Signal encryption processing method, signal decryption processing method and signal processing system

Abstract

This application relates to a signal encryption and decryption processing method and a signal processing system. The method includes randomly generating chaotic parameters, generating a measurement matrix based on the chaotic parameters, and performing compressed sensing processing on the original sensor signal under the control of the measurement matrix to obtain a target signal; encrypting the chaotic parameters based on a target quantum key obtained from a quantum key distribution network to obtain encrypted chaotic parameters; transmitting the target signal, the encrypted chaotic parameters, and a key identifier of the target quantum key to a receiving device in the sensor network, so that the receiving device decrypts the encrypted chaotic parameters using the target quantum key corresponding to the key identifier to obtain the chaotic parameters; and performing compressed sensing signal recovery on the target signal based on the chaotic parameters to obtain the original sensor signal. This method can improve data transmission efficiency and data security in sensor networks.

Description

Technical Field

[0001] The present application relates to the field of network security technology, and in particular to a signal encryption processing method, a signal decryption processing method, and a signal processing system. Background Art

[0002] One of the core goals of the development of 6G (sixth-generation mobile networks) is to achieve wider network coverage and support massive sensor connectivity. The explosive growth of IoT (Internet of Things) devices places even higher demands on 6G networks: they must not only be ubiquitous and provide high-speed, low-latency data transmission capabilities, but also ensure secure connections. After all, any security vulnerability could pose a serious threat to data security.

[0003] In sensor networks, due to the scarcity of sensor node resources and limited storage capacity, how to achieve high-speed signal transmission while improving the security of the signal transmission process is an urgent problem that needs to be solved. Summary of the Invention

[0004] Based on this, it is necessary to provide a signal encryption processing method, a signal decryption processing method and a signal processing system to address the above technical problems, which can improve the signal transmission efficiency and security in sensor networks.

[0005] In a first aspect, the present application provides a signal encryption processing method, which is applied to a sending device in a sensor network, and the method includes:

[0006] randomly generating chaotic parameters, generating a measurement matrix based on the chaotic parameters, and performing compressed sensing processing on the original sensor signal under the control of the measurement matrix to obtain a target signal;

[0007] Encrypting the chaotic parameters based on a target quantum key obtained from a quantum key distribution network to obtain encrypted chaotic parameters;

[0008] The target signal, the encrypted chaotic parameters, and a key identifier of the target quantum key are sent to a receiving device in the sensor network, so that the receiving device uses the target quantum key corresponding to the key identifier to decrypt the encrypted chaotic parameters to obtain the chaotic parameters, and performs compressed sensing signal recovery on the target signal based on the chaotic parameters to obtain the original sensor signal.

[0009] In one embodiment, the sending device locally stores at least one quantum key and a key identifier of the quantum key that are pre-acquired from a quantum key distribution network;

[0010] The step of encrypting the chaotic parameters based on the target quantum key obtained from the quantum key distribution network to obtain the encrypted chaotic parameters comprises:

[0011] Obtaining a target quantum key for communicating with a receiving device from at least one locally stored quantum key;

[0012] The target quantum key is used to encrypt the chaotic parameters to obtain encrypted chaotic parameters.

[0013] In one embodiment, encrypting the chaotic parameter based on a target quantum key obtained from a quantum key distribution network to obtain the encrypted chaotic parameter includes:

[0014] Sending a quantum key acquisition request for a receiving device to a quantum key distribution node in the quantum key distribution network;

[0015] receiving a target quantum key and a key identifier of the target quantum key fed back by the quantum key distribution node in response to the quantum key acquisition request;

[0016] The target quantum key is used to encrypt the chaotic parameters to obtain encrypted chaotic parameters.

[0017] In one embodiment, performing compressed sensing processing on the original sensor signal under the control of the measurement matrix to obtain the target signal includes:

[0018] Performing a multiplication operation on the amplified original sensor signal and the measurement matrix to obtain a compressed representation signal of the original sensor signal;

[0019] Extracting features of the compressed representation signal within a preset time interval to obtain target signal features;

[0020] The target signal characteristics are sampled according to the preset time interval to obtain the target signal.

[0021] In a second aspect, the present application provides a signal decryption processing method, which is applied to a receiving device of a sensor network, and the method includes:

[0022] Receiving a target signal, an encrypted chaotic parameter, and a key identifier sent by a sending device in the sensor network;

[0023] Decrypting the encrypted chaotic parameters based on a target quantum key corresponding to the key identifier to obtain chaotic parameters, wherein the target quantum key is a quantum key obtained from a quantum key distribution network;

[0024] The chaotic parameters are used to perform compressed sensing signal recovery on the target signal to obtain the original sensor signal.

[0025] In one embodiment, the receiving device locally stores at least one quantum key and a key identifier of the quantum key that are pre-acquired from a quantum key distribution network;

[0026] The decrypting the encrypted chaotic parameter based on the target quantum key corresponding to the key identifier to obtain the chaotic parameter includes:

[0027] Searching for a target quantum key corresponding to the key identifier from at least one locally stored quantum key;

[0028] When the target quantum key is found, the encrypted chaotic parameters are decrypted using the target quantum key to obtain the chaotic parameters.

[0029] In one embodiment, decrypting the encrypted chaotic parameter based on the target quantum key corresponding to the key identifier to obtain the chaotic parameter includes:

[0030] Based on the key identifier, sending a quantum key acquisition request to a quantum key distribution node in the quantum key distribution network;

[0031] receiving a target quantum key fed back by the quantum key distribution node in response to the quantum key acquisition request;

[0032] The encrypted chaotic parameters are decrypted using the target quantum key to obtain the chaotic parameters.

[0033] In a third aspect, the present application provides a signal processing system, comprising a sensor network and a quantum key network, wherein a transmitting device and a receiving device are deployed in the sensor network, and a quantum key distribution node is deployed in the quantum key network, wherein:

[0034] The transmitting device is configured to randomly generate chaotic parameters, generate a measurement matrix based on the chaotic parameters, and perform compressed sensing undersampling on the original sensor signal under the control of the measurement matrix to obtain a target signal;

[0035] The sending device is further configured to encrypt the chaotic parameters based on the target quantum key obtained from the quantum key distribution network to obtain encrypted chaotic parameters, and send the target signal, the encrypted chaotic parameters, and a key identifier of the target quantum key to a receiving device in the sensor network;

[0036] The receiving device is used to, after receiving the target signal, encrypted chaotic parameters and key identifier sent by the sending device, decrypt the encrypted chaotic parameters based on the target quantum key corresponding to the key identifier to obtain chaotic parameters, and use the chaotic parameters to perform compressed sensing signal recovery on the target signal to obtain the original sensor signal.

[0037] In a fourth aspect, the present application provides a signal encryption processing device, which is applied to a sending device of a sensor network, and the device includes:

[0038] an undersampling module, configured to randomly generate chaotic parameters, generate a measurement matrix based on the chaotic parameters, and perform compressed sensing processing on the original sensor signal under the control of the measurement matrix to obtain a target signal;

[0039] An encryption module, configured to encrypt the chaotic parameters based on a target quantum key obtained from a quantum key distribution network to obtain encrypted chaotic parameters;

[0040] A sending module is configured to send the target signal, the encrypted chaotic parameters, and a key identifier of the target quantum key to a receiving device in the sensor network, so that the receiving device uses the target quantum key corresponding to the key identifier to decrypt the encrypted chaotic parameters to obtain the chaotic parameters, and performs compressed sensing signal recovery on the target signal based on the chaotic parameters to obtain the original sensor signal.

[0041] In one embodiment, the sending device locally stores at least one quantum key and a key identifier of the quantum key pre-acquired from a quantum key distribution network, and the encryption module is specifically configured to:

[0042] Obtaining a target quantum key for communicating with a receiving device from at least one locally stored quantum key;

[0043] The target quantum key is used to encrypt the chaotic parameters to obtain encrypted chaotic parameters.

[0044] In one embodiment, the encryption module is specifically used to:

[0045] Sending a quantum key acquisition request for a receiving device to a quantum key distribution node in the quantum key distribution network;

[0046] receiving a target quantum key and a key identifier of the target quantum key fed back by the quantum key distribution node in response to the quantum key acquisition request;

[0047] The target quantum key is used to encrypt the chaotic parameters to obtain encrypted chaotic parameters.

[0048] In one embodiment, the undersampling module is specifically configured to:

[0049] Performing a multiplication operation on the amplified original sensor signal and the measurement matrix to obtain a compressed representation signal of the original sensor signal;

[0050] Extracting features of the compressed representation signal within a preset time interval to obtain target signal features;

[0051] The target signal characteristics are sampled according to the preset time interval to obtain the target signal.

[0052] In a fifth aspect, the present application provides a signal decryption processing device, which is applied to a receiving device of a sensor network, and the device includes:

[0053] A receiving module, configured to receive a target signal, an encrypted chaotic parameter, and a key identifier sent by a sending device in the sensor network;

[0054] a decryption module, configured to decrypt the encrypted chaotic parameters based on a target quantum key corresponding to the key identifier to obtain chaotic parameters, wherein the target quantum key is a quantum key obtained from a quantum key distribution network;

[0055] The signal recovery module is used to perform compressed sensing signal recovery on the target signal using the chaotic parameters to obtain the original sensor signal.

[0056] In one embodiment, the receiving device locally stores at least one quantum key and a key identifier of the quantum key pre-acquired from a quantum key distribution network, and the decryption module is specifically configured to:

[0057] Searching for a target quantum key corresponding to the key identifier from at least one locally stored quantum key;

[0058] When the target quantum key is found, the encrypted chaotic parameters are decrypted using the target quantum key to obtain the chaotic parameters.

[0059] In one embodiment, the decryption module is specifically configured to:

[0060] Based on the key identifier, sending a quantum key acquisition request to a quantum key distribution node in the quantum key distribution network;

[0061] receiving a target quantum key fed back by the quantum key distribution node in response to the quantum key acquisition request;

[0062] The encrypted chaotic parameters are decrypted using the target quantum key to obtain the chaotic parameters.

[0063] In a sixth aspect, the present application also provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements any one of the above signal encryption processing methods or signal decryption processing methods when executing the computer program.

[0064] In a seventh aspect, the present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, it implements any of the above signal encryption processing methods or signal decryption processing methods.

[0065] In an eighth aspect, the present application also provides a computer program product, comprising a computer program, which, when executed by a processor, implements any one of the above signal encryption processing methods or signal decryption processing methods.

[0066] In the aforementioned signal encryption and decryption processing methods and signal processing systems, a transmitting device in a sensor network can randomly generate chaotic parameters, generate a measurement matrix based on the chaotic parameters, and, under the control of the measurement matrix, perform compressed sensing processing on the original sensor signal to obtain a target signal. The chaotic parameters are then encrypted using a target quantum key obtained from a quantum key distribution network. After obtaining the encrypted chaotic parameters, the target signal, the encrypted chaotic parameters, and a key identifier of the target quantum key are transmitted to a receiving device in the sensor network. The receiving device then decrypts the encrypted chaotic parameters using the target quantum key corresponding to the key identifier to obtain the chaotic parameters. After obtaining the chaotic parameters, the receiving device performs compressed sensing signal recovery on the target signal based on the chaotic parameters to obtain the original sensor signal. The signal encryption processing method, signal decryption processing method and signal processing system provided in the embodiments of the present application are adopted. By performing compressed sensing processing on the original sensor signal, the signal is undersampled at a sampling rate lower than that of the traditional sampling method, the amount of collected data is reduced, the purpose of signal compression is achieved, the transmission burden in the sensor network is effectively reduced, and the efficiency of signal transmission is improved. The quantum key distributed by the quantum key network is used to encrypt the chaotic parameters used to generate the measurement matrix, and the encrypted chaotic parameters are sent to the receiving device, thereby realizing the "one-time one-key" of the measurement matrix and effectively improving the security of signal transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0068] Figure 1Schematic diagram of a flow chart of a signal encryption processing method in one embodiment;

[0069] Figure 2 102 is a flow chart of step 102 in one embodiment;

[0070] Figure 3 is a schematic diagram of compressed sensing processing in one embodiment;

[0071] Figure 4 104 is a flow chart of step 104 in one embodiment;

[0072] Figure 5 is a flow chart of step 104 in another embodiment;

[0073] Figure 6 1 is a flow chart of a signal decryption processing method according to an embodiment;

[0074] Figure 7 FIG. 6 is a flow chart of step 604 in one embodiment;

[0075] Figure 8 is a flow chart of step 604 in another embodiment;

[0076] Figure 9 is a schematic diagram of a signal processing process in one embodiment;

[0077] Figure 10 is a schematic diagram of a signal processing process in another embodiment;

[0078] Figure 11 is a schematic diagram of a signal processing system in one embodiment;

[0079] Figure 12 is a structural block diagram of a signal encryption processing device in one embodiment;

[0080] Figure 13 is a structural block diagram of a signal decryption processing device in one embodiment;

[0081] Figure 14 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0082] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0083] A sensor network is a network of distributed sensor nodes that monitor and collect environmental data. These nodes collaborate through wireless communications to transmit data to a central processing system for analysis. A sensor network consists of sensor nodes, sink nodes, and management nodes. These nodes:

[0084] A sensor node is the basic unit of a sensor network and typically consists of a sensor module, a processor module, a communication module, and a power module. The sensor module is responsible for sensing various physical information such as temperature, humidity, and light intensity; the processor module processes and stores the collected data; the communication module is used to communicate with other nodes; and the power module provides energy to the node.

[0085] A sink node, also called a base station or gateway, collects data from sensor nodes and transmits it to an external network or data processing center. It typically has strong computing, storage, and communication capabilities.

[0086] The management node is responsible for configuring, managing, and maintaining the entire sensor network, including node deployment, network topology control, energy management, etc. The management node can be a standalone device or integrated with the sink node or other nodes.

[0087] Due to the scarcity of sensor node resources and limited storage capacity, how to achieve high-speed signal transmission in sensor networks while improving the security of signal transmission is an urgent problem that needs to be solved.

[0088] The embodiments of the present application provide a signal encryption processing method and a signal decryption processing method, which combine compressed sensing processing and quantum key to realize signal transmission in a sensor network. By performing compressed sensing processing on the original sensor signal, the signal is undersampled at a sampling rate lower than that of the traditional sampling method, the amount of collected data is reduced, the purpose of signal compression is achieved, the transmission burden in the sensor network is effectively reduced, and the efficiency of signal transmission is improved. The quantum key distributed by the quantum key network is used to encrypt the chaotic parameters used to generate the measurement matrix, and the encrypted chaotic parameters are sent to the receiving device, thereby realizing the "one-time one-key" of the measurement matrix and effectively improving the security of signal transmission.

[0089] In one embodiment, Figure 1 As shown, a signal encryption processing method is provided. This embodiment uses the method as an example to illustrate the application of the method to a sending device in a sensor network. The sending device may include a sensor device in the sensor network. In this embodiment, the method includes the following steps 102 to 106, wherein:

[0090] Step 102: randomly generate chaotic parameters, generate a measurement matrix based on the chaotic parameters, and perform compressed sensing processing on the original sensor signal under the control of the measurement matrix to obtain a target signal.

[0091] In the embodiments of this application, chaotic parameters refer to various variables or constants used to describe and control chaotic behavior in a chaotic system. Common methods for generating chaotic parameters include logistic mapping, Lorenz system, and Henon mapping. The following uses the logistic mapping as an example to illustrate the embodiments of this application.

[0092] Exemplarily, chaotic parameters can include system parameters and initial value parameters. The system parameter μ, serving as a control parameter, determines the evolutionary behavior of the chaotic system. When μ∈[3.57,4], the system enters a chaotic state. Because chaotic systems are extremely sensitive to initial conditions, different initial value parameters x0 can produce completely different chaotic trajectories. The sending device can randomly generate system parameters and initial value parameters based on the chaotic system: randomly selecting an initial value x0∈(0,1), such as x0=0.5; and randomly selecting control parameters: selecting a μ value within the chaotic region, such as μ=3.8.

[0093] After generating the chaotic parameters, a measurement matrix can be generated based on the chaotic parameters. For example, a Logistic chaotic sequence can be generated based on the chaotic parameters through multiple rounds of iterations, and the generation method is shown in the following formula (1):

[0094] Formula (1)

[0095] in, ∈[0,1] is the initial value parameter The value after the nth iteration, is a system parameter.

[0096] After obtaining the Logistic chaotic sequence, the Logistic chaotic sequence can be sampled with a sufficient step size to form an initial measurement matrix that meets the RIP (Restricted Isometry Property) condition. The extraction method can refer to the following formula (2):

[0097] Formula (2)

[0098] in, is the element in the initial measurement matrix, t represents the initial value of the Logistic chaotic sequence, and d represents the sampling distance. After normalizing the initial measurement matrix, we can get the M×N measurement matrix , refer to formula (3):

[0099] Formula (3)

[0100] in, Used to normalize a matrix.

[0101] After obtaining the measurement matrix, compressed sensing processing can be performed on the raw sensor signals based on the measurement matrix to obtain the target signal. The raw sensor signals can be signals collected from the physical environment, such as a temperature sensor collecting signals of ambient temperature changes over time, or an accelerometer collecting acceleration signals of an object in motion. These signals are usually analog signals and need to be converted to digital signals using an ADC (analog to digital converter).

[0102] In an exemplary embodiment, referring to Figure 2 As shown, in step 102, under the control of the measurement matrix, compressed sensing processing is performed on the original sensor signal to obtain the target signal, which may include the following steps 202 to 206, wherein:

[0103] Step 202: multiplying the amplified original sensor signal with the measurement matrix to obtain a compressed representation signal of the original sensor signal;

[0104] Step 204: extracting features from the compressed representation signal within a preset time interval to obtain target signal features;

[0105] Step 206: Sample the target signal characteristics at preset time intervals to obtain the target signal.

[0106] Reference Figure 3 Figure 1 shows the process of performing compressed sensing processing on raw sensor signals to obtain target signals. Because the raw sensor signals collected by the sensor can be very weak, amplification is necessary to improve the accuracy and reliability of subsequent processing. This can be achieved using an amplifier circuit, such as an operational amplifier. The appropriate amplification factor can be selected based on the signal characteristics and subsequent processing requirements.

[0107] The function of the measurement matrix is to compress the high-dimensional original sensor signal into a low-dimensional space. The compressed representation signal can be obtained by multiplying the amplified original sensor signal with the measurement matrix.

[0108] Furthermore, an appropriate preset time interval can be determined based on the actual application requirements and signal characteristics. For example, a real-time monitoring system may require a shorter time interval to ensure timely capture of signal changes; for slowly varying signals, a longer time interval can be selected. The compressed representation signal is divided into multiple time windows according to the preset time interval. Assuming the signal sampling frequency is fs, the number of samples contained in each time window is n = Δt × fs, where Δt is the preset time interval.

[0109] In each time window, feature extraction is performed on the compressed representation signal, including extracting time domain features and / or frequency domain features. For example, the compressed representation signal can enter the integration module " to t", and perform feature extraction on the compressed representation signal to obtain the target signal features.

[0110] After extracting the target signal features corresponding to the compressed representation signals of each time window, these extracted target signal features can be sampled. For example, the timing control module samples the target signal features at the specific time "t = nT." Finally, the sampled signals are fed into the "AD sampling" module to convert the analog signals into digital signals, yielding the target signal.

[0111] Step 104: encrypt the chaotic parameters based on the target quantum key obtained from the quantum key distribution network to obtain encrypted chaotic parameters.

[0112] In the embodiments of the present application, the sending device can obtain a key pair for encrypting chaotic parameters by interacting with a quantum key distribution node in a quantum key distribution network. The key pair includes a target quantum key and a key identifier of the target quantum key. Alternatively, the sending device can pre-acquire a large number of key pairs and store them locally on the sending device, which is not specifically limited in the embodiments of the present application.

[0113] In an exemplary embodiment, the sending device locally stores at least one quantum key and a key identifier of the quantum key obtained in advance from the quantum key distribution network. Figure 4 As shown, in step 104, the chaotic parameters are encrypted based on the target quantum key obtained from the quantum key distribution network to obtain the encrypted chaotic parameters, which may include the following steps 402 to 404, wherein:

[0114] Step 402: Obtain a target quantum key for communicating with a receiving device from at least one locally stored quantum key;

[0115] Step 404: encrypt the chaotic parameters using the target quantum key to obtain encrypted chaotic parameters.

[0116] In this embodiment, any entity in the sensor network (e.g., transmitting device A and receiving device B) is pre-bound to a QKD node in the QKD network. Each entity is bound to only one QKD node, and mutual authentication is performed between the entity and the corresponding QKD node. For example, transmitting device A is bound to QKD-A node, and receiving device B is bound to QKD-B node.

[0117] Transmitting device A can send a quantum key batch acquisition request to the QKD-A node. The quantum key batch acquisition request can carry the device identification of receiving device B, which is used to instruct the batch acquisition of quantum keys for communication with receiving device B. After receiving the quantum key batch acquisition request sent by transmitting device A, the QKD-A node searches for the QKD-B node bound to receiving device B in the QKD network.

[0118] For example, QKD-A and QKD-B can negotiate to generate multiple quantum key pairs (quantum keys and key identifiers corresponding to the quantum keys) required for communication between transmitting device A and receiving device B. Alternatively, if QKD-B has pre-set the communication key for receiving device B, QKD-B will inform QKD-A of these pre-set quantum key pairs.

[0119] After the QKD-A node obtains multiple quantum key pairs for communication with the receiving device B, it can send the multiple quantum key pairs to the sending device A. After receiving the multiple quantum key pairs, the sending device A can store them locally.

[0120] After acquiring the target signal, sending device A can randomly select one from multiple locally stored quantum key pairs used to communicate with receiving device B as the target quantum key to encrypt the chaotic parameters, thereby obtaining the encrypted chaotic parameters. In one example, the used quantum key pair will be discarded by sending device A.

[0121] The sending device A can periodically obtain quantum keys for communicating with the receiving device B in batches from the QKD-A node. If multiple pre-acquired quantum keys are discarded within a cycle and the next acquisition cycle has not yet arrived, the sending device A can send a quantum key acquisition request to the QKD-A node. The quantum key acquisition request can carry the device identification of the receiving device B, which is used to indicate the acquisition of a quantum key pair for communicating with the receiving device B. The method for obtaining the quantum key pair is similar to the method for obtaining quantum key pairs in batches as mentioned above. Please refer to the relevant description in the previous embodiment, and will not be repeated here in the embodiment of this application.

[0122] In an exemplary embodiment, referring to Figure 5As shown, in step 104, the chaotic parameters are encrypted based on the target quantum key obtained from the quantum key distribution network to obtain the encrypted chaotic parameters, which may include the following steps 502 to 506, wherein:

[0123] Step 502: Send a quantum key acquisition request for a receiving device to a quantum key distribution node in a quantum key distribution network;

[0124] Step 504: receiving the target quantum key and the key identifier of the target quantum key fed back by the quantum key distribution node in response to the quantum key acquisition request;

[0125] Step 506: Use the target quantum key to encrypt the chaotic parameters to obtain encrypted chaotic parameters.

[0126] In this embodiment, any entity in the sensor network (e.g., transmitting device A and receiving device B) is pre-bound to a QKD node in the QKD network. Each entity is bound to only one QKD node, and mutual authentication is performed between the entity and the corresponding QKD node. For example, transmitting device A is bound to QKD-A node, and receiving device B is bound to QKD-B node.

[0127] After acquiring the target signal, transmitting device A can send a quantum key acquisition request to the QKD-A node. This quantum key acquisition request can carry the device identification of receiving device B, which is used to instruct the acquisition of the quantum key for communicating with receiving device B. After receiving the quantum key acquisition request sent by transmitting device A, the QKD-A node searches for the QKD-B node bound to receiving device B in the QKD network.

[0128] For example, QKD-A and QKD-B can negotiate to generate the quantum key pair (quantum key and key identifier corresponding to the quantum key) required for communication between transmitting device A and receiving device B. Alternatively, if QKD-B has pre-set the communication key of receiving device B, QKD-B will inform QKD-A of the pre-set quantum key pair.

[0129] After the QKD-A node obtains the quantum key pair for communication with the receiving device B, it can send the quantum key pair to the sending device A. After receiving it, the sending device A can use the quantum key in the quantum key pair as the target quantum key to encrypt the chaotic parameters and obtain the encrypted chaotic parameters.

[0130] Among them, the chaotic parameters are encrypted using a quantum key, that is, the chaotic parameters are encrypted using an encryption function with the participation of a quantum key. The encryption function may include but is not limited to symmetric encryption algorithms (such as AES (Advanced Encryption Standard), DES (Data Encryption Standard)), asymmetric encryption algorithms (such as RSA (Rivest-Shamir-Adleman), ECC (Elliptic Curve Cryptography)), hash algorithms (such as SHA-1 (Secure Hash Algorithm-1), SHA-256 (Secure Hash Algorithm-256)), etc.

[0131] Step 106: Send the target signal, the encrypted chaotic parameters, and the key identifier of the target quantum key to a receiving device in the sensor network, so that the receiving device uses the target quantum key corresponding to the key identifier to decrypt the encrypted chaotic parameters to obtain the chaotic parameters, and performs compressed sensing signal recovery on the target signal based on the chaotic parameters to obtain the original sensor signal.

[0132] In an embodiment of the present application, after obtaining the target signal and encrypted chaotic parameters, the target signal, encrypted chaotic parameters, and key identifier of the target quantum key can be sent to a receiving device. After receiving the target signal, encrypted chaotic parameters, and key identifier of the target quantum key, the receiving device can obtain the target quantum key based on the key identifier of the target quantum key, use the target quantum key to decrypt the encrypted chaotic parameters, and obtain the chaotic parameters. Then, based on the chaotic parameters, a measurement matrix can be generated. Based on the measurement matrix, compressed sensing signal recovery is performed on the target signal to obtain the original sensor signal. The process of compressed sensing signal recovery will be described in the embodiment on the receiving device side and will not be repeated here in the embodiment of the present application.

[0133] In the above-mentioned signal encryption processing method, the sending device in the sensor network can randomly generate chaotic parameters, generate a measurement matrix based on the chaotic parameters, and perform compressed sensing processing on the original sensor signal under the control of the measurement matrix to obtain the target signal. The chaotic parameters are encrypted based on the target quantum key obtained from the quantum key distribution network. After obtaining the encrypted chaotic parameters, the target signal, the encrypted chaotic parameters and the key identifier of the target quantum key are sent to the receiving device in the sensor network, so that the receiving device uses the target quantum key corresponding to the key identifier to decrypt the encrypted chaotic parameters to obtain the chaotic parameters. After that, the target signal is subjected to compressed sensing signal recovery based on the chaotic parameters to obtain the original sensor signal. The signal encryption processing method provided by the embodiment of the present application is adopted. By performing compressed sensing processing on the original sensor signal, the signal is undersampled at a sampling rate lower than that of the traditional sampling method, the amount of collected data is reduced, the purpose of signal compression is achieved, the transmission burden in the sensor network is effectively reduced, the efficiency of signal transmission is improved, and the quantum key distributed by the quantum key network is used to encrypt the chaotic parameters used to generate the measurement matrix, and the encrypted chaotic parameters are sent to the receiving device, thereby achieving the "one-time one-key" of the measurement matrix and effectively improving the security of signal transmission.

[0134] In one embodiment, Figure 6 As shown, a signal decryption processing method is provided. This embodiment uses the method applied to a receiving device in a sensor network as an example for illustration. The receiving device may include a sensor device, a server, and other devices in the sensor network. In this embodiment, the method includes the following steps 602 to 606, wherein:

[0135] Step 602: Receive a target signal, encrypted chaotic parameters, and a key identifier sent by a sending device in the sensor network.

[0136] Step 604: decrypt the encrypted chaotic parameters based on the target quantum key corresponding to the key identifier to obtain the chaotic parameters. The target quantum key is the quantum key obtained from the quantum key distribution network.

[0137] Step 606: Perform compressed sensing signal recovery on the target signal using the chaotic parameters to obtain the original sensor signal.

[0138] In the embodiment of the present application, the process of the sending device collecting the target signal and encrypting the chaotic parameters to obtain the encrypted chaotic parameters can refer to the relevant description of the aforementioned embodiment, and will not be repeated here in the embodiment of the present application.

[0139] After the receiving device receives the target signal, encrypted chaotic parameters and key identifier sent by the sending device, it can first obtain the corresponding target quantum key based on the key identifier, and then use the target quantum key to decrypt the encrypted chaotic parameters. After obtaining the chaotic parameters, a measurement matrix is generated based on the chaotic parameters, and then compressed sensing signal recovery is performed on the target signal based on the measurement matrix to obtain the original sensor signal.

[0140] The process of decrypting the encrypted chaotic parameters using the target quantum key can be performed using a decryption function that is consistent with the encryption function used by the transmitting device. After decrypting the chaotic parameters, the process of generating a measurement matrix based on the chaotic parameters can be described in the relevant description of the previous embodiment and will not be repeated in this embodiment.

[0141] In the embodiment of the present application, compressed sensing signal recovery is the process of recovering the original sensor signal from the target signal. This recovery process is described as the L0 norm problem: , where A is the sensing matrix, is the measurement matrix and the sparse matrix s is the sparse vector of the original sensor signal, that is, a vector in which most elements are 0 or close to 0, and its relationship with the original sensor signal x is .

[0142] In one example, an iterative hard thresholding (IHT) algorithm can be used to solve the sparse vector of the original sensor signal. The algorithm process includes:

[0143] Input: sensor matrix A, target signal, and signal sparsity k. The signal sparsity k represents the approximate number of non-zero elements in the sparse vector s and is an important parameter in the algorithm, used to control the iterative process and the sparse representation of the signal.

[0144] During the initialization phase, the signal to be recovered, s0, can be set to 0: the initial sparse vector is set to an all-zero vector, which is the starting point of the iteration. The number of iterations, t, can be set to 0: the number of iterations is recorded, starting from 0. The residual, R0, can be set to 0: the residual is initialized to 0. The residual is used to measure the difference between the current recovered signal and the target signal.

[0145] During the loop iteration phase, the following execution processes are included:

[0146] Iteration condition t<2k: limits the maximum number of iterations to 2k to prevent the algorithm from looping infinitely.

[0147] t=t+1: Increase the number of iterations by 1 for each iteration.

[0148] :This is the iterative update formula for sparse vectors.k It is a hard threshold operation function, which retains the k elements with the largest absolute value in the vector and sets the rest to 0. t , so that it gradually approaches the sparse vector s of the original sensor signal.

[0149] : Calculate the residual under the current iteration and use the L2 norm to measure the target signal and the sparse vector s recovered by the current t The difference between the reconstructed signals Ast.

[0150] : This is the condition for stopping the iteration. When the difference between the residuals of two consecutive iterations is less than a pre-set threshold ε, the algorithm is considered to have converged, that is, the recovered signal is close enough to the true signal, and the iteration is stopped.

[0151] Output part: the final output s=s t It is the sparse vector recovered by the iterative hard threshold algorithm, and then the estimated value of the original sensor signal x can be obtained through x=Ψs, that is, the original sensor signal can be recovered.

[0152] The signal decryption processing method provided in the embodiment of the present application performs compressed sensing processing on the original sensor signal and undersamples the signal at a sampling rate lower than that of the traditional sampling method, thereby reducing the amount of collected data and achieving the purpose of signal compression. It effectively reduces the transmission burden in the sensor network and improves the efficiency of signal transmission. The quantum key distributed by the quantum key network is used to encrypt the chaotic parameters used to generate the measurement matrix, and the encrypted chaotic parameters are sent to the receiving device, thereby realizing the "one-time one-key" of the measurement matrix and effectively improving the security of signal transmission.

[0153] In an exemplary embodiment, the receiving device locally stores at least one quantum key and a key identifier of the quantum key obtained in advance from the quantum key distribution network. Figure 7 As shown, in step 604, the encrypted chaotic parameters are decrypted based on the target quantum key corresponding to the key identifier to obtain the chaotic parameters, which may include the following steps 702 to 704, wherein:

[0154] Step 702: searching for a target quantum key corresponding to the key identifier from at least one locally stored quantum key;

[0155] Step 704: When the target quantum key is found, the encrypted chaotic parameters are decrypted using the target quantum key to obtain the chaotic parameters.

[0156] In this embodiment, any entity in the sensor network (e.g., transmitting device A and receiving device B) is pre-bound to a QKD node in the QKD network. Each entity is bound to only one QKD node, and mutual authentication is performed between the entity and the corresponding QKD node. For example, transmitting device A is bound to QKD-A node, and receiving device B is bound to QKD-B node.

[0157] Transmitting device A can send a quantum key batch acquisition request to the QKD-A node. The quantum key batch acquisition request can carry the device identification of receiving device B, which is used to instruct the batch acquisition of quantum keys for communication with receiving device B. After receiving the quantum key batch acquisition request sent by transmitting device A, the QKD-A node searches for the QKD-B node bound to receiving device B in the QKD network.

[0158] For example, QKD-node A and QKD-node B can negotiate to generate multiple quantum key pairs (quantum keys and key identifiers corresponding to the quantum keys) required for communication between transmitting device A and receiving device B. After negotiation, both QKD-node A and QKD-B locally store these multiple quantum key pairs. Alternatively, QKD-node B can pre-set the communication key on QKD-node B, and QKD-node B will notify QKD-node A of these multiple pre-set quantum key pairs.

[0159] Receiving device B can obtain multiple quantum key pairs required for communication from the QKD-B node in advance and store them locally. After receiving the key identifier sent by sending device A, receiving device B can search for the target quantum key corresponding to the key identifier from the multiple quantum key pairs stored locally. After finding the target quantum key, it can use it to decrypt the encrypted chaotic parameters to obtain the chaotic parameters.

[0160] In another example, referring to Figure 8 As shown, in step 604, the encrypted chaotic parameters are decrypted based on the target quantum key corresponding to the key identifier to obtain the chaotic parameters, which may include steps 802 to 806, wherein:

[0161] Step 802: Send a quantum key acquisition request to a quantum key distribution node in the quantum key distribution network based on the key identifier;

[0162] Step 804: receiving the target quantum key fed back by the quantum key distribution node in response to the quantum key acquisition request;

[0163] Step 806: Decrypt the encrypted chaotic parameters using the target quantum key to obtain the chaotic parameters.

[0164] In this embodiment, any entity in the sensor network (e.g., transmitting device A and receiving device B) is pre-bound to a QKD node in the QKD network. Each entity is bound to only one QKD node, and mutual authentication is performed between the entity and the corresponding QKD node. For example, transmitting device A is bound to QKD-A node, and receiving device B is bound to QKD-B node.

[0165] After acquiring the target signal, transmitting device A can send a quantum key acquisition request to the QKD-A node. This quantum key acquisition request can carry the device identification of receiving device B, which is used to instruct the acquisition of the quantum key for communicating with receiving device B. After receiving the quantum key acquisition request sent by transmitting device A, the QKD-A node searches for the QKD-B node bound to receiving device B in the QKD network.

[0166] For example, QKD-A and QKD-B can negotiate to generate the quantum key pair (quantum key and key identifier corresponding to the quantum key) required for communication between transmitting device A and receiving device B. After negotiation, both QKD-A and QKD-B nodes locally store the quantum key pair. Alternatively, if QKD-B has pre-set the communication key for receiving device B, QKD-B will notify QKD-A of the pre-set quantum key pair.

[0167] After receiving the key identifier sent by the sending device A, the receiving device B can send a quantum key acquisition request to the QKD-B node. The QKD-B node can search for the corresponding quantum key based on the key identifier carried in the quantum key acquisition request, and after the search, the quantum key is fed back to the receiving device B as the target quantum key. Then, the receiving device B uses the target quantum key to decrypt the encrypted chaotic parameters to obtain the chaotic parameters.

[0168] In order to enable those skilled in the art to better understand the embodiments of the present application, the embodiments of the present application are described below with reference to specific examples.

[0169] In Example 1, the sending device includes quantum key acquisition, chaos parameter encryption, chaos sequence generation and measurement matrix generation, compressed sensing signal acquisition, and data transmission functions. Figure 9 As shown, the operation steps include:

[0170] (1) Randomly generate chaotic parameters, including system parameters and initial parameters;

[0171] (2) Generate chaotic sequence and measurement matrix;

[0172] (3) Under the control of the measurement matrix, compressed sensing processing is performed on the original sensor signal to obtain the target signal;

[0173] (4) The sending device obtains the quantum key and key identifier from the QKD network;

[0174] (5) Encrypting the chaotic parameters using quantum keys to obtain encrypted chaotic parameters;

[0175] (6) Transmit the target signal, encrypted chaotic parameters and key identifier to the receiving device.

[0176] The receiving device includes quantum key acquisition, chaotic parameter decryption, chaotic sequence generation and measurement matrix generation, compressed sensing signal recovery, and data transmission functions. Figure 9 As shown, the operation steps include:

[0177] (1) Extract the target signal, encryption chaos parameters and key identifier from the received data;

[0178] (2) Use the key identifier to obtain the corresponding quantum key from the QKD network;

[0179] (3) Use the obtained quantum key to decrypt the encrypted chaotic parameters to obtain the chaotic parameters;

[0180] (4) Using chaotic parameters, including system parameters and initial parameters, to generate chaotic sequences and measurement matrices, the generation method is consistent with that of the sending device;

[0181] (5) With the participation of the measurement matrix, compressed sensing signal recovery is performed to obtain the original sensor signal.

[0182] In Example 2, the sending device and the receiving device obtain a large number of quantum keys and corresponding identifiers from the QKD nodes of the QKD network in advance and store them locally. Figure 10 As shown, the sending end and the receiving end then perform the following steps:

[0183] Sending end:

[0184] (1) Randomly generate chaotic parameters, including system parameters and initial parameters;

[0185] (2) Generate chaotic sequence and measurement matrix;

[0186] (3) Under the control of the measurement matrix, compressed sensing processing is performed on the original sensor signal to obtain the target signal;

[0187] (4) Encrypting the chaotic parameters using quantum keys to obtain encrypted chaotic parameters;

[0188] (5) Transmit the target signal, encrypted chaotic parameters and key identifier to the receiving device.

[0189] Receiver:

[0190] (1) Extract the target signal, encryption chaos parameters and key identifier from the received data;

[0191] (2) Retrieve the quantum key used for this round of decryption based on the key identifier;

[0192] (3) Use the quantum key to decrypt the encrypted chaotic parameters to obtain the chaotic parameters;

[0193] (4) Using chaotic parameters, including system parameters and initial parameters, to generate chaotic sequences and measurement matrices, the generation method is consistent with that of the sending device;

[0194] (5) With the participation of the measurement matrix, compressed sensing signal recovery is performed on the target to obtain the original sensor signal.

[0195] The signal encryption and decryption processing methods provided in the embodiments of this application utilize quantum key distribution to achieve unified key management for the network, even under the limited AD sampling, storage, and computational capabilities of sensors. This reduces the resource consumption of key maintenance by sampling and processing nodes. Furthermore, to reduce the amount of data and sampling device requirements in IoT sensors, a compressed sensing method based on a chaotic measurement matrix is introduced for data acquisition, completing signal acquisition while undersampling the signal. Key encryption using quantum key distribution allows for the transmission of chaotic parameters without the need to transmit the entire measurement matrix.

[0196] Reference Figure 11 As shown, an embodiment of the present application provides a signal processing system, including a sensor network and a quantum key network, wherein a transmitting device and a receiving device are deployed in the sensor network, and a quantum key distribution node is deployed in the quantum key network, wherein:

[0197] a transmitting device, configured to randomly generate chaotic parameters, generate a measurement matrix based on the chaotic parameters, and perform compressed sensing processing on the original sensor signal under the control of the measurement matrix to obtain a target signal;

[0198] The sending device is further used to encrypt the chaotic parameters based on the target quantum key obtained from the quantum key distribution network to obtain the encrypted chaotic parameters, and send the target signal, the encrypted chaotic parameters and the key identifier of the target quantum key to the receiving device in the sensor network;

[0199] The receiving device is used to decrypt the encrypted chaotic parameters based on the target quantum key corresponding to the key identifier after receiving the target signal, encrypted chaotic parameters and key identifier sent by the sending device to obtain the chaotic parameters, and use the chaotic parameters to perform compressed sensing signal recovery on the target signal to obtain the original sensor signal.

[0200] In the embodiments of the present application, the sending device is usually a sensor, and the receiving device is a server or sensor device. The operations performed by the sending device mainly include: chaotic parameter generation, chaotic sequence generation and measurement matrix generation, compressed sensing signal acquisition, QKD network key acquisition, chaotic parameter encryption, and data transmission functions. The operations performed by the receiving device mainly include: data reception, QKD network key acquisition, chaotic parameter decryption, chaotic sequence generation and measurement matrix generation, and compressed sensing signal recovery. The specific process can be referred to the relevant description of the aforementioned embodiment, and will not be repeated here in the embodiments of the present application.

[0201] In an embodiment of the present application, a method for obtaining quantum keys by interfacing a sensor network with a QKD network is provided, including both static and dynamic acquisition methods. A transmitting device can interface with the QKD network (typically via optical fiber or deployed within the same security domain) and obtain quantum keys and key identifiers through the QKD network's key distribution nodes. Specifically, this includes:

[0202] Method 1: Static Acquisition. Before performing compressed sensing processing, the sending device obtains a large number of quantum keys and corresponding identifiers from the QKD nodes of the QKD network and stores them locally. When subsequently encrypting the chaotic parameters, the corresponding quantum keys and key identifiers are obtained locally for encryption.

[0203] Method 2: Dynamic Acquisition. After generating a measurement matrix based on the chaotic matrix and using it to sample the signal, the transmitting device obtains a quantum key and key identifier from the QKD network. The new quantum key and identifier are then acquired in real time during the next compressed sampling.

[0204] After obtaining the quantum key, the chaotic parameters (including the system parameter μ and the initial value parameter x0) can be encrypted using the quantum key. This means that the chaotic parameter plaintext P(μ, x0) is encrypted using an encryption function E (such as AES) with the quantum key Qk, generating the chaotic parameter ciphertext C, where C = E(Qk, P). The specific encryption algorithm to be used is negotiated in advance by both parties over a classical channel.

[0205] The sending device can transmit the encrypted chaotic parameters, key identifier and collected target signal to the receiving device.

[0206] Similarly, the receiving device can also connect to the QKD network (usually via optical fiber or deployed in the same security domain) and obtain the quantum key and key identifier through the QKD network key distribution node. Specifically, it includes:

[0207] Method 1: Static acquisition. The receiving device obtains a large number of quantum keys and corresponding identifiers from the QKD node of the QKD network in advance and stores them locally. When decrypting the chaotic parameters, the corresponding quantum key is retrieved locally based on the key identifier sent by the sending device.

[0208] Method 2: Dynamic Acquisition. Before signal recovery, the receiving device requests the corresponding quantum key from the QKD network node in real time based on the key identifier sent by the transmitting device. Before the next signal recovery, the receiving device requests a new quantum key from the QKD network node in real time based on the new key identifier.

[0209] The receiving device can retrieve the quantum key Qk used for this round of decryption based on the key identifier, and use the same decryption function D (such as AES) to decrypt the encrypted chaotic parameter C with the participation of the quantum key Qk to obtain the chaotic parameter P (μ, x0), P = D (Qk, C).

[0210] The receiving device can generate a chaotic sequence based on the chaotic parameters and further generate a measurement matrix. The chaotic sequence and measurement matrix generation methods are consistent with those of the sensor. After obtaining the measurement matrix, the compressed sensing signal recovery of the target signal is performed based on the measurement matrix to obtain the original sensor signal.

[0211] The signal processing system provided in the embodiments of this application combines the Internet of Things with a quantum QKD network. The QKD network's key distribution nodes provide quantum keys and key identifiers to IoT sensor nodes. Quantum keys provide a secure transmission channel for sensor signal acquisition and encryption. Keys are centrally managed and distributed by the QKD network, reducing the overhead of key transmission and maintenance for IoT devices. Data sampling, compression, and encryption are implemented simultaneously, improving signal acquisition and processing efficiency and reducing sensor resource overhead. Chaotic parameters are encrypted using quantum keys, achieving a one-time, one-pad measurement matrix and ensuring the security of signal sampling and recovery. A specific implementation method for combining the Internet of Things with a quantum QKD network is provided, including static and dynamic acquisition methods, to synchronize keys between senders and receivers, ensuring the consistency of their quantum keys.

[0212] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0213] Based on the same inventive concept, embodiments of the present application also provide a signal encryption processing device for implementing the aforementioned signal encryption processing method. The implementation solution provided by this device is similar to the implementation solution described in the aforementioned method. Therefore, the specific limitations of one or more signal processing device embodiments provided below can be found in the above-mentioned limitations of the signal encryption processing method and will not be repeated here.

[0214] In an exemplary embodiment, Figure 12 As shown, a signal encryption processing device 1200 is provided, comprising: an undersampling module 1202, an encryption module 1204 and a sending module 1206, wherein:

[0215] An undersampling module 1202 is configured to randomly generate chaotic parameters, generate a measurement matrix based on the chaotic parameters, and perform compressed sensing processing on the original sensor signal under the control of the measurement matrix to obtain a target signal;

[0216] An encryption module 1204 is configured to encrypt the chaotic parameters based on a target quantum key obtained from a quantum key distribution network to obtain encrypted chaotic parameters;

[0217] The sending module 1206 is configured to send the target signal, the encrypted chaotic parameters, and the key identifier of the target quantum key to a receiving device in the sensor network, so that the receiving device uses the target quantum key corresponding to the key identifier to decrypt the encrypted chaotic parameters to obtain the chaotic parameters, and performs compressed sensing signal recovery on the target signal based on the chaotic parameters to obtain the original sensor signal.

[0218] The signal encryption processing device provided in the embodiment of the present application performs compressed sensing processing on the original sensor signal and undersamples the signal at a sampling rate lower than that of the traditional sampling method, thereby reducing the amount of collected data and achieving the purpose of signal compression. It effectively reduces the transmission burden in the sensor network and improves the efficiency of signal transmission. The quantum key distributed by the quantum key network is used to encrypt the chaotic parameters used to generate the measurement matrix, and the encrypted chaotic parameters are sent to the receiving device, thereby realizing the "one-time one-key" of the measurement matrix and effectively improving the security of signal transmission.

[0219] In one embodiment, the sending device locally stores at least one quantum key and a key identifier of the quantum key pre-acquired from a quantum key distribution network, and the encryption module 1204 is specifically configured to:

[0220] Obtaining a target quantum key for communicating with a receiving device from at least one locally stored quantum key;

[0221] The target quantum key is used to encrypt the chaotic parameters to obtain encrypted chaotic parameters.

[0222] In one embodiment, the encryption module 1204 is specifically configured to:

[0223] Sending a quantum key acquisition request for a receiving device to a quantum key distribution node in the quantum key distribution network;

[0224] receiving a target quantum key and a key identifier of the target quantum key fed back by the quantum key distribution node in response to the quantum key acquisition request;

[0225] The target quantum key is used to encrypt the chaotic parameters to obtain encrypted chaotic parameters.

[0226] In one embodiment, the undersampling module 1202 is specifically configured to:

[0227] Performing a multiplication operation on the amplified original sensor signal and the measurement matrix to obtain a compressed representation signal of the original sensor signal;

[0228] Extracting features of the compressed representation signal within a preset time interval to obtain target signal features;

[0229] The target signal characteristics are sampled according to the preset time interval to obtain the target signal.

[0230] Based on the same inventive concept, embodiments of the present application also provide a signal decryption processing device for implementing the aforementioned signal decryption processing method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more signal processing device embodiments provided below can be found in the aforementioned limitations of the signal decryption processing method and will not be further elaborated here.

[0231] In an exemplary embodiment, Figure 13 As shown, a signal decryption processing device 1300 is provided, comprising: a receiving module 1302, a decryption module 1304 and a signal recovery module 1306, wherein:

[0232] The receiving module 1302 is configured to receive a target signal, an encrypted chaotic parameter, and a key identifier sent by a sending device in the sensor network;

[0233] A decryption module 1304 is configured to decrypt the encrypted chaotic parameters based on a target quantum key corresponding to the key identifier to obtain chaotic parameters, where the target quantum key is a quantum key obtained from a quantum key distribution network;

[0234] The signal recovery module 1306 is configured to perform compressed sensing signal recovery on the target signal using the chaotic parameters to obtain an original sensor signal.

[0235] The signal decryption processing device provided in the embodiment of the present application performs compressed sensing processing on the original sensor signal and undersamples the signal at a sampling rate lower than that of the traditional sampling method, thereby reducing the amount of collected data and achieving the purpose of signal compression. It effectively reduces the transmission burden in the sensor network and improves the efficiency of signal transmission. The quantum key distributed by the quantum key network is used to encrypt the chaotic parameters used to generate the measurement matrix, and the encrypted chaotic parameters are sent to the receiving device, thereby realizing the "one-time one-key" of the measurement matrix and effectively improving the security of signal transmission.

[0236] In one embodiment, the receiving device locally stores at least one quantum key and a key identifier of the quantum key pre-acquired from a quantum key distribution network, and the decryption module 1304 is specifically configured to:

[0237] Searching for a target quantum key corresponding to the key identifier from at least one locally stored quantum key;

[0238] When the target quantum key is found, the encrypted chaotic parameters are decrypted using the target quantum key to obtain the chaotic parameters.

[0239] In one embodiment, the decryption module 1304 is specifically configured to:

[0240] Based on the key identifier, sending a quantum key acquisition request to a quantum key distribution node in the quantum key distribution network;

[0241] receiving a target quantum key fed back by the quantum key distribution node in response to the quantum key acquisition request;

[0242] The encrypted chaotic parameters are decrypted using the target quantum key to obtain the chaotic parameters.

[0243] Each module in the aforementioned signal encryption and decryption processing devices may be implemented in whole or in part through software, hardware, or a combination thereof. Each module may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0244] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 14As shown. The computer device includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via wired or wireless means, and the wireless means can be implemented via Wi-Fi, a mobile cellular network, near-field communication (NFC), or other technologies. When executed by the processor, the computer program implements a signal encryption processing method or a signal decryption processing method. The display unit of the computer device is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0245] Those skilled in the art will understand that Figure 14 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0246] In one embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0247] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0248] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0249] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data permitted by the user or fully permitted by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0250] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0251] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0252] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A signal encryption processing method, characterized in that: A transmitting device applied to a sensor network, the method comprising: randomly generating chaotic parameters, generating a measurement matrix based on the chaotic parameters, and performing compressed sensing processing on the original sensor signal under the control of the measurement matrix to obtain a target signal; Encrypting the chaotic parameters based on a target quantum key obtained from a quantum key distribution network to obtain encrypted chaotic parameters, wherein the target quantum key includes a quantum key obtained by the sending device through real-time interaction with a quantum key distribution node in the quantum key distribution network, or a quantum key obtained in advance from the quantum key distribution network and stored locally by the sending device; The target signal, the encrypted chaotic parameters, and a key identifier of the target quantum key are sent to a receiving device in the sensor network, so that the receiving device uses the target quantum key corresponding to the key identifier to decrypt the encrypted chaotic parameters to obtain the chaotic parameters, generates a measurement matrix based on the chaotic parameters, and performs compressed sensing signal recovery on the target signal based on the measurement matrix to obtain the original sensor signal.

2. The method according to claim 1, characterized in that The sending device locally stores at least one quantum key and a key identifier of the quantum key that are pre-acquired from a quantum key distribution network; The step of encrypting the chaotic parameters based on the target quantum key obtained from the quantum key distribution network to obtain the encrypted chaotic parameters comprises: Obtaining a target quantum key for communicating with a receiving device from at least one locally stored quantum key; The target quantum key is used to encrypt the chaotic parameters to obtain encrypted chaotic parameters.

3. The method according to claim 1, characterized in that The step of encrypting the chaotic parameters based on the target quantum key obtained from the quantum key distribution network to obtain the encrypted chaotic parameters comprises: Sending a quantum key acquisition request for a receiving device to a quantum key distribution node in the quantum key distribution network; receiving a target quantum key and a key identifier of the target quantum key fed back by the quantum key distribution node in response to the quantum key acquisition request; The target quantum key is used to encrypt the chaotic parameters to obtain encrypted chaotic parameters.

4. The method according to any one of claims 1 to 3, characterized in that The method of performing compressed sensing processing on the original sensor signal under the control of the measurement matrix to obtain the target signal includes: Performing a multiplication operation on the amplified original sensor signal and the measurement matrix to obtain a compressed representation signal of the original sensor signal; Extracting features of the compressed representation signal within a preset time interval to obtain target signal features; The target signal characteristics are sampled according to the preset time interval to obtain the target signal.

5. A signal decryption processing method, characterized in that: The method is applied to a receiving device of a sensor network, and includes: Receiving a target signal, an encrypted chaotic parameter, and a key identifier sent by a sending device in the sensor network; decrypting the encrypted chaotic parameters based on a target quantum key corresponding to the key identifier to obtain chaotic parameters, wherein the target quantum key includes a quantum key obtained by the receiving device through real-time interaction with a quantum key distribution node in a quantum key distribution network, or a quantum key obtained in advance by the receiving device from the quantum key distribution network and stored locally; A measurement matrix is generated based on the chaotic parameters, and compressed sensing signal recovery is performed on the target signal based on the measurement matrix to obtain an original sensor signal.

6. The method according to claim 5, characterized in that The receiving device locally stores at least one quantum key and a key identifier of the quantum key that are pre-acquired from a quantum key distribution network; The decrypting the encrypted chaotic parameter based on the target quantum key corresponding to the key identifier to obtain the chaotic parameter includes: Searching for a target quantum key corresponding to the key identifier from at least one locally stored quantum key; When the target quantum key is found, the encrypted chaotic parameters are decrypted using the target quantum key to obtain the chaotic parameters.

7. The method according to claim 5, characterized in that The decrypting the encrypted chaotic parameter based on the target quantum key corresponding to the key identifier to obtain the chaotic parameter includes: Based on the key identifier, sending a quantum key acquisition request to a quantum key distribution node in the quantum key distribution network; receiving a target quantum key fed back by the quantum key distribution node in response to the quantum key acquisition request; The encrypted chaotic parameters are decrypted using the target quantum key to obtain the chaotic parameters.

8. A signal processing system, characterized in that: The system includes a sensor network and a quantum key distribution network, wherein a sending device and a receiving device are deployed in the sensor network, and a quantum key distribution node is deployed in the quantum key distribution network, wherein: The transmitting device is configured to randomly generate chaotic parameters, generate a measurement matrix based on the chaotic parameters, and perform compressed sensing processing on the original sensor signal under the control of the measurement matrix to obtain a target signal; The sending device is further configured to encrypt the chaotic parameters based on a target quantum key obtained from the quantum key distribution network to obtain encrypted chaotic parameters, and send the target signal, the encrypted chaotic parameters, and a key identifier of the target quantum key to a receiving device in the sensor network, wherein the target quantum key includes a quantum key obtained by the sending device through real-time interaction with a quantum key distribution node in the quantum key distribution network, or any one of quantum keys obtained in advance from the quantum key distribution network and stored locally by the sending device; The receiving device is configured to, after receiving the target signal, encrypted chaotic parameters and key identifier sent by the sending device, decrypt the encrypted chaotic parameters based on the target quantum key corresponding to the key identifier to obtain chaotic parameters, generate a measurement matrix based on the chaotic parameters, and perform compressed sensing signal recovery on the target signal based on the measurement matrix to obtain the original sensor signal, wherein the target quantum key includes a quantum key obtained by the receiving device through real-time interaction with a quantum key distribution node in the quantum key distribution network, or a quantum key obtained by the receiving device in advance from the quantum key distribution network and stored locally.

9. A signal encryption processing device, characterized in that: A transmitting device applied to a sensor network, the device comprising: an undersampling module, configured to randomly generate chaotic parameters, generate a measurement matrix based on the chaotic parameters, and perform compressed sensing processing on the original sensor signal under the control of the measurement matrix to obtain a target signal; an encryption module, configured to encrypt the chaotic parameters based on a target quantum key obtained from a quantum key distribution network to obtain encrypted chaotic parameters, wherein the target quantum key includes a quantum key obtained by the sending device through real-time interaction with a quantum key distribution node in the quantum key distribution network, or a quantum key obtained in advance from the quantum key distribution network and stored locally by the sending device; A sending module is configured to send the target signal, the encrypted chaotic parameters, and a key identifier of the target quantum key to a receiving device in the sensor network, so that the receiving device uses the target quantum key corresponding to the key identifier to decrypt the encrypted chaotic parameters to obtain the chaotic parameters, generates a measurement matrix based on the chaotic parameters, and performs compressed sensing signal recovery on the target signal based on the measurement matrix to obtain the original sensor signal.

10. A signal decryption processing device, characterized in that: A receiving device applied to a sensor network, the device comprising: A receiving module, configured to receive a target signal, an encrypted chaotic parameter, and a key identifier sent by a sending device in the sensor network; a decryption module, configured to decrypt the encrypted chaotic parameters based on a target quantum key corresponding to the key identifier to obtain the chaotic parameters, wherein the target quantum key includes a quantum key obtained by the receiving device through real-time interaction with a quantum key distribution node in a quantum key distribution network, or a quantum key obtained in advance by the receiving device from the quantum key distribution network and stored locally; A signal recovery module is used to generate a measurement matrix based on the chaotic parameters, and perform compressed sensing signal recovery on the target signal based on the measurement matrix to obtain an original sensor signal.

11. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 or 5 to 7 are implemented.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 or 5 to 7 are implemented.

13. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 or 5 to 7 are implemented.

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