Sensor signal transmission method and system

Abstract

One or more embodiments of this specification provide a sensor signal transmission method and system, comprising: receiving an encrypted sensor signal, the encrypted sensor signal being an encrypted sensor signal output by a sensor system based on a chaotic signal generated by a chaotic system; decrypting the encrypted sensor signal using a preset extended state observer to obtain the sensor signal; wherein the extended state observer is configured to observe a combined state obtained by merging the state of the sensor system with the state of the chaotic system. Leveraging the unpredictable nature of chaotic signals, the method effectively resists attacks such as eavesdropping, tampering, and replay, thereby ensuring the security and integrity of sensor signal transmission.

Description

Technical Field

[0001] One or more embodiments of this specification relate to the field of sensor technology, and more particularly, to a sensor signal transmission method and system. Background Art

[0002] With the advancement of industrial automation and intelligence, industrial sensors play a vital role in production processes. In industrial environments, sensor signals rely on wireless or wired transmission, exposed over open or insecure communication channels, making them vulnerable to cyberattacks such as eavesdropping, tampering, and replay. Eavesdropping attacks can leak sensitive information; tampering attacks can alter transmitted data, leading to incorrect control system decisions, safety hazards, and production failures. These attacks pose a potential threat to enterprise production processes and may also cause data leakage, financial loss, and even endanger personal safety.

[0003] Related security mechanisms often rely on traditional encryption algorithms, such as symmetric and asymmetric encryption. While these algorithms are somewhat effective in protecting data privacy, they are computationally complex and can cause system response delays in industrial environments with high real-time requirements.

[0004] In summary, industrial sensor systems urgently need an efficient, simple and effective security protection mechanism. Summary of the Invention

[0005] In view of this, one or more embodiments of this specification provide the following technical solutions:

[0006] According to a first aspect of one or more embodiments of the present specification, a sensor signal transmission method is proposed, comprising: receiving an encrypted sensor signal, wherein the encrypted sensor signal is a signal obtained by encrypting a sensor signal output by a sensor system based on a chaotic signal generated by a chaotic system; decrypting the encrypted sensor signal by a preset extended state observer to obtain the sensor signal; wherein the extended state observer is used to observe a joint state obtained by merging the state of the sensor system and the state of the chaotic system.

[0007] According to a second aspect of one or more embodiments of this specification, a sensor signal transmission method is proposed, the method comprising: acquiring a sensor signal output by a sensor system; encrypting the sensor signal based on a chaotic signal generated by a chaotic system, and sending the encrypted sensor signal so that a receiving end decrypts the encrypted sensor signal through a preset extended state observer to obtain the sensor signal.

[0008] According to a third aspect of one or more embodiments of this specification, a sensor signal transmission system is proposed, comprising: a sensor system, a chaotic system, a signal transmitter, a signal receiver, and an extended state observer; wherein the sensor system is used to generate a sensor signal; the chaotic system is used to generate a chaotic signal, and to encrypt the sensor signal based on the chaotic signal to obtain an encrypted sensor signal; the signal transmitter is used to send the encrypted sensor signal to the signal receiver; and the extended state observer is used to decrypt the encrypted sensor signal received by the signal receiver to obtain the sensor signal.

[0009] According to a fourth aspect of one or more embodiments of this specification, an electronic device is proposed, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor implements the steps of the method described in the first aspect or the second aspect by running the executable instructions.

[0010] According to a fifth aspect of one or more embodiments of this specification, a computer-readable storage medium is provided, on which computer instructions are stored. When the instructions are executed by a processor, the steps of the method described in the first aspect or the second aspect are implemented.

[0011] According to a sixth aspect of one or more embodiments of this specification, a computer program product is proposed, comprising a computer program / instruction, which implements the steps of the method described in the first aspect or the second aspect when executed by a processor.

[0012] It can be seen from the above embodiments that this specification encrypts the sensor signal by using the chaotic signal generated by the chaotic system, and decrypts it with the help of the extended state observer. It takes advantage of the unpredictable characteristics of the chaotic signal to effectively resist attacks such as eavesdropping, tampering and replay, thereby ensuring the security and integrity of the sensor signal transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a structural block diagram of a sensor signal transmission system provided by an exemplary embodiment.

[0014] Figure 2 This is one of the structural diagrams of a sensor signal transmission system provided by an exemplary embodiment.

[0015] Figure 3 It is a flowchart of a sensor signal transmission method provided by an exemplary embodiment.

[0016] Figure 4 This is the second structural diagram of a sensor signal transmission system provided by an exemplary embodiment.

[0017] Figure 5It is a structural diagram of an electronic device provided by an exemplary embodiment.

[0018] Figure 6 It is a block diagram of a sensor signal decryption device provided by an exemplary embodiment.

[0019] Figure 7 It is a block diagram of a sensor signal encryption device provided by an exemplary embodiment. DETAILED DESCRIPTION

[0020] 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 manual are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0021] With the advancement of industrial automation and intelligent manufacturing, various industrial sensors play a vital role in production processes. Sensors collect key data such as temperature, pressure, humidity, and gas concentration in real time and transmit this data to control systems for analysis and decision-making, enabling precise control and optimization of production processes. However, with the widespread adoption of the Industrial Internet of Things (IIoT) and smart manufacturing, sensor security issues have become increasingly prominent, becoming a bottleneck restricting their widespread application.

[0022] In industrial environments, the transmission of sensor signals typically relies on wireless or wired communications. These signals are often exposed over open or insecure communication channels, making them vulnerable to various cyberattacks, including eavesdropping, tampering, and replay. Eavesdropping attacks allow attackers to intercept transmitted signals and obtain sensitive information. Tampering attacks alter transmitted data, causing control systems to make incorrect decisions, leading to safety hazards or production failures. Replay attacks resend historical signals to trick the system into performing incorrect operations. These attacks not only pose a potential threat to a company's production processes but can also lead to data leaks, financial losses, and even personal safety.

[0023] To effectively address these security threats, industrial sensor systems urgently need an efficient, simple, and effective security protection mechanism. Related security mechanisms primarily rely on traditional encryption algorithms, such as symmetric and asymmetric encryption. While these algorithms are somewhat effective in protecting data privacy, they often have high computational complexity and can cause system response delays, especially in industrial environments with high real-time requirements. Furthermore, traditional encryption algorithms often have shortcomings when it comes to preventing complex attacks, such as replay attacks and eavesdropping attacks.

[0024] In summary, a solution that balances security, real-time performance, and computational efficiency is urgently needed to ensure that industrial sensors can effectively protect the integrity, confidentiality, and authenticity of data in the face of various cyberattacks. At the same time, this solution should have low computational overhead to ensure its practical application in industrial automation systems.

[0025] The present invention aims to solve the above problems and proposes a sensor security transmission mechanism based on chaotic signals, which can not only improve the transmission efficiency while ensuring data security, but also effectively resist attacks such as eavesdropping, tampering and replay, providing a simple, efficient and effective security protection solution for industrial sensor signal transmission.

[0026] In view of this, this specification proposes a sensor signal transmission method, which encrypts the sensor signal generated by the sensor system through a chaotic signal and decrypts the encrypted sensor signal at the receiving end through an extended state observer.

[0027] During implementation, an encrypted sensor signal is received, which is a signal obtained by encrypting the sensor signal output by the sensor system based on the chaotic signal generated by the chaotic system; the encrypted sensor signal is decrypted by a preset extended state observer to obtain the sensor signal; wherein the extended state observer is used to observe the joint state obtained by merging the state of the sensor system and the state of the chaotic system.

[0028] In the above technical solution, the sensor signal is encrypted by using the chaotic signal generated by the chaotic system, and decrypted with the help of the extended state observer. The unpredictable characteristics of the chaotic signal are utilized to effectively resist attacks such as eavesdropping, tampering and replay, thereby ensuring the security and integrity of the sensor signal transmission.

[0029] Figure 1 FIG. 1 is a schematic diagram of the architecture of a sensor signal transmission system provided by an exemplary embodiment. Figure 1 As shown, the system may include a server 11, a network 12, several electronic devices, such as an industrial control machine 13, and sensors 14 connected to the electronic devices.

[0030] The server 11 may be a physical server containing an independent host, or a virtual server hosted by a host cluster. During operation, the server 11 may run a server-side program of an application to implement the relevant functions of the application. For example, when the server 11 runs a program for transmitting sensor signals, it may be implemented as a receiver of the corresponding sensor signals.

[0031] Figure 1 The industrial controller 13 shown is only a subset of the electronic devices that a user can use. In practice, users can obviously also use electronic devices such as PCs (Personal Computers), tablets, laptops, PDAs (Personal Digital Assistants), and wearable devices (such as smart glasses and smart watches). This specification and one or more embodiments are not intended to limit this. During operation, the electronic device can run a program on the sending side of an application to implement the relevant functions of that application. For example, when the electronic device runs a program for sensor signal transmission, it can obtain sensor signals from sensor 14 and perform encryption processing. The application on the sending side of the sensor signal transmission can be launched and run on the electronic device. The program on the sending side can be a native application installed on the electronic device, or it can be a mini-program, quick app, or other similar form. Of course, when using web technologies such as HTML5 or similar, the relevant functions can be implemented through a page displayed by a browser. The browser here can be a standalone browser application or a browser module embedded in certain applications.

[0032] Regarding the network 12 for interaction between the electronic device such as PC 13 and the server 11, the communication can be realized by using a wired or wireless network based on the communication method supported by the corresponding electronic device, and this specification does not limit this. For example, if PC 13 supports both wired and wireless communication, then the communication can be realized by using a wired or wireless network as needed.

[0033] In order to enable people skilled in the art to better understand the technical solutions in this application, the technical solutions in this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this application.

[0034] See Figure 2 , Figure 2 A sensor signal transmission system is provided by an exemplary embodiment. Figure 2As shown, the system includes a transmitting end 210 and a receiving end 220 , wherein the transmitting end 210 may include a sensor system 211 , a chaotic system 212 and a signal transmitter 213 ; the receiving end 220 may include a signal receiver 221 and an extended state observer 222 .

[0035] In one embodiment, sensor system 211 may include several sensors from an industrial system, such as temperature sensors, pressure sensors, and flow sensors. These sensors can be used to collect real-time operational status data from various devices in the industrial system. Sensor system 211 can generate corresponding sensor signals based on the status data collected by the sensors.

[0036] The sensor system collects state data of the measured object, and its dynamics can be represented by a preset first dynamic model:

[0037]

[0038] in, The system matrix representing the sensor system is used to describe the state variables of the sensor dynamic relationships between Represents the input matrix of the sensor system, which is used to reflect the control input Impact on the state, in actual application scenarios, control input It can be externally applied control instructions, adjustment parameters, etc. Represents the output matrix of the sensor system, which is used to map the state into the sensor signal y output by the sensor system, that is, to convert the collected state information into a signal that can be transmitted.

[0039] In one embodiment, the chaotic system 212 is characterized by high nonlinearity, extreme sensitivity to initial conditions, and variable predictability of long-term behavior.

[0040] The chaotic system can be represented by a pre-defined second dynamic model:

[0041]

[0042] in, The system matrix representing the chaotic system is used to describe the chaotic state of the chaotic system. The dynamic linear relationship between Represents the output matrix of the chaotic system, which is used to convert the chaotic state Mapped to the chaotic signal d output by the chaotic system; It is a nonlinear mapping, which may contain high-order terms such as the square and product of state variables. The interaction of these nonlinear terms makes the evolution trajectory of the system extremely complex and unpredictable.

[0043] In one embodiment, in order to ensure the stability and controllability of the chaotic system, the nonlinear terms of the chaotic system need to meet preset stability conditions, such as the Lipheath condition, the Herder condition, etc.

[0044] In one embodiment, the nonlinear term of the chaotic system satisfies the Lipheath condition,

[0045]

[0046] The Lipheath condition states that in a chaotic system, for a set Any two state variables in and , which are nonlinearly mapped The difference after , will be subject to a constraint related to the difference between the two state variables. Represents the Lipheath coefficient, which is used to measure nonlinear mapping The severity of the change.

[0047] based on Figure 2 The system shown, Figure 3 An exemplary embodiment provides a sensor signal transmission method. The method may include the following steps:

[0048] S310: Collect sensor signals output by the sensor system.

[0049] The sensor system can generate sensor signals based on the monitoring of the operating status of various devices by several sensors included in the sensor system.

[0050] S320: Encrypt the sensor signal based on the chaotic signal generated by the chaotic system, and send the encrypted sensor signal.

[0051] Based on its unique nonlinear dynamics, chaotic systems can generate chaotic signals with nonlinear dynamic characteristics. These chaotic signals are then used to encrypt sensor signals, resulting in encrypted sensor signals. The unpredictability of chaotic signals provides a strong guarantee for data encryption, making it difficult for attackers to decrypt the encrypted content by analyzing the signals.

[0052] In one embodiment, the encryption processing method can be set according to actual needs. For example, the sensor signal can be directly superimposed with the chaotic signal, that is, the encryption processing signal Alternatively, the sensor signal and the chaotic signal may be combined; or a preset encryption algorithm may be used to fuse the chaotic signal into the sensor signal. For simplicity, in the following embodiments, the encrypted sensor signal obtained by superimposing the sensor signal and the chaotic signal is used as an example for illustration.

[0053] After obtaining the encrypted sensor signal, the signal transmitter may send the encrypted sensor signal to the receiving end via a wireless or wired communication network.

[0054] S330: Receive encrypted sensor signals.

[0055] At the receiving end, the signal receiver can be in a continuous monitoring state at all times. After receiving the encrypted sensor signal, the encrypted sensor signal can be sent to the extended state observer.

[0056] S340. Decrypt the encrypted sensor signal through a preset extended state observer to obtain a sensor signal; wherein the extended state observer is used to observe a joint state obtained by combining the state of the sensor system and the state of the chaotic system.

[0057] The extended state observer can separate the original sensor signal from the encrypted sensor signal and complete the decryption operation by observing and estimating the joint state of the sensor system and the chaotic system.

[0058] In the above embodiment, the sensor signal is encrypted by using the chaotic signal generated by the chaotic system and decrypted with the help of the extended state observer. The unpredictable nature of the chaotic signal is utilized to effectively resist attacks such as eavesdropping, tampering and replay, thereby ensuring the security and integrity of the sensor signal transmission.

[0059] In one embodiment, a unified dynamic model can be constructed based on the first dynamic model corresponding to the sensor system, the second dynamic model corresponding to the chaotic system, and the encryption method used in the encryption process. This unified dynamic model is used as the third dynamic model corresponding to the extended state observer, as specifically expressed as follows:

[0060]

[0061]

[0062] in, is the extended state, that is, the joint state after the states of the sensor system and the chaotic system are merged; A represents the system matrix in the third dynamic model, B represents the input matrix in the third dynamic model, and C represents the output matrix in the third dynamic model. Represents the matrix corresponding to the nonlinear term.

[0063]

[0064] The calculation formula for decrypting the input encrypted sensor signal using the extended state observer can be expressed as follows:

[0065]

[0066]

[0067]

[0068] in, Represents the extended state observer for the joint state The state observation results, Represents the encrypted sensor signal input by the extended state observer The sensor signal observation result, A represents the system matrix in the third dynamic model, B represents the input matrix in the third dynamic model, C represents the output matrix in the third dynamic model, represents the matrix corresponding to the nonlinear term, Indicates the value used to limit the nonlinear term observation The amplitude saturation function, L represents the observation gain matrix, represents the observation result of the sensor signal.

[0069] The observation gain matrix L can be calculated by a preset inequality, and the observation gain matrix can be used to converge the observation results of the extended state observer so that the state observation results Converge to the actual joint state , which makes the observation results of sensor signals Converge to the actual sensor signal , and finally the observation results of the sensor signal The sensor signal is output as decrypted signal.

[0070] In one embodiment, when the nonlinear term of the chaotic system satisfies the Lipheath condition, the Lipheath coefficient in the Lipheath condition can be , combined with the preset inequality to calculate the observation gain matrix L.

[0071] In one embodiment, the inequality used to calculate the observation gain matrix may be an inequality constructed based on Lyapunov stability theory.

[0072] In one embodiment, the inequality may be expressed as follows:

[0073]

[0074] Wherein, P represents an arbitrary positive definite matrix, A represents the system matrix in the third dynamic model, and C represents the output matrix in the third dynamic model. Denotes the Lipsheath coefficient corresponding to the nonlinear term in the second dynamic model. According to the above inequality, the appropriate observation gain matrix L can be obtained.

[0075] In one embodiment, the sensor system is an aircraft longitudinal axis motion model, which includes a sensor state vector Contains 4 state variables, namely elevation angle ( )、Pitch angle( ), pitch rate ( ) and true airspeed ( ); the control input vector in the model Contains 3 variables, namely the elevator deflection angle ( ), total thrust ( ), and horizontal stabilizer deflection angle ( ).

[0076] The system matrix, input matrix, and output matrix of the first dynamic model corresponding to the aircraft longitudinal axis motion model are:

[0077]

[0078]

[0079]

[0080] The system matrix and output matrix in the second dynamic model corresponding to the chaotic system, and the nonlinear mapping are:

[0081]

[0082] By the function By calculating the derivative of When the nonlinear term of the chaotic system Satisfies the Lipheath condition.

[0083] Based on the above parameters, by solving the inequality, the extended observer parameter L can be obtained:

[0084]

[0085] In the above-described embodiment, by constructing a corresponding dynamic model for the extended state observer based on the corresponding dynamic models and encryption methods of the sensor system and chaotic system, an efficient and concise framework for encrypting and decrypting sensor signals is provided. The extended state observer can rapidly decrypt encrypted sensor signals by observing the combined state of the sensor and chaotic systems, without requiring complex hardware or high computing power, and is easy to implement. The present invention does not rely on complex encryption and decryption algorithms and can inherently synchronize encryption and decryption, eliminating the need for additional synchronization signals between the sensor transmitter and receiver.

[0086] Figure 4 is a structural diagram of a sensor signal transmission system provided by an exemplary embodiment, Figure 2 In contrast, the receiving end 220 further includes a detector 223 for detecting possible attacks.

[0087] In one embodiment, to prevent tampering attacks, the detector can calculate the received encrypted sensor signal And the sensor signal observation results output by the extended state observer The difference is compared with the preset first threshold range; if the difference is within the first threshold range, it indicates that there is no tampering attack; if the difference is not within the first threshold range, it indicates that there is a spontaneous attack. The specific calculation formula can be expressed as follows:

[0088]

[0089] in, Indicates new information, Represents a vector The square of the modulus is used to measure the size of the new information so as to be consistent with the first threshold range. For comparison, and Used to adjust the first threshold range; if it is within the first threshold range, it means that the sensor signal is encrypted It is not a tampering attack signal; otherwise, it means the received encrypted sensor signal To tamper with the attack signal.

[0090] In one embodiment, the first threshold range is less than the first threshold, and the detector compares the difference between the encrypted sensor signal and the sensor signal observation result output by the extended state observer with the first threshold; if the difference reaches or exceeds the first threshold, it indicates that a tampering attack has occurred; otherwise, it indicates that no tampering attack has occurred.

[0091] In the above embodiment, by determining whether the difference between the encrypted sensor signal and the sensor signal observation result output by the extended state observer reaches a first threshold, it is possible to timely and effectively detect whether there is a tampering attack, thereby providing a simple and effective detection method for ensuring the authenticity and integrity of the sensor signal.

[0092] In one embodiment, to prevent replay attacks, the detector can calculate the received encrypted sensor signal Encrypted sensor signals with history The similarity is calculated and compared with the second threshold range. If the similarity is within the second threshold range, it indicates that a replay attack has occurred. If the similarity is not within the second threshold range, it indicates that no replay attack has occurred. The specific calculation formula can be expressed as follows:

[0093]

[0094] in, Indicates encrypted sensor signal Encrypted sensor signals with history The degree of correlation, For measuring encrypted sensor signals Encrypted sensor signals with history similarity so that it is within the second threshold range For comparison, and Used to adjust the second threshold range; if it is within the second threshold range, it means that the sensor signal is encrypted It is not a replay attack signal; otherwise, it means the received encrypted sensor signal To replay the attack signal.

[0095] In one embodiment, the second threshold range is less than the second threshold, and the detector compares the similarity between the encrypted sensor signal and the historical encrypted sensor signal with the second threshold; if the similarity reaches or exceeds the second threshold, it indicates that a replay attack exists; otherwise, it indicates that no replay attack exists.

[0096] In the above embodiment, by determining whether the similarity between the received encrypted sensor signal and the historical encrypted sensor signal reaches the second threshold, a replay attack can be accurately identified, providing an effective monitoring method for preventing replay attacks and further ensuring the security of sensor signal transmission.

[0097] Figure 5 This is a schematic structural diagram of a device provided by an exemplary embodiment. Figure 5At the hardware level, the device includes a processor 502, an internal bus 504, a network interface 506, a memory 508, and a non-volatile memory 510. Of course, it may also include hardware required for other functions. One or more embodiments of this specification can be implemented based on software, such as the processor 502 reading the corresponding computer program from the non-volatile memory 510 into the memory 508 and then running it. Of course, in addition to software implementation, one or more embodiments of this specification do not exclude other implementation methods, such as logic devices or a combination of software and hardware, etc., that is, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0098] Please refer to Figure 6 , the sensor signal decryption device can be used for Figure 5 The sensor signal decryption device may include: a signal receiving module 601 and a signal decryption module 602.

[0099] Among them, the signal receiving module 601 is used to receive the encrypted sensor signal, which is a signal obtained by encrypting the sensor signal output by the sensor system based on the chaotic signal generated by the chaotic system; the signal decryption module 602 is used to decrypt the encrypted sensor signal through a preset extended state observer to obtain the sensor signal; wherein, the extended state observer is used to observe the joint state obtained by merging the state of the sensor system and the state of the chaotic system.

[0100] Furthermore, the signal decryption module 602 is also used to obtain a first dynamic model corresponding to the sensor system and a second dynamic model corresponding to the chaotic system; based on the first dynamic model and the second dynamic model, as well as the encryption method of the encryption processing, a third dynamic model corresponding to the extended state observer is generated, and an observation gain matrix is ​​calculated to ensure that the observation results of the state observer converge.

[0101] Furthermore, the signal decryption module 602 is configured to obtain the observation gain matrix by calculating a preset inequality based on the Lipsheath coefficient corresponding to the nonlinear term in the second dynamic model.

[0102] Furthermore, the signal decryption module 602 is further configured to determine whether a difference between the encrypted sensor signal and the sensor signal observation result output by the extended state observer is within a first threshold range; if not, it is determined that a tampering attack has occurred.

[0103] Furthermore, the signal decryption module 602 is further configured to determine whether the similarity between the received encrypted sensor signal and the historical encrypted sensor signal is within a second threshold range; if not, it is determined that a replay attack has occurred.

[0104] Please refer to Figure 7 , the sensor signal encryption device can be applied to Figure 5 The sensor signal encryption device may include: a signal acquisition module 701 and a signal encryption module 702.

[0105] Among them, the signal acquisition module 701 is used to collect the sensor signal output by the sensor system; the signal encryption module 702 is used to encrypt the sensor signal based on the chaotic signal generated by the chaotic system, and send the encrypted sensor signal so that the receiving end can decrypt the encrypted sensor signal through a preset extended state observer to obtain the sensor signal.

[0106] Based on the same concept as the above method, this specification also provides an electronic device, including: a processor; a memory for storing processor-executable instructions; wherein the processor implements the steps of the method described in any of the above embodiments by running the executable instructions.

[0107] Based on the same concept as the above method, this specification also provides a computer-readable storage medium on which computer instructions are stored. When the instructions are executed by a processor, the steps of the method described in any of the above embodiments are implemented.

[0108] Based on the same concept as the above method, this specification also provides a computer program product, including a computer program / instruction, which implements the steps of the method described in any of the above embodiments when executed by a processor.

Claims

1. A sensor signal transmission method, characterized in that: include: receiving an encrypted sensor signal, wherein the encrypted sensor signal is a signal obtained by encrypting a sensor signal output by the sensor system based on a chaotic signal generated by the chaotic system; Acquiring a first dynamic model corresponding to the sensor system and a second dynamic model corresponding to the chaotic system; Based on the first dynamic model and the second dynamic model, and the encryption method of the encryption process, generating a third dynamic model corresponding to the extended state observer, and calculating an observation gain matrix; The joint state of the sensor system and the chaotic system is observed and estimated through a preset extended state observer, the original sensor signal is separated from the encrypted sensor signal, and the observation results of the extended state observer are converged based on the observation gain matrix, so that the state observation results converge to the actual joint state, and then the observation results of the sensor signal converge to the actual sensor signal, and finally the observation results of the sensor signal are output as the sensor signal obtained after decryption.

2. The method according to claim 1, characterized in that The calculation to obtain the observation gain matrix includes: The observation gain matrix is ​​obtained by calculating a preset inequality based on the Lipsheath coefficient corresponding to the nonlinear term in the second dynamic model.

3. The method according to claim 2, characterized in that The inequality is an inequality constructed based on Lyapunov's stability theory.

4. The method according to claim 3, characterized in that The inequality is as follows: Wherein, P represents an arbitrary positive definite matrix, A represents the system matrix in the third dynamic model, and C represents the output matrix in the third dynamic model. represents the Lipheath coefficient corresponding to the nonlinear term in the second kinetic model.

5. The method according to claim 1, wherein The calculation formula for decrypting the encrypted sensor signal by the preset extended state observer is expressed as follows: in, Indicates the joint status The state observation results, Indicates the encrypted sensor signal for the input The sensor signal observation result, A represents the system matrix in the third dynamic model, B represents the input matrix in the third dynamic model, C represents the output matrix in the third dynamic model, represents the matrix corresponding to the nonlinear term, Indicates the value used to limit the nonlinear term observation The amplitude saturation function, L represents the observation gain matrix, Represents the observation result of the sensor signal.

6. The method according to claim 1, wherein The method further comprises: Determine whether a difference between the encrypted sensor signal and a sensor signal observation result output by the extended state observer is within a first threshold range; if not, determine that a tampering attack has occurred.

7. The method according to claim 1, characterized in that The method further comprises: Determine whether the similarity between the received encrypted sensor signal and the historical encrypted sensor signal is within a second threshold range; if not, determine that a replay attack exists.

8. A sensor signal transmission method, characterized in that: The method comprises: Collect sensor signals output by the sensor system; The sensor signal is encrypted based on the chaotic signal generated by the chaotic system, and the encrypted sensor signal is sent, so that the receiving end generates a third dynamic model corresponding to the extended state observer based on the acquired first dynamic model corresponding to the sensor and the second dynamic model corresponding to the chaotic system, as well as the encryption method of the encryption processing, and calculates the observation gain matrix. The joint state of the sensor system and the chaotic system is observed and estimated by the preset extended state observer, the original sensor signal is separated from the encrypted sensor signal, and the observation result of the extended state observer is converged based on the observation gain matrix, so that the state observation result converges to the actual joint state, and then the observation result of the sensor signal converges to the actual sensor signal, and finally the observation result of the sensor signal is output as the sensor signal obtained after decryption.

9. A sensor signal transmission system, characterized in that: include: A sensor system, a chaotic system, a signal transmitter, a signal receiver, and an extended state observer; wherein the sensor system is used to generate a sensor signal; the chaotic system is used to generate a chaotic signal, so as to encrypt the sensor signal based on the chaotic signal to obtain an encrypted sensor signal; the signal transmitter is used to send the encrypted sensor signal to the signal receiver; the extended state observer is used to observe and estimate the joint state of the sensor system and the chaotic system, separate the original sensor signal from the encrypted sensor signal, converge the observation results of the extended state observer based on the observation gain matrix, so that the state observation results converge to the actual joint state, and then make the observation results of the sensor signal converge to the actual sensor signal, and finally output the observation results of the sensor signal as the sensor signal obtained after decryption; wherein the observation gain matrix is ​​calculated after generating a third dynamic model corresponding to the extended state observer based on a first dynamic model corresponding to the sensor system and a second dynamic model corresponding to the chaotic system, as well as the encryption method of the encryption processing.

10. An electronic device, characterized in that: include: processor; A memory for storing processor-executable instructions; wherein the processor implements the steps of the method according to any one of claims 1 to 8 by executing the executable instructions.

11. A computer-readable storage medium, characterized in that Computer instructions are stored thereon, and when the instructions are executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

12. A computer program product, characterized in that The method comprises a computer program / instruction, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 8.

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