and any number of terminal devices, networks and servers may be provided according to actual needs, and the embodiments of the present disclosure do not limit this.

[0050] In the present disclosure, a technology for data compression and encryption transmission of the Internet of Things is involved. The terminal device 101 can be various sensors, and the sensor is used to complete the compressed sensing sampling of the signal and encrypt the sampling result, and transmit the ciphertext of the sampling result to the server. The server completes the decryption of the signal and uses the compressed sensing recovery to obtain the recovery signal.

[0051] Sensors can include environmental monitoring, motion and position control, safety and health detection, and other special types of sensors. Environmental monitoring sensors can include temperature sensors, humidity sensors, gas sensors, light sensors, etc.; motion and position control sensors can include motion sensors, proximity sensors, acceleration sensors, gyroscopes, etc.; safety and health monitoring sensors can include pressure sensors, smoke sensors, biosensors, etc.; other special sensors can include noise sensors, image sensors, distance sensors, etc.

[0052] The Internet of Things mainly uses compression to reduce the amount of data transmission during data transmission, thereby meeting the transmission needs of the Internet of Things and reducing the demand for energy for transmission. However, in practical applications, the compression method has the following defects: on the one hand, the compression algorithm is highly complex and computationally intensive at the compression end (i.e., the sensor end), while the decoding end (i.e., the server end) is relatively computationally simple. The above method is inconsistent with the hardware resource allocation scheme with low actual sensor node configuration and high processing node configuration, and is not suitable for implementing the compression algorithm on sensors with simple configurations. At the same time, the compression algorithm counts and removes redundant features in the signal after signal acquisition is completed, wasting sampling resources. On the other hand, the information collection and transmission process of the Internet of Things is mostly in open mode. In the process of data transmission, the above method is prone to information leakage, which poses a great security risk.

[0053] In order to solve at least some of the above technical problems, the present disclosure provides a data transmission method, receiving the sampled data ciphertext and the chaotic parameter ciphertext sent by the sensor; using a private key to decrypt the chaotic parameter ciphertext to obtain the chaotic parameters, and generating a measurement chaotic matrix according to the chaotic parameters; based on the measurement chaotic matrix, the sampled data ciphertext is decrypted to obtain the measurement result; the measurement result is compressed sensing signal recovery by measuring the chaotic matrix to obtain the initial signal. On the one hand, the present disclosure generates a measurement chaotic matrix by chaotic parameters, and uses the measurement chaotic matrix to perform encryption operations after data measurement, which can reduce the parameter generation overhead, improve the signal encryption effect, and improve the security. On the other hand, the dynamic measurement chaotic matrix is ​​used to encrypt and decrypt the measurement result, which can effectively improve the security of data transmission and resist plaintext attacks.

[0054] The present exemplary implementation is described in detail below with reference to the accompanying drawings and embodiments.

[0055] First, a data transmission method is provided in an embodiment of the present disclosure, and the method can be executed by any electronic device with computing and processing capabilities. For example, the method can be executed by a sensor end; it can also be executed by a server end; it can also be executed by the interaction between a sensor and a server.

[0056] Figure 2 FIG. 1 is a flow chart of a data transmission method provided by an embodiment of the present disclosure. Figure 2 As shown, the data transmission method provided in the embodiment of the present disclosure is applied to a server, and the method mainly includes the following steps: S202: Receive the sampled data ciphertext and the chaotic parameter ciphertext sent by the sensor.

[0057] The sampled data ciphertext is the ciphertext obtained by encrypting the measurement result at the sensor end, and the measurement result is obtained by performing compressed sensing sampling on the initial signal by measuring the chaotic matrix.

[0058] The initial signal is the unprocessed original signal collected by the sensor, and the initial signal can be a one-dimensional signal or a two-dimensional signal. For example, the one-dimensional signal can be an audio signal, a voltage signal, etc., and the two-dimensional signal can be an image signal, a video frame, etc.

[0059] The chaotic parameter ciphertext is the ciphertext obtained by encrypting the chaotic parameter at the sensor end using the asymmetric public key corresponding to the server.

[0060] The chaotic parameters are randomly generated by the sensor, and the chaotic parameters include the system parameter μ and the initial value x0. The chaotic sequence is generated by the chaotic parameters to generate the measurement chaotic matrix according to the chaotic sequence.

[0061] In one embodiment, the value range of the system parameter μ is 3.569946≤μ≤4, so that the system exhibits chaotic behavior. The system parameter μ can be generated by uniform sampling within the above value range.

[0062] The initial value x0 has a range of (0,1). In the interval (0,1), it avoids fixed points (such as 0, 0.5, 1) to avoid non-chaotic behavior. The initial value x0 can be generated by uniform sampling in the interval (0,1).

[0063] S204, using a private key to decrypt the chaotic parameter ciphertext to obtain the chaotic parameters, and generating a measured chaotic matrix according to the chaotic parameters.

[0064] In one embodiment, the server uses the private key in the generated public-private key pair to decrypt the chaotic parameter ciphertext, including calculating the point T=kC1, calculating A=C2-T, and obtaining the chaotic parameter plaintext A, that is, obtaining the chaotic system parameter μ and the initial value x0. Among them, C1 is a point on the randomly generated elliptic curve, representing a temporary public key, which can be obtained by scalar product operation based on the elliptic curve parameter (such as the base point G) and the random number k; C2 is the chaotic parameter ciphertext.

[0065] The measurement chaos matrix is ​​a random matrix generated by the chaotic system based on the chaotic parameters. It is used in compressed sensing technology to project high-dimensional signals into low-dimensional space and realize data compression and encryption at the same time. The measurement chaos matrix can be compressed and sampled, and the randomness of the chaotic system can reduce the data dimension and storage and transmission overhead. The measurement chaos matrix can also be encrypted and protected. The nonlinear characteristics of the chaotic sequence make the matrix difficult to be measured or reverse cracked, which enhances security.

[0066] S206. Based on the measurement chaotic matrix, the sampled data ciphertext is decrypted to obtain a measurement result.

[0067] In one embodiment, the decryption process may include but is not limited to an inverse diffusion operation, an inverse scrambling operation, etc. It should be noted that in the encryption operations such as diffusion operation and inverse scrambling operation performed on the measurement results at the sensor end, the measurement chaos matrix is ​​used as a parameter of the diffusion operation and the scrambling operation, thereby reducing the overhead of parameter generation.

[0068] The measurement result is a sampling result obtained by performing compressed sensing signal sampling on the initial signal by measuring the chaotic matrix.

[0069] S208. Perform compressed sensing signal recovery on the measurement result by measuring the chaotic matrix to obtain an initial signal.

[0070] The compressed sensing signal recovery process on the server side is the inverse process or reverse operation of the compressed sensing signal acquisition process on the sensor side.

[0071] In one embodiment, the above compressed sensing signal recovery can be described as an l0 norm problem. By minimizing the l0 norm of the vector s, a solution satisfying the linear constraint y=As is found, which is expressed as follows: (Formula 1) Among them, s is the coefficient vector to be solved, that is, the initial signal of the present invention, y is the measurement result, and A is the known measurement matrix, that is, the measurement chaos matrix of the present invention.

[0072] In S208, an iteratively reweighted least squares (IRLS) algorithm may be used to recover the compressed sensing signal, wherein when the initial signal is a one-dimensional signal, the signal is directly recovered, and when the initial signal is a two-dimensional signal, the signal is recovered column by column. The IRLS algorithm may be used for signal reconstruction, and the original signal may be recovered through sparse representation, thereby improving the accuracy and robustness of signal reconstruction.

[0073] Before S208 performs compressed sensing signal recovery on the measurement result by measuring the chaotic matrix to obtain the initial signal, the method also includes: when the initial signal is a one-dimensional signal, extracting the first column of the measured chaotic matrix to obtain a one-dimensional measured chaotic matrix, and the dimension of the measurement result remains unchanged; when the initial signal is a two-dimensional signal, merging the measured chaotic matrix into a one-dimensional series by column to obtain a one-dimensional measured chaotic matrix, and merging the measurement results into one-dimensional data by column to obtain a one-dimensional measurement result, thereby enhancing the applicability of encryption and decryption on one-dimensional data and two-dimensional data on sensors during data transmission.

[0074] In the embodiment of the present disclosure, the sampling data ciphertext and the chaos parameter ciphertext sent by the sensor are received; the chaos parameter ciphertext is decrypted by using a private key to obtain the chaos parameter, and a measurement chaos matrix is ​​generated according to the chaos parameter; based on the measurement chaos matrix, the sampling data ciphertext is decrypted to obtain the measurement result; the measurement result is subjected to compressed sensing signal recovery by using the measurement chaos matrix to obtain the initial signal. On the one hand, the present disclosure generates a measurement chaos matrix by using the chaos parameter, and uses the measurement chaos matrix to perform encryption operation after the data is measured, which can reduce the parameter generation overhead, improve the signal encryption effect, and provide better security. On the other hand, the measurement result is encrypted and decrypted by using a dynamic measurement chaos matrix, which can effectively improve the security of data transmission and resist plaintext attacks.

[0075] In one embodiment, before receiving the sampled data ciphertext and the chaotic parameter ciphertext sent by the sensor in S202, the method may further include: using an asymmetric encryption algorithm to generate a public-private key pair; and sending or presetting the public key in the sensor.

[0076] Asymmetric encryption algorithms may include but are not limited to Elliptic Curve Cryptography (ECC), Commercial Secret SM2, Post Quantum Cryptography (PQC) and other algorithms.

[0077] In one embodiment, the server generates a public key P and a private key k according to the selected elliptic curve and base point G, wherein the private key k is retained locally for decryption, and the public key P is sent to the sensor or pre-set in the sensor for encryption.

[0078] Select a random number r and generate chaotic parameter ciphertext C from chaotic parameter plaintext A, C=(C1, C2), where C1=rG, C2=A+rP, where r is a random number, G is a base point, A is chaotic parameter plaintext, and P is a public key.

[0079] In the embodiment of the present disclosure, the server can configure the public key in the sensor, so that the sensor does not need to generate an additional secret key, and uses the server's public key to directly encrypt the chaotic parameters, thereby reducing the overhead of secret key generation and maintenance on the sensor side and greatly reducing the energy consumption of the sensor.

[0080] Figure 3 FIG. 2 shows a flow chart of a method for generating a measurement chaos matrix provided by an embodiment of the present disclosure. Figure 3 As shown, in one embodiment, generating a measurement chaos matrix according to the chaos parameters in S204 includes: S302, generating a chaotic sequence according to chaotic parameters; S304, using a preset step size to extract samples from the chaotic sequence to obtain a measurement chaotic matrix, and the measurement chaotic matrix satisfies a restricted isometry property (RIP) condition.

[0081] In one embodiment, the measurement chaos matrix is ​​obtained by using a Logistic chaotic sequence.

[0082] In S302, a chaotic sequence is generated using the system parameter μ and the initial value x0. The chaotic sequence can be expressed as: (Formula 2) Where n=0,1,…,x n+1 and x n are the n+1th and nth terms of the chaotic sequence.

[0083] In S304, the chaotic sequence is subjected to sampling using a preset step size to form a measurement matrix that satisfies the RIP condition. The sampling method can be expressed as: (Formula 3) Among them, t represents the initial value of the chaotic sequence, d represents the preset step size or sampling distance, and the measurement chaotic matrix Ф is expressed as: (Formula 4) Where M and N are positive integers. Used to normalize the measured chaos matrix.

[0084] In the embodiments of the present disclosure, by decrypting the transmitted chaotic parameter ciphertext and generating a measurement chaotic matrix in the same manner as the sensor end, the overhead of the sensor end can be reduced.

[0085] Figure 4 FIG. 2 shows another flow chart of a data transmission method provided by an embodiment of the present disclosure. Figure 2 Based on the embodiment, S206 is further refined into S2062, and the decryption process includes a reverse diffusion operation; wherein S206 performs decryption processing on the sampled data ciphertext to obtain a measurement result, including: S2062. Perform a reverse diffusion operation on the sampled data ciphertext by measuring the chaotic matrix to obtain reverse diffusion information, wherein the reverse diffusion operation is a bidirectional XOR reverse diffusion operation.

[0086] In one embodiment, the server extracts the sample data ciphertext from the received data, and uses a bidirectional XOR de-diffusion operation to obtain de-diffusion information.

[0087] For the anti-diffusion operation, first perform the M×N~1 anti-diffusion operation, which can be expressed as: (Formula 5) Among them, i is the data index, D i is the i-th element of the one-dimensional measurement matrix Φ', C i+1 and C i They are the i+1th and ith sample data ciphertexts respectively.

[0088] Then, a 1~M×N anti-diffusion operation is performed, which can be expressed as: (Formula 6) Among them, Divide by the measured chaos matrix element , we can get the reverse diffusion information P i .

[0089] In one embodiment, the sensor end may perform a diffusion operation on the measurement result to encrypt it and obtain a ciphertext of the sampled data. At this time, the compressed sensing signal recovery may be performed on the reverse diffusion signal Pi by measuring the chaotic matrix to obtain the initial signal.

[0090] In the embodiments of the present disclosure, based on the measurement chaos matrix, the decryption of the sampled data ciphertext is achieved through the reverse diffusion operation, which can improve the security and reliability of data transmission.

[0091] Figure 5 A flow chart of another data transmission method provided by an embodiment of the present disclosure is shown. Figure 4 On the basis of the embodiment, S2064 is added after S2062 to limit the scheme of first performing a reverse diffusion operation and then a reverse scrambling operation to decrypt the sampled data ciphertext. Figure 5 As shown, in one embodiment, the decryption process also includes an inverse scrambling operation; wherein the above S206 performs decryption processing on the sampled data ciphertext to obtain a measurement result, and further includes: S2064. Generate a scrambling index according to the measurement chaos matrix in the same manner as the sensor side; perform a descrambling operation on the de-diffusion information according to the scrambling index to obtain a measurement result.

[0092] In one embodiment, using the generated measurement chaotic matrix as an index for generating a scrambled matrix can avoid additional matrix generation computational overhead.

[0093] The scrambling order based on the measurement chaos matrix can be used to generate indexes in ascending or descending order, and the present disclosure does not make any specific limitation on this.

[0094] The descrambling operation can be expressed as: (Formula 7) in, Represents the index after sorting the measurement chaos matrix.

[0095] For signal dimension transformation, when the initial signal is a one-dimensional signal, the dimension of the sampled signal after the inverse scrambling operation remains unchanged. When the initial signal is a two-dimensional signal, the one-dimensional sampled signal Y after the inverse scrambling operation is restored column by column according to the sampling size d at the sensor end.

[0096] It should be noted that the sensor end can also perform a scrambling operation on the measurement data separately to obtain the sampled data ciphertext. Correspondingly, the server end performs a descrambling operation on the sampled data ciphertext to obtain the measurement data, thereby realizing data encryption and decryption.

[0097] In the embodiments of the present disclosure, the chaotic matrix is ​​measured to generate the index of the scrambled matrix, and the inverse scrambling is performed, which can reduce the calculation overhead of parameters and additional matrix generation.

[0098] Figure 6 FIG. 1 is a flow chart of a data transmission method for a sensor provided by an embodiment of the present disclosure. Figure 6As shown, in one embodiment, the data transmission method disclosed in the present invention is applied to a sensor end, and the method mainly includes the following steps: S602: randomly generate chaotic parameters, and encrypt the chaotic parameters using a public key to obtain a chaotic parameter ciphertext.

[0099] The chaotic parameters are randomly generated by the sensor, and the chaotic parameters include the system parameter μ and the initial value x0. The chaotic sequence is generated by the chaotic parameters to generate the measurement chaotic matrix according to the chaotic sequence.

[0100] In one embodiment, the value range of the system parameter μ is 3.569946≤μ≤4, so that the system exhibits chaotic behavior. The system parameter μ can be generated by uniform sampling within the above value range.

[0101] The initial value x0 has a range of (0,1). In the interval (0,1), it avoids fixed points (such as 0, 0.5, 1) to avoid non-chaotic behavior. The initial value x0 can be generated by uniform sampling in the interval (0,1).

[0102] In one embodiment, the public key is generated on the server side. The sensor needs to deploy the public key P on the server side before data collection, which can be preset before deployment or transmitted through an information channel after deployment, so that the sensor does not need to generate additional keys, and directly encrypts the chaotic parameters using the public key on the server side, reducing the overhead of key generation and maintenance on the sensor side.

[0103] The sensor and the server need to negotiate to use the same elliptic curve and the same base point G on the selected elliptic curve. The elliptic curve may be predefined by a standardization organization, for example, elliptic curves such as SECP256R1 or SECP384R1 may be used, and the present disclosure does not specifically limit this.

[0104] The chaotic parameters are directly encrypted using the server-side public key P. A random number r is selected to generate the ciphertext C from the chaotic parameter plaintext A, C=(C1, C2), where C1=rG, C2=A+rP, r is the random number, G is the base point, A is the chaotic parameter plaintext, and P is the public key.

[0105] S604: Generate a measurement chaos matrix according to the chaos parameters.

[0106] The measurement chaos matrix is ​​a random matrix generated by the chaotic system based on the chaotic parameters. It is used in compressed sensing technology to project high-dimensional signals into low-dimensional space and realize data compression and encryption at the same time. The measurement chaos matrix can be compressed and sampled, and the randomness of the chaotic system can reduce the data dimension and storage and transmission overhead. The measurement chaos matrix can also be encrypted and protected. The nonlinear characteristics of the chaotic sequence make the matrix difficult to be measured or reverse cracked, which enhances security.

[0107] S606: Perform compressed sensing sampling on the initial signal based on the measurement chaos matrix to obtain a measurement result.

[0108] In one embodiment, the measurement process can be expressed as y=Φx, where Φ is the measurement chaos matrix, , y is the measurement result, .

[0109] S608: Encrypt the measurement result based on the measurement chaotic matrix to obtain a ciphertext of the sampled data.

[0110] In one embodiment, the encryption process may include but is not limited to scrambling operations, diffusion operations, etc. The scrambling operation may change the position of characters in the plain text to generate ciphertext, and the diffusion operation may change the element value of the corresponding position without changing the element position, so that the pixel information of a certain position is diffused to other ciphertext elements.

[0111] S610: Send the chaotic parameter ciphertext and the sampled data ciphertext to the server.

[0112] In the embodiment of the present disclosure, the sensor randomly generates chaotic parameters, and uses public key encryption to encrypt the chaotic parameters to obtain chaotic parameter ciphertext; generates a measurement chaotic matrix according to the chaotic parameters; performs compressed sensing sampling on the initial signal based on the measurement chaotic matrix to obtain a measurement result; encrypts the measurement result based on the measurement chaotic matrix to obtain a sampled data ciphertext; sends the chaotic parameter ciphertext and the sampled data ciphertext to the server. On the one hand, the present disclosure generates a measurement chaotic matrix through chaotic parameters, and uses the measurement chaotic matrix for encryption operations after data measurement, which can reduce parameter generation overhead, improve signal encryption effect, and improve security. On the other hand, the use of a dynamic measurement chaotic matrix to encrypt and decrypt the measurement results can effectively improve the security of data transmission and resist plaintext attacks.

[0113] In one embodiment, the above S604 generates a measurement chaotic matrix according to chaotic parameters, including: using the chaotic parameters to generate a chaotic sequence; using a preset step size to extract samples from the chaotic sequence to obtain a measurement chaotic matrix, and the measurement chaotic matrix satisfies a restricted equidistance condition.

[0114] It should be noted that the method of generating the measurement chaos matrix according to the chaos parameters at the sensor end is the same as the method of generating the measurement chaos matrix according to the chaos parameters at the server end, which will not be described in detail here.

[0115] In one embodiment, the above S606 performs compressed sensing sampling on the initial signal based on the measurement chaos matrix to obtain a measurement result, including: when the initial signal is a one-dimensional signal, extracting the first column of the measurement chaos matrix to obtain a one-dimensional measurement chaos matrix, and the dimension of the measurement result remains unchanged; when the initial signal is a two-dimensional signal, merging the measurement chaos matrix into one-dimensional data by column to obtain a one-dimensional measurement chaos matrix, and merging the measurement results into one-dimensional data by column to obtain a one-dimensional measurement result, thereby unifying the acquisition and encryption processes of one-dimensional signals and two-dimensional signals, and effectively improving the applicability of the data transmission scheme disclosed in the present invention to one-dimensional data sensors and two-dimensional data sensors.

[0116] Figure 7 FIG. 2 is a flow chart of another data transmission method for a sensor provided by an embodiment of the present disclosure. Figure 6 Based on the embodiment, S608 is further refined into S6082 to define the method of encrypting the measurement result through the scrambling operation. Figure 7 As shown, in one embodiment, the encryption process includes a scrambling operation; wherein S608 performs encryption processing on the measurement result based on the measurement chaotic matrix to obtain a sampled data ciphertext, including: S6082. Use the measurement chaos matrix to generate a scrambling index, and perform a scrambling operation on the measurement result according to the scrambling index to generate a scrambling signal.

[0117] In one embodiment, using the generated measurement chaotic matrix as an index for generating a scrambled matrix can avoid additional matrix generation computational overhead.

[0118] The scrambling order based on the measurement chaos matrix can be used to generate indexes in ascending or descending order, and the present disclosure does not make any specific limitation on this.

[0119] The scrambling operation can be expressed as: (Formula 8) in, Represents the index after sorting the measurement chaos matrix.

[0120] In the embodiments of the present disclosure, the chaotic matrix is ​​measured to generate the index of the scrambled matrix, and the inverse scrambling is performed, which can reduce the calculation overhead of parameters and additional matrix generation.

[0121] Continue to refer Figure 7 , S608 is further refined into S6084 to define the encryption processing method of the measurement result through the scrambling operation and the diffusion operation. Figure 7 As shown, in one embodiment, the encryption process further includes a diffusion operation; wherein S608 performs encryption processing on the measurement result based on the measurement chaotic matrix to obtain the sampled data ciphertext, and further includes: S6084. Perform a diffusion operation on the scrambled signal based on the measured chaotic matrix to obtain a sampled data ciphertext, wherein the diffusion operation includes a bidirectional XOR diffusion operation.

[0122] In one embodiment, a bidirectional XOR diffusion operation is used to rearrange the input M×N data into a one-dimensional sequence. The forward diffusion operation from index 1 to M×N can be expressed as: (Formula 9) Where i is the data index, D is the diffusion key, and in the present disclosure, the one-dimensional measurement chaos matrix Φ', is the one-dimensional measurement chaos matrix Ф' and the above scrambled signal P i The product of .

[0123] The reverse diffusion operation from index M×N~1 can be expressed as: (Formula 10) Among them, C i is the obtained sample data ciphertext.

[0124] To implement the OR operation, the above diffusion parameter must be multiplied by a fixed large number, rounded up, and then divided by this number to recover during the decryption stage.

[0125] In the embodiments of the present disclosure, based on the measurement chaos matrix, the encryption of the measurement result is achieved through diffusion operation, which can improve the security and reliability of data transmission.

[0126] In order to deepen the understanding of the embodiments of the present disclosure, Figure 8 Provide detailed explanation.

[0127] like Figure 8 As shown, the data transmission method, the processing at the sensor end mainly includes: server public key acquisition, chaos parameter generation, chaos parameter encryption, measurement chaos matrix generation, compressed sensing sampling, signal dimension transformation, sampling data scrambling, data diffusion to generate encrypted data, encryption parameters and encrypted data transmission and other operations. The sensor end mainly includes the following steps: S1. Preset or obtain the public key of the server; S2, the sensor randomly generates chaotic parameters, which include system parameters μ and initial value x0; S3, using the asymmetric public key P corresponding to the server to encrypt the chaotic parameter to obtain the chaotic parameter ciphertext; S4, using the chaotic parameters in S2 to generate a measurement chaotic matrix; S5. Use the measurement chaos matrix to complete the compressed sensing signal acquisition and obtain the measurement result; S6, according to whether the initial signal is a one-dimensional signal or a two-dimensional signal, adjusting the dimension of the measurement chaos matrix and the measurement result to be one-dimensional; S7, using the measured chaotic matrix to generate a scrambling index, performing a scrambling operation, and forming a scrambling signal; S8, using the measurement chaos matrix to perform a diffusion operation on the scrambled signal to form a sampled data ciphertext; S9, merge the sample data ciphertext in S8 and the chaotic parameter ciphertext in S3, and transmit them to the server.

[0128] The data transmission method uses the reverse operation of the sensor operation on the server side, and the processing mainly includes: server public-private key pair generation, chaotic parameter decryption, measurement chaotic matrix generation, encrypted data de-diffusion, encrypted data de-scrambling, signal dimension transformation, compressed sensing signal recovery and other operations. The steps of server-side data decryption and recovery mainly include: S10. The server generates a private key and a public key using an elliptic curve asymmetric algorithm. S11, decrypting the received chaotic parameter ciphertext using the private key to obtain the decrypted chaotic parameter; S12, using the chaotic parameters in S11 to generate a measurement chaotic matrix; S13, extracting the sampled data ciphertext from the received data, and obtaining the reverse diffusion information by using a bidirectional reverse diffusion operation according to the measured chaotic matrix; S14, using the same method as the sensor end to generate a scrambled index, and performing a descrambling operation on the de-diffusion information to obtain a measurement result Y'; S15, adjusting the decrypted data dimension to one dimension or two dimensions according to the actual one-dimensional or two-dimensional signal; S16. Use a compressed sensing recovery algorithm to recover the collected signal X' from the compressed sensing collected signal, that is, to recover the initial signal.

[0129] It should be noted that the above examples are only provided to illustrate the embodiments of the present disclosure and should not be regarded as limiting the scope of protection of the present disclosure. The above steps can also be adjusted in order according to actual needs, and this application does not make specific limitations.

[0130] The present disclosure provides a sensor compression sensing encryption and transmission scheme suitable for resource-constrained sensors. In the present disclosure, chaotic parameters are used to generate a Logistic chaotic sequence and sampled to obtain a measurement chaotic matrix. After data measurement, the measurement chaotic matrix is ​​used to perform scrambling and diffusion operations to hide signal power information, further improving signal encryption characteristics. In order to achieve secure transmission of chaotic parameters, the asymmetric public key of the server is used in the present disclosure for data encryption. The present disclosure has the following beneficial effects: 1. The present disclosure uses an easy-to-implement Logistic chaotic sequence to generate a measurement chaotic matrix, thereby reducing the overhead on the sensor side; 2. The measurement chaotic matrix is ​​used as a parameter for encryption scrambling operations and diffusion operations, thereby reducing the overhead of parameter generation; 3. The sensor side does not need to generate additional keys, and the chaotic parameters are directly encrypted using the public key on the server side, thereby reducing the overhead of key generation and maintenance on the sensor side; 4. In view of the characteristics of the chaotic parameters (small data volume and high importance), the chaotic parameters are directly encrypted using the public key on the server side. Compared with the method of first negotiating a shared key and then performing symmetric encryption, the method has less overhead and higher security, and is more suitable for resource-constrained sensor compressed sensing data transmission scenarios; 5. The acquisition and encryption processes of one-dimensional and two-dimensional signals are unified, thereby increasing the applicability of the encrypted data transmission method to one-dimensional data and two-dimensional data sensors.

[0131] Based on the same inventive concept, the embodiments of the present disclosure also provide a data transmission device and system, as described in the following embodiments. Since the principle of solving the problem in the device and system embodiments is similar to that in the above method embodiments, the implementation of this embodiment can refer to the implementation of the above method embodiments, and the repeated parts will not be repeated.

[0132] Fig. 9 FIG. 2 is a schematic diagram showing a structure of a data transmission device provided by an embodiment of the present disclosure. Fig. 9 As shown, a data transmission device of this embodiment is applied to a server, and the device includes: a data receiving module 910, which is used to receive the sampling data ciphertext and the chaotic parameter ciphertext sent by the sensor; a first generating module 920, which is used to decrypt the chaotic parameter ciphertext with a private key to obtain the chaotic parameters, and generate a measurement chaotic matrix according to the chaotic parameters; a data decryption module 930, which is used to decrypt the sampling data ciphertext to obtain a measurement result; a signal recovery module 940, which is used to perform compressed sensing signal recovery on the measurement result through the measurement chaotic matrix to obtain an initial signal.

[0133] In one embodiment, the first generating module 920 is used to generate a chaotic sequence according to the chaotic parameters; and to extract samples from the chaotic sequence using a preset step size to obtain a measurement chaotic matrix, and the measurement chaotic matrix satisfies a restricted equidistance condition.

[0134] In one embodiment, the device also includes a dimensional transformation module, which is used to perform compressed sensing signal recovery on the measurement result through the measurement chaos matrix to obtain the initial signal. When the initial signal is a one-dimensional signal, the first column of the measurement chaos matrix is ​​extracted to obtain a one-dimensional measurement chaos matrix, and the dimension of the measurement result remains unchanged; when the initial signal is a two-dimensional signal, the measurement chaos matrix is ​​merged into a one-dimensional series by column to obtain a one-dimensional measurement chaos matrix, and the measurement result is merged into one-dimensional data by column to obtain a one-dimensional measurement result.

[0135] In one embodiment, the signal recovery module 940 is used to perform compressed sensing signal recovery using an iterative reweighted least squares algorithm, wherein when the initial signal is a one-dimensional signal, the recovery is performed directly, and when the initial signal is a two-dimensional signal, the signal recovery is performed column by column.

[0136] In one embodiment, the decryption process includes a reverse diffusion operation; the data decryption module 930 is used to perform a reverse diffusion operation on the sampled data ciphertext by measuring the chaotic matrix to obtain reverse diffusion information, wherein the reverse diffusion operation is a bidirectional XOR reverse diffusion operation.

[0137] In one embodiment, the decryption process also includes an inverse scrambling operation; the data decryption module 930 is used to generate a scrambling index according to the measurement chaotic matrix in the same manner as the sensor side; and perform an inverse scrambling operation on the reverse diffusion information according to the scrambling index to obtain a measurement result.

[0138] In one embodiment, the device also includes a key generation module not shown in the accompanying drawings, which is used to generate a public-private key pair using an asymmetric encryption algorithm before receiving the sampling data ciphertext and chaotic parameter ciphertext sent by the sensor; and send or pre-set the public key in the sensor.

[0139] In the embodiment of the present disclosure, the sampling data ciphertext and the chaos parameter ciphertext sent by the sensor are received; the chaos parameter ciphertext is decrypted by using a private key to obtain the chaos parameter, and a measurement chaos matrix is ​​generated according to the chaos parameter; based on the measurement chaos matrix, the sampling data ciphertext is decrypted to obtain the measurement result; the measurement result is subjected to compressed sensing signal recovery by using the measurement chaos matrix to obtain the initial signal. On the one hand, the present disclosure generates a measurement chaos matrix by using the chaos parameter, and uses the measurement chaos matrix to perform encryption operation after the data is measured, which can reduce the parameter generation overhead, improve the signal encryption effect, and provide better security. On the other hand, the measurement result is encrypted and decrypted by using a dynamic measurement chaos matrix, which can effectively improve the security of data transmission and resist plaintext attacks.

[0140] Fig.10 FIG. 2 is a schematic diagram showing the structure of another data transmission device provided by an embodiment of the present disclosure. Fig.10As shown, a data transmission device of this embodiment is applied to a sensor, and the device includes: The parameter encryption module 1010 is used to randomly generate chaotic parameters and encrypt the chaotic parameters using a public key to obtain a chaotic parameter ciphertext; The second generating module 1020 is used to generate a measurement chaos matrix according to the chaos parameters; The signal sampling module 1030 is used to perform compressed sensing sampling on the initial signal based on the measurement chaotic matrix to obtain a measurement result; The data encryption module 1040 is used to encrypt the measurement result based on the measurement chaotic matrix to obtain the sampled data ciphertext; The data sending module 1050 is used to send the chaotic parameter ciphertext and the sampled data ciphertext to the server.

[0141] In one embodiment, the second generating module 1020 is used to generate a chaotic sequence using chaotic parameters; and to extract samples from the chaotic sequence using a preset step size to obtain a measurement chaotic matrix, and the measurement chaotic matrix satisfies a restricted equidistance condition.

[0142] In one embodiment, the signal sampling module 1030 is used to extract the first column of the measurement chaotic matrix when the initial signal is a one-dimensional signal to obtain a one-dimensional measurement chaotic matrix, and the dimension of the measurement result remains unchanged; when the initial signal is a two-dimensional signal, the measurement chaotic matrix is ​​merged into one-dimensional data by columns to obtain a one-dimensional measurement chaotic matrix, and the measurement results are merged into one-dimensional data by columns to obtain a one-dimensional measurement result.

[0143] In one embodiment, the encryption process includes a scrambling operation; the data encryption module 1040 is used to generate a scrambling index using the measurement chaotic matrix, and perform a scrambling operation on the measurement result according to the scrambling index to generate a scrambling signal.

[0144] In one embodiment, the encryption process also includes a diffusion operation; the data encryption module 1040 is used to perform a diffusion operation on the scrambled signal based on the measurement chaotic matrix to obtain the sampled data ciphertext, wherein the diffusion operation includes a bidirectional XOR diffusion operation.

[0145] In the embodiment of the present disclosure, the sensor randomly generates chaotic parameters, and uses public key encryption to encrypt the chaotic parameters to obtain chaotic parameter ciphertext; generates a measurement chaotic matrix according to the chaotic parameters; performs compressed sensing sampling on the initial signal based on the measurement chaotic matrix to obtain a measurement result; encrypts the measurement result based on the measurement chaotic matrix to obtain a sampled data ciphertext; sends the chaotic parameter ciphertext and the sampled data ciphertext to the server. On the one hand, the present disclosure generates a measurement chaotic matrix through chaotic parameters, and uses the measurement chaotic matrix for encryption operations after data measurement, which can reduce parameter generation overhead, improve signal encryption effect, and improve security. On the other hand, the use of a dynamic measurement chaotic matrix to encrypt and decrypt the measurement results can effectively improve the security of data transmission and resist plaintext attacks.

[0146] The present disclosure also provides a data transmission system, which includes a server and a sensor, wherein: the server is used to receive sampling data ciphertext and chaos parameter ciphertext sent by the sensor; the chaos parameter ciphertext is decrypted using a private key to obtain chaos parameters, and a measurement chaos matrix is ​​generated according to the chaos parameters; the sampling data ciphertext is decrypted to obtain a measurement result; the measurement result is compressed sensing signal recovery is performed on the measurement result by measuring the chaos matrix to obtain an initial signal; the sensor is used to randomly generate chaos parameters, and the chaos parameters are encrypted using a public key to obtain chaos parameter ciphertext; the measurement chaos matrix is ​​generated according to the chaos parameters; the initial signal is compressed sensing sampled based on the measurement chaos matrix to obtain a measurement result; the measurement result is encrypted based on the measurement chaos matrix to obtain sampling data ciphertext; the chaos parameter ciphertext and the sampling data ciphertext are sent to the server.

[0147] Those skilled in the art will appreciate that various aspects of the present disclosure may be implemented as systems, methods or program products. Therefore, various aspects of the present disclosure may be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as "circuits", "modules" or "systems".

[0148] Refer to the following Fig.11 1100 according to this embodiment of the present disclosure is described. Fig.11 The electronic device 1100 shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0149] like Fig.11 As shown, the electronic device 1100 is in the form of a general computing device. The components of the electronic device 1100 may include but are not limited to: at least one processing unit 1110, at least one storage unit 1120, and a bus 1130 connecting different system components (including the storage unit 1120 and the processing unit 1110).

[0150] The storage unit stores a program code, and the program code can be executed by the processing unit 1110, so that the processing unit 1110 executes the steps described in the above "Exemplary Method" section of this specification according to various exemplary embodiments of the present disclosure. For example, the processing unit 1110 can execute the following steps of the above method embodiment: receiving the sampling data ciphertext and the chaotic parameter ciphertext sent by the sensor; decrypting the chaotic parameter ciphertext using a private key to obtain the chaotic parameters, and generating a measurement chaotic matrix based on the chaotic parameters; decrypting the sampling data ciphertext based on the measurement chaotic matrix to obtain a measurement result; performing compressed sensing signal recovery on the measurement result through the measurement chaotic matrix to obtain an initial signal.

[0151] For example, the processing unit 1110 can execute the following steps of the above method embodiment: randomly generate chaotic parameters, and use public key encryption to obtain chaotic parameter ciphertext; generate a measurement chaotic matrix according to the chaotic parameters; perform compressed sensing sampling on the initial signal based on the measurement chaotic matrix to obtain a measurement result; encrypt the measurement result based on the measurement chaotic matrix to obtain a sampling data ciphertext; and send the chaotic parameter ciphertext and the sampling data ciphertext to the server.

[0152] The storage unit 1120 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 11201 and / or a cache storage unit 11202 , and may further include a read-only storage unit (ROM) 11203 .

[0153] The storage unit 1120 may also include a program / utility 11204 having a set (at least one) of program modules 11205, such program modules 11205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0154] Bus 1130 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0155] The electronic device 1100 may also communicate with one or more external devices 1140 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable a user to interact with the electronic device 1100, and / or any device that enables the electronic device 1100 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 1150. Furthermore, the electronic device 1100 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 1160. Fig.11 As shown, the network adapter 1160 communicates with other modules of the electronic device 1100 via the bus 1130. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device 1100, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0156] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes a number of instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0157] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is further provided, which may be a readable signal medium or a readable storage medium. Fig.12 A schematic diagram of a computer-readable storage medium provided in an embodiment of the present disclosure is shown. Fig.12 As shown, a program product capable of implementing the above method of the present disclosure is stored on the computer-readable storage medium 1200. In an exemplary embodiment of the present disclosure, a computer program product is also provided, the computer program product includes a computer program or a computer instruction, and the computer program or the computer instruction is loaded and executed by a processor to enable a computer to implement any of the above data transmission methods.

[0158] More specific examples of computer-readable storage media in the present disclosure may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0159] In the present disclosure, a computer readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, wherein a readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A readable signal medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0160] Alternatively, the program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0161] In specific implementation, the program code for performing the operation of the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" language or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as an independent software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0162] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0163] In addition, although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0164] Through the description of the above implementation modes, it is easy for those skilled in the art to understand that the example implementation modes described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation mode of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the implementation mode of the present disclosure.

[0165] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present disclosure is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary technical means in the art that are not disclosed in the present disclosure. The description and examples are to be regarded as exemplary only, and the true scope of the present disclosure is indicated by the appended claims.

Claims

1. A data transmission method, characterized in that: Applied to a server, the method comprises: Receive the sampled data ciphertext and chaos parameter ciphertext sent by the sensor; Decrypting the chaotic parameter ciphertext with a private key to obtain the chaotic parameters, and generating a measured chaotic matrix according to the chaotic parameters; Based on the measurement chaotic matrix, the sampled data ciphertext is decrypted to obtain a measurement result; The measurement result is subjected to compressed sensing signal recovery through the measurement chaotic matrix to obtain an initial signal.

2. The data transmission method according to claim 1, characterized in that: The generating a measurement chaos matrix according to the chaos parameters comprises: Generate chaotic sequences according to chaotic parameters; The chaotic sequence is sampled using a preset step length to obtain the measurement chaotic matrix, and the measurement chaotic matrix satisfies a restricted equidistance condition.

3. The data transmission method according to claim 1 or 2, characterized in that: Before performing compressed sensing signal recovery on the measurement result through the measurement chaotic matrix to obtain an initial signal, the method further includes: When the initial signal is a one-dimensional signal, extracting the first column of the measurement chaotic matrix to obtain a one-dimensional measurement chaotic matrix, the dimension of the measurement result remains unchanged; When the initial signal is a two-dimensional signal, the measurement chaotic matrix is ​​merged into a one-dimensional series by column to obtain a one-dimensional measurement chaotic matrix, and the measurement results are merged into one-dimensional data by column to obtain a one-dimensional measurement result.

4. The data transmission method according to claim 3, characterized in that: The performing compressed sensing signal recovery on the measurement result by using the measurement chaotic matrix to obtain an initial signal includes: An iterative reweighted least squares algorithm is used to recover the compressed sensing signal. When the initial signal is a one-dimensional signal, the signal is directly recovered. When the initial signal is a two-dimensional signal, the signal is recovered column by column.

5. The data transmission method according to claim 1, characterized in that: The decryption process includes a reverse diffusion operation; The decrypting of the sampled data ciphertext to obtain the measurement result includes: The reverse diffusion operation is performed on the sampled data ciphertext through the measurement chaotic matrix to obtain reverse diffusion information, wherein the reverse diffusion operation is a bidirectional XOR reverse diffusion operation.

6. The data transmission method according to claim 5, characterized in that: The decryption process also includes a descrambling operation; The decrypting of the sampled data ciphertext to obtain the measurement result includes: Generate a scrambled index according to the measured chaotic matrix in the same manner as the sensor side; According to the scrambling index, a descrambling operation is performed on the de-diffusion information to obtain the measurement result.

7. The data transmission method according to claim 1, characterized in that: Before receiving the sampled data ciphertext and the chaotic parameter ciphertext sent by the sensor, the method further includes: Use an asymmetric encryption algorithm to generate a public-private key pair; The public key is sent or pre-set in the sensor.

8. A data transmission method, characterized in that: Applied to the sensor end, the method includes: Randomly generate chaotic parameters, and encrypt the chaotic parameters using a public key to obtain a chaotic parameter ciphertext; According to the chaotic parameters, a measurement chaotic matrix is ​​generated; Performing compressed sensing sampling on the initial signal based on the measurement chaotic matrix to obtain a measurement result; Encrypting the measurement result based on the measurement chaotic matrix to obtain a sampled data ciphertext; The chaotic parameter ciphertext and the sampled data ciphertext are sent to a server.

9. The method according to claim 8, characterized in that The step of generating a measurement chaos matrix according to the chaos parameters comprises: generating a chaotic sequence using the chaotic parameters; The chaotic sequence is sampled using a preset step length to obtain the measurement chaotic matrix, and the measurement chaotic matrix satisfies a restricted equidistance condition.

10. The method according to claim 8 or 9, characterized in that: The method of performing compressed sensing sampling on the initial signal based on the measurement chaotic matrix to obtain a measurement result includes: When the initial signal is a one-dimensional signal, extracting the first column of the measurement chaotic matrix to obtain a one-dimensional measurement chaotic matrix, the dimension of the measurement result remains unchanged; When the initial signal is a two-dimensional signal, the measurement chaotic matrix is ​​merged into one-dimensional data by column to obtain a one-dimensional measurement chaotic matrix, and the measurement results are merged into one-dimensional data by column to obtain a one-dimensional measurement result.

11. The method according to claim 8, characterized in that The encryption process includes a scrambling operation; The step of encrypting the measurement result based on the measurement chaotic matrix to obtain a ciphertext of sampled data includes: The measurement chaotic matrix is ​​used to generate a scrambling index, and the scrambling operation is performed on the measurement result according to the scrambling index to generate a scrambling signal.

12. The method according to claim 11, characterized in that The encryption process also includes a diffusion operation; The step of encrypting the measurement result based on the measurement chaotic matrix to obtain a ciphertext of sampled data further includes: The diffusion operation is performed on the scrambled signal based on the measurement chaotic matrix to obtain the sampled data ciphertext, wherein the diffusion operation includes a bidirectional XOR diffusion operation.

13. A data transmission device, applied to a server, characterized in that: The device comprises: A data receiving module is used to receive the ciphertext of sampled data and the ciphertext of chaotic parameters sent by the sensor; A first generating module is used to decrypt the chaotic parameter ciphertext with a private key to obtain chaotic parameters, and generate a measured chaotic matrix according to the chaotic parameters; A data decryption module is used to decrypt the sampled data ciphertext to obtain a measurement result; The signal recovery module is used to perform compressed sensing signal recovery on the measurement result through the measurement chaotic matrix to obtain an initial signal.

14. A data transmission device, applied to a sensor, characterized in that: The device comprises: A parameter encryption module is used to randomly generate chaotic parameters and encrypt the chaotic parameters using a public key to obtain a chaotic parameter ciphertext; A second generating module is used to generate a measurement chaos matrix according to the chaotic parameters; A signal sampling module, used for performing compressed sensing sampling on the initial signal based on the measurement chaotic matrix to obtain a measurement result; A data encryption module, used for encrypting the measurement result based on the measurement chaotic matrix to obtain a sampled data ciphertext; The data sending module is used to send the chaotic parameter ciphertext and the sampled data ciphertext to the server.

15. A data transmission system, characterized in that: It includes servers and sensors, including: The server is used to receive the sampled data ciphertext and the chaotic parameter ciphertext sent by the sensor; decrypt the chaotic parameter ciphertext using a private key to obtain the chaotic parameters, and generate a measurement chaotic matrix according to the chaotic parameters; decrypt the sampled data ciphertext to obtain a measurement result; perform compressed sensing signal recovery on the measurement result through the measurement chaotic matrix to obtain an initial signal; The sensor is used to randomly generate chaotic parameters, and encrypt the chaotic parameters with a public key to obtain chaotic parameter ciphertext; generate a measurement chaotic matrix based on the chaotic parameters; perform compressed sensing sampling on the initial signal based on the measurement chaotic matrix to obtain a measurement result; encrypt the measurement result based on the measurement chaotic matrix to obtain a sampling data ciphertext; and send the chaotic parameter ciphertext and the sampling data ciphertext to a server.

16. An electronic device, characterized in that: It comprises a processor and a memory, wherein the memory is used to store executable instructions of the processor; wherein the processor is configured to execute the data transmission method described in any one of claims 1 to 7, or execute the data transmission method described in any one of claims 8 to 12, by executing the executable instructions.

17. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the data transmission method described in any one of claims 1 to 7, or implements the data transmission method described in any one of claims 8 to 12.

18. A computer program product, characterized in that The method comprises a computer program or a computer instruction, wherein the computer program or the computer instruction is loaded and executed by a processor so that a computer implements the data transmission method according to any one of claims 1 to 7, or implements the data transmission method according to any one of claims 8 to 12.

Images