Ultra-limit and cross-field based sensor out-of-band vulnerability analysis method

Abstract

This application discloses a sensor out-of-band vulnerability analysis method based on limit and cross-field vulnerability analysis, relating to the field of sensor vulnerability analysis technology. The method includes: defining a sensor out-of-band vulnerability model; the sensor out-of-band vulnerability model describes the sensor's out-of-band mapping, which includes limit mapping and cross-field mapping; limit mapping is the mapping between the input signal and output signal when the sensor's input signal is the expected input physical field signal but exceeds the limit parameter; cross-field mapping is the mapping between the input signal and output signal when the sensor's input signal is an unexpected input physical field signal; based on the sensor out-of-band vulnerability model, the sensor's out-of-band vulnerability is analyzed and tested to obtain the sensor's out-of-band vulnerability analysis results; the out-of-band vulnerability analysis results include limit vulnerability analysis results and cross-field vulnerability analysis results. This application implements sensor out-of-band vulnerability analysis.

Description

Technical Field

[0001] This application relates to the field of sensor vulnerability analysis technology, and in particular to a method for out-of-band vulnerability analysis of sensors based on overlimit and cross-field conditions. Background Technology

[0002] A sensor is a device or apparatus capable of sensing specific physical, chemical, or biological quantities and converting them into usable electrical signals according to predetermined conversion rules. Its core function is to achieve real-time sensing, quantification, and information output of objective environmental parameters, providing fundamental data support for subsequent signal processing, analysis, and control. Depending on the object being measured and the application requirements, over 350 types of sensors have been developed, covering a wide range of transduction methods and diverse working principles. Modern sensors typically consist of major hardware modules such as transducers, signal conditioning circuits, power supply modules, and communication interfaces.

[0003] Sensors, as key devices that convert environmental physical stimuli into processable electrical signals, are an important bridge connecting the physical world and the digital world. They have become a core component of modern information society and are widely used.

[0004] However, the widespread use of sensors has also brought increasingly severe security challenges. Sensors are vulnerable to carefully designed physical signal attacks, leading to unexpected deviations in output results. Although numerous information security technologies are used to ensure the secure operation of cyber-physical systems, they still struggle to effectively address the underlying security problems caused by sensor measurement errors. The root cause lies in the lack of a systematic understanding of the fundamental mechanisms underlying sensor measurement errors, resulting in insufficient defensive measures.

[0005] Therefore, a method for analyzing the out-of-band vulnerability of sensors based on over-limit and cross-field conditions is needed to achieve the fundamental mechanism analysis of sensor measurement errors. Summary of the Invention

[0006] The purpose of this application is to provide a sensor out-of-band vulnerability analysis method based on overlimit and cross-field conditions, so as to realize sensor out-of-band vulnerability analysis.

[0007] To achieve the above objectives, this application provides the following solution.

[0008] This application provides a method for analyzing the out-of-band vulnerability of sensors based on exceeding limits and crossing fields, including: Define a sensor out-of-band vulnerability model; the sensor out-of-band vulnerability model is used to describe the sensor out-of-band mapping, which includes overlimit mapping and cross-field mapping; the overlimit mapping is the mapping between the input signal and the output signal when the sensor's input signal is the expected input physical field signal but exceeds the overlimit parameter; the cross-field mapping is the mapping between the input signal and the output signal when the sensor's input signal is an unexpected input physical field signal. Based on the sensor out-of-band vulnerability model, the sensor's out-of-band vulnerability is analyzed and tested to obtain the sensor's out-of-band vulnerability analysis results; the out-of-band vulnerability analysis results include over-limit vulnerability analysis results and cross-field vulnerability analysis results.

[0009] In one embodiment, based on the sensor's out-of-band vulnerability model, the sensor's out-of-band vulnerability is analyzed and tested to obtain the sensor's out-of-band vulnerability analysis results, including: Based on the aforementioned over-limit mapping, the over-limit vulnerability of the sensor is analyzed and tested, and the over-limit vulnerability analysis results are obtained. Based on the cross-field mapping, the cross-field vulnerability of the sensor is analyzed and tested, and the cross-field vulnerability analysis results are obtained.

[0010] In one embodiment, the results of the vulnerability analysis include: amplitude vulnerability analysis sub-results and frequency vulnerability analysis sub-results; The sensor's vulnerability beyond its limits was analyzed and tested, and the results of the vulnerability analysis were obtained, including: Obtain the sensor's out-of-limit parameters; the out-of-limit parameters include: the upper limit of the amplitude and the upper limit of the frequency of the input signal; Based on the aforementioned out-of-limit parameters, the amplitude out-of-limit signal and the frequency out-of-limit signal are determined; The sensor was subjected to injection tests using amplitude over-limit signals and frequency over-limit signals respectively, and the results of the amplitude over-limit vulnerability analysis and the frequency over-limit vulnerability analysis were determined.

[0011] In one embodiment, determining the amplitude over-limit signal and the frequency over-limit signal based on the over-limit parameters includes: The input signal that does not exceed the frequency limit but exceeds the amplitude limit is defined as the amplitude over-limit signal; An input signal that exceeds the frequency limit but does not exceed the amplitude limit is defined as a frequency over-limit signal.

[0012] In one embodiment, an injection test is performed on the sensor using both amplitude over-limit signals and frequency over-limit signals to determine the amplitude over-limit vulnerability analysis sub-results and frequency over-limit vulnerability analysis sub-results, including: An amplitude over-limit signal injection test is performed on the sensor. If the sensor's output signal exhibits saturation during the injection test, the amplitude over-limit vulnerability analysis result of the sensor is determined to be that amplitude over-limit vulnerability exists. The sensor is subjected to frequency over-limit signal injection test. If the sensor output signal exhibits nonlinearity or aliasing effect during the injection test, the frequency over-limit vulnerability analysis result of the sensor is determined to be that frequency over-limit vulnerability exists.

[0013] In one embodiment, the cross-field vulnerability analysis results include at least one of the following: acoustic cross-field vulnerability analysis sub-results, optical cross-field vulnerability analysis sub-results, electromagnetic cross-field vulnerability analysis sub-results, mechanical cross-field vulnerability analysis sub-results, and thermal cross-field vulnerability analysis sub-results; The cross-field vulnerability of the sensor was analyzed and tested, and the cross-field vulnerability analysis results were obtained, including: When the expected input physical field signal of the sensor does not include the acoustic signal, the sensor is subjected to acoustic cross-field vulnerability analysis test to obtain the acoustic cross-field vulnerability analysis sub-results; When the expected input physical field signal of the sensor does not include the optical signal, the sensor is subjected to optical cross-field vulnerability analysis test to obtain the optical cross-field vulnerability analysis sub-results; When the expected input physical field signal of the sensor does not include electromagnetic signals, an electromagnetic cross-field vulnerability analysis test is performed on the sensor to obtain the electromagnetic cross-field vulnerability analysis sub-results. When the expected input physical field signal of the sensor does not include mechanical signals, a mechanical cross-field vulnerability analysis test is performed on the sensor to obtain the mechanical cross-field vulnerability analysis sub-results; When the expected input physical field signal of the sensor does not include the thermal signal, a thermal cross-field vulnerability analysis test is performed on the sensor to obtain the thermal cross-field vulnerability analysis sub-result.

[0014] In one embodiment, an acoustic cross-field vulnerability analysis test is performed on the sensor to obtain acoustic cross-field vulnerability analysis sub-results, including: Set up multiple sets of sound signals; the multiple sets of sound signals include sound signals with different frequencies and amplitudes; Multiple sets of acoustic signal injection tests were performed on the sensor. If the sensor's output signal exhibited abnormal resonance or an acoustic signal was present during the injection test, the acoustic cross-field vulnerability analysis result of the sensor was determined to be that acoustic cross-field vulnerability exists.

[0015] In one embodiment, an optical cross-field vulnerability analysis test is performed on the sensor to obtain optical cross-field vulnerability analysis sub-results, including: Set up multiple sets of optical signals; the multiple sets of optical signals include optical signals with different frequencies and amplitudes; Multiple sets of optical signal injection tests were performed on the sensor. If the sensor's output signal exhibited abnormal resonance, bias, or the presence of optical signals during the injection test, the result of the optical cross-field vulnerability analysis of the sensor was determined to be that optical cross-field vulnerability exists.

[0016] In one embodiment, an electromagnetic cross-field vulnerability analysis test is performed on the sensor to obtain electromagnetic cross-field vulnerability analysis sub-results, including: Set up multiple sets of electromagnetic signals; these multiple sets of electromagnetic signals include electromagnetic signals with different frequencies and amplitudes. Multiple sets of electromagnetic signal injection tests were performed on the sensor. If the sensor's output signal showed an abnormal response or electromagnetic signal was present during the injection test, the electromagnetic cross-field vulnerability analysis result of the sensor was determined to be electromagnetic cross-field vulnerability.

[0017] In one embodiment, a mechanical cross-field vulnerability analysis test is performed on the sensor to obtain a mechanical cross-field vulnerability analysis sub-result, including: Set multiple sets of mechanical signals; these multiple sets of mechanical signals include mechanical signals with different frequencies and amplitudes. Multiple sets of mechanical signal injection tests were performed on the sensor. If the sensor's output signal showed an abnormal response or mechanical signal was present during the injection test, the mechanical cross-field vulnerability analysis result of the sensor was determined to be that mechanical cross-field vulnerability exists.

[0018] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application discloses a sensor out-of-band vulnerability analysis method based on limit and cross-field mapping, defining a sensor out-of-band vulnerability model. The sensor out-of-band vulnerability model describes the sensor's out-of-band mapping, which includes limit mapping and cross-field mapping. Limit mapping is the mapping between the input signal and output signal when the sensor's input signal is the expected input physical field signal but exceeds the limit parameter. Cross-field mapping is the mapping between the input signal and output signal when the sensor's input signal is an unexpected input physical field signal. Based on the sensor out-of-band vulnerability model, the sensor's out-of-band vulnerability is analyzed and tested, obtaining the sensor's out-of-band vulnerability analysis results. The out-of-band vulnerability analysis results include limit vulnerability analysis results and cross-field vulnerability analysis results. This application utilizes the defined sensor out-of-band vulnerability model to analyze and test the sensor's out-of-band vulnerability, realizing sensor out-of-band vulnerability analysis. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A flowchart of a sensor out-of-band vulnerability analysis method based on overlimit and cross-field conditions provided in an embodiment of this application; Figure 2 A schematic diagram of the sensor out-of-band vulnerability analysis method architecture based on overlimit and cross-field provided in an embodiment of this application; Figure 3 This is a schematic diagram of the sensor's out-of-band vulnerability model; Figure 4 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0021] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] The purpose of this application is to provide a method for analyzing the out-of-band vulnerability of sensors based on overlimit and cross-field conditions, aiming to achieve out-of-band vulnerability analysis of sensors.

[0023] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0024] In one exemplary embodiment, such as Figure 1 and Figure 2 As shown, a method for analyzing the out-of-band vulnerability of sensors based on over-limit and cross-field conditions is provided, including the following steps.

[0025] Step 1: Define the sensor out-of-band vulnerability model.

[0026] Among them, the sensor out-of-band vulnerability model is used to describe the sensor out-of-band mapping, which includes overlimit mapping and cross-field mapping. Overlimit mapping is the mapping between the input signal and the output signal when the sensor's input signal is the expected input physical field signal but exceeds the overlimit parameter. Cross-field mapping is the mapping between the input signal and the output signal when the sensor's input signal is an unexpected input physical field signal.

[0027] Specifically, in fact, such as Figure 3 As shown, out-of-band mapping and cross-field mapping are collectively referred to as out-of-band mapping. The counterpart to out-of-band mapping is in-band mapping. In-band mapping is the mapping between the input signal and the output signal when the sensor's input signal is the expected input physical field signal.

[0028] Step 2: Based on the sensor out-of-band vulnerability model, analyze and test the sensor's out-of-band vulnerability to obtain the sensor's out-of-band vulnerability analysis results.

[0029] The out-of-band vulnerability analysis results include both over-limit vulnerability analysis results and cross-field vulnerability analysis results.

[0030] As an optional implementation, step 2 includes the following steps (steps 21-22 are actually described in different cases and are not strictly performed in order).

[0031] Step 21: Based on the out-of-limit mapping, analyze and test the out-of-limit vulnerability of the sensor to obtain the out-of-limit vulnerability analysis results.

[0032] As an optional implementation, the results of the over-limit vulnerability analysis include: amplitude over-limit vulnerability analysis sub-results and frequency over-limit vulnerability analysis sub-results.

[0033] In step 21, the over-limit vulnerability of the sensor is analyzed and tested to obtain the over-limit vulnerability analysis results, including the following steps.

[0034] Step 211: Obtain the sensor's out-of-limit parameters; the out-of-limit parameters include: the upper limit of the amplitude and the upper limit of the frequency of the input signal.

[0035] Step 212: Based on the out-of-limit parameters, determine the amplitude out-of-limit signal and the frequency out-of-limit signal.

[0036] As an optional implementation, step 212 includes: Step 2121: Set the input signal that does not exceed the frequency limit but exceeds the amplitude limit as the amplitude over-limit signal; Step 2122: Set the input signal that exceeds the frequency limit but does not exceed the amplitude limit as the frequency over-limit signal.

[0037] Step 213: Use the amplitude over-limit signal and the frequency over-limit signal to perform injection tests on the sensor respectively, and determine the amplitude over-limit vulnerability analysis sub-results and frequency over-limit vulnerability analysis sub-results of the sensor.

[0038] As an optional implementation, step 213 includes the following steps (steps 2132-2133 are actually described in different cases and are not strictly performed in order).

[0039] Step 2131: Perform an amplitude over-limit signal injection test on the sensor. If the output signal of the sensor exhibits saturation during the injection test, the amplitude over-limit vulnerability analysis result of the sensor is determined to be that amplitude over-limit vulnerability exists.

[0040] Specifically, a sensor typically includes a transducer, signal conditioning circuitry, a power supply module, and a communication interface. Amplitude exceeding the limit refers to the input signal exceeding the amplitude limit of the transducer and signal conditioning circuitry. Generally, transducers and signal conditioning circuits have defined operating ranges. When the input signal exceeds this range, saturation occurs, leading to signal saturation distortion, which is the amplitude exceeding vulnerability model. Use the formula It indicates. Among them, This means that when the amplitude of the actual input signal exceeds the upper limit of the sensor's input signal amplitude, a constant will be output due to the saturation effect. This refers to the actual input signal of the sensor at a certain amplitude. This refers to the sensor's input signal at its amplitude upper limit. For transducers, saturation is primarily caused by the physical limitations of the transducer material. For signal conditioning circuits, saturation is typically caused by the limitation of the supply voltage in the active circuit components. Other active circuits may also exhibit the same vulnerability mechanism.

[0041] Step 2132: Perform a frequency over-limit signal injection test on the sensor. If the output signal of the sensor exhibits nonlinearity or aliasing during the injection test, the frequency over-limit vulnerability analysis result of the sensor is determined to be that frequency over-limit vulnerability exists.

[0042] Specifically, frequency over-limit refers to the input signal exceeding the frequency limit of the sensor circuit. Due to the non-ideal characteristics of the components in the sensor circuit, a frequency over-limit signal can be output. Nonlinearity is a common non-ideal characteristic; strictly speaking, all devices are non-linear. Frequency over-limit vulnerability model Use the formula It indicates. Among them, This refers to the constant term in the output signal; These are the coefficients of the linear terms in the output signal; These are the coefficients of the nonlinear terms in the output signal; This refers to the actual input signal of the sensor at a certain frequency. Within the input range specified in the sensor's manual, it can be approximated as linear, i.e. The nonlinearity is approximately zero, and can be ignored. However, when the frequency of the input signal exceeds the limit, the nonlinearity cannot be ignored. Aliasing refers to the phenomenon where the input signal of the analog-to-digital converter in the signal conditioning circuit exceeds the Nyquist frequency (i.e., the frequency of the input signal exceeds the limit). When ), the spectrum of its output signal Includes aliasing frequency , This generates new spectral components, which can cause distortion in the sensor output. Among these, The frequency of the actual input signal to the sensor; The sampling frequency of the analog-to-digital converter in the sensor; For aliasing frequency, It is a constant; This rounds down to the nearest integer.

[0043] Specifically, during step 213, the test platform includes a host computer and a signal injection device. The sensor is connected to the host computer for real-time readings, and the signal injection device injects an amplitude over-limit signal or a frequency over-limit signal into the sensor. The signal injection device consists of a signal generator, a power amplifier, and a signal emission source; different input signals correspond to different signal emission sources. Acoustic signals typically use loudspeakers, optical signals typically use light sources such as lasers or LEDs, electromagnetic signals use wireless electromagnetic antennas or physical cables, mechanical signals typically use vibrations propagated through a solid medium, and thermal signals typically use a heat source for radiation injection.

[0044] Step 22: Based on cross-field mapping, analyze and test the cross-field vulnerability of the sensor to obtain the cross-field vulnerability analysis results.

[0045] As an optional implementation, the cross-field vulnerability analysis results include at least one of the following: acoustic cross-field vulnerability analysis sub-results, optical cross-field vulnerability analysis sub-results, electromagnetic cross-field vulnerability analysis sub-results, mechanical cross-field vulnerability analysis sub-results, and thermal cross-field vulnerability analysis sub-results; In step 22, the cross-field vulnerability of the sensor is analyzed and tested to obtain the cross-field vulnerability analysis results, including the following steps (steps 221-225 are actually described in different cases and are not strictly executed in order).

[0046] Step 221: When the expected input physical field signal of the sensor does not include the acoustic signal, perform acoustic cross-field vulnerability analysis test on the sensor to obtain the acoustic cross-field vulnerability analysis sub-result.

[0047] As an optional implementation, in step 221, the sensor undergoes an acoustic cross-field vulnerability analysis test to obtain acoustic cross-field vulnerability analysis sub-results, including: Step 2211: Set up multiple sets of sound signals; the multiple sets of sound signals include sound signals at different frequencies and amplitudes; Step 2212: Perform multiple sets of acoustic signal injection tests on the sensor. If the sensor's output signal exhibits abnormal resonance or an acoustic signal is present during the injection test, the result of the acoustic cross-field vulnerability analysis of the sensor is determined to be that acoustic cross-field vulnerability exists.

[0048] Specifically, in step 2212, a loudspeaker is used as the signal transmitter, and a microphone is used as the sensor. Acoustic cross-field refers to the abnormal response of a non-acoustic sensor under the influence of an acoustic signal. Acoustic signals primarily affect the sensor through resonance. When the frequency of an external sound wave or ultrasonic wave approaches the sensor's resonant frequency, it may induce a high-intensity interference signal within the sensor; this response is the acoustic cross-field vulnerability model. Use the formula It indicates. Among them, The amplitude of the acoustic signal; The frequency of the acoustic signal; For time; This represents the phase of the acoustic signal. In testing the acoustic cross-field vulnerability of sensors, an acoustic signal input is required to observe whether there is an out-of-limit output caused by non-ideal mapping; simultaneously, an out-of-limit input is required to observe whether there is an acoustic cross-field output (i.e., the output acoustic signal) caused by non-ideal mapping.

[0049] Step 222: When the expected input physical field signal of the sensor does not include the optical signal, perform optical cross-field vulnerability analysis test on the sensor to obtain the optical cross-field vulnerability analysis sub-result.

[0050] As an optional implementation, in step 222, the sensor undergoes an optical cross-field vulnerability analysis test to obtain optical cross-field vulnerability analysis sub-results, including: Step 2221: Set up multiple sets of optical signals; the multiple sets of optical signals include optical signals at different frequencies and amplitudes; Step 2222: Perform multiple sets of optical signal injection tests on the sensor. If the sensor's output signal exhibits abnormal resonance, bias, or the presence of optical signals during the injection test, then the result of the optical cross-field vulnerability analysis of the sensor is determined to be that optical cross-field vulnerability exists.

[0051] Specifically, during step 2222, the signal emission source uses light sources such as lasers or LEDs, and the sensor is an optical sensor. Optical cross-field refers to the abnormal response of a non-optical sensor under the influence of an optical signal. Its mechanism is mainly based on two physical mechanisms: photoacoustic effect and photoelectric effect. The photoacoustic effect converts light energy into mechanical vibration energy, which can interfere with sensors that rely on mechanical vibration detection. In this case, the output signal is the optical cross-field vulnerability model. Use the formula It indicates. Among them, The amplitude of the optical signal; The modulation frequency of the optical signal; This represents the phase of the optical signal. The photoelectric effect manifests as the characteristic that electrons on the surface of a material are excited to generate a current under light irradiation. For sensor elements with exposed conductors, an output bias phenomenon occurs under illumination. In this case, the output signal is the optical cross-field vulnerability model. Use the formula It indicates. Among them, This represents the DC offset. In testing the sensor's optical cross-field vulnerability, a cross-field optical input is required to observe whether there is an out-of-limit output caused by non-ideal mapping; simultaneously, an out-of-limit input is required to observe whether there is an out-of-field optical output caused by non-ideal mapping.

[0052] Step 223: When the expected input physical field signal of the sensor does not include electromagnetic signals, perform electromagnetic cross-field vulnerability analysis test on the sensor to obtain the electromagnetic cross-field vulnerability analysis sub-result.

[0053] As an optional implementation, in step 223, an electromagnetic cross-field vulnerability analysis test is performed on the sensor to obtain electromagnetic cross-field vulnerability analysis sub-results, including: Step 2231: Set up multiple sets of electromagnetic signals; the multiple sets of electromagnetic signals include electromagnetic signals with different frequencies and amplitudes; Step 2232: Perform multiple electromagnetic signal injection tests on the sensor. If the sensor's output signal shows an abnormal response or electromagnetic signals are present during the injection test, the electromagnetic cross-field vulnerability analysis result of the sensor is determined to be electromagnetic cross-field vulnerability.

[0054] Specifically, in step 2232, the signal transmitter uses a wireless electromagnetic antenna or a physical cable, and the sensor is an electromagnetic induction probe. Electromagnetic cross-field interference refers to the phenomenon where non-electromagnetic sensors and their circuits produce abnormal responses under external electromagnetic field interference. The core mechanism of this interference stems from the antenna effect exhibited by conductive elements (especially wires) in the sensing system, which can both receive and emit electromagnetic radiation. Testing the electromagnetic cross-field vulnerability of sensors requires electromagnetic cross-field input to observe whether there is an out-of-limit output caused by non-ideal mapping; simultaneously, it requires out-of-limit input to observe whether there is an electromagnetic cross-field output caused by non-ideal mapping.

[0055] Step 224: When the expected input physical field signal of the sensor does not include mechanical signals, perform mechanical cross-field vulnerability analysis test on the sensor to obtain the mechanical cross-field vulnerability analysis sub-result.

[0056] As an optional implementation, in step 224, a mechanical cross-field vulnerability analysis test is performed on the sensor to obtain a mechanical cross-field vulnerability analysis sub-result, including: Step 2241: Set multiple sets of mechanical signals; the multiple sets of mechanical signals include mechanical signals with different frequencies and amplitudes; Step 2242: Perform multiple sets of mechanical signal injection tests on the sensor. If the sensor output signal shows an abnormal response or mechanical signal is present during the injection test, the mechanical cross-field vulnerability analysis result of the sensor is determined to be that mechanical cross-field vulnerability exists.

[0057] Specifically, during step 2242, the signal source uses a solid medium to propagate vibration, and the sensor is a Micro-Electro-Mechanical Systems Gyroscope (MEMS) or a MEMS accelerometer. Mechanical cross-field refers to the abnormal response of a non-mechanical sensor due to external mechanical vibration; mechanical vibration can influence acoustic sensors in reverse through resonance. Testing the sensor's mechanical cross-field vulnerability requires a mechanical cross-field input to observe whether there is an out-of-limit output caused by non-ideal mapping; simultaneously, an out-of-limit input is required to observe whether there is a mechanical cross-field output caused by non-ideal mapping.

[0058] Step 225: When the expected input physical field signal of the sensor does not include the thermal signal, perform thermal cross-field vulnerability analysis test on the sensor to obtain the thermal cross-field vulnerability analysis sub-result.

[0059] Specifically, in step 225, a thermal cross-field vulnerability analysis test is performed on the sensor to obtain the thermal cross-field vulnerability analysis sub-results, including: Step 2251: Set up multiple sets of heat signals; the multiple sets of heat signals include heat signals under different heat levels; Step 2252: Perform multiple thermal signal injection tests on the sensor. If the sensor output signal shows an abnormal response or thermal signal is present during the injection test, the result of the thermal cross-field vulnerability analysis of the sensor is determined to be thermal cross-field vulnerability.

[0060] Specifically, in step 2252, a heat source is used as the signal transmitter, and an infrared detector is used as the sensor. Thermal cross-field refers to the measurement deviation caused by external temperature changes in non-temperature sensors. In high-precision measurement scenarios, even small deviations caused by temperature can be maliciously exploited. Testing the sensor's thermal cross-field vulnerability requires thermal cross-field input to observe whether there is any out-of-limit output caused by non-ideal mapping; simultaneously, it requires out-of-limit input to observe whether there is any thermal cross-field output caused by non-ideal mapping.

[0061] The following experiments were conducted on a MEMS accelerometer based on the method described in this application.

[0062] 1. Out-of-band vulnerability analysis of MEMS accelerometers.

[0063] 1) After consulting the relevant documentation for MEMS accelerometers, it was learned that they are used to sense motion signals and utilize the inertia of an oscillator. Based on the out-of-band vulnerability analysis theory, the following analysis can be performed.

[0064] 2) Analysis of Vulnerability to Exceeding Limits. Here, we take amplitude exceeding-limit vulnerability as an example. An amplitude exceeding-limit signal is designed based on the maximum induced acceleration value of the MEMS accelerometer. Using a signal injection device, the amplitude exceeding-limit signal is injected into the MEMS accelerometer. It is observed that the sensor's output signal exhibits saturation, thus demonstrating that the MEMS accelerometer possesses amplitude exceeding-limit vulnerability.

[0065] 3) Analysis of Cross-Field Vulnerability. Here, we take acoustic cross-field vulnerability analysis as an example. The acoustic signal is designed as a swept-frequency signal, with a sweep range of 0~30kHz. The amplitude of the acoustic signal is varied to obtain multiple sets of acoustic signals. Using a signal injection device, the acoustic signal is injected into a MEMS accelerometer. It is observed that under the influence of the acoustic signal, the output of the MEMS accelerometer changes drastically at certain fixed frequency points. Furthermore, research shows that MEMS accelerometers in mobile phones can sense the minute vibrations of human speech, and thus demodulate the speaker's voice from these vibrations, achieving acoustic side-channel attacks. Both of these findings demonstrate that MEMS accelerometers possess acoustic cross-field vulnerability.

[0066] In one exemplary embodiment, a computer device is provided, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the computer program to implement a sensor out-of-band vulnerability analysis method based on over-limit and cross-field conditions.

[0067] In one exemplary embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements a method for analyzing sensor out-of-band vulnerability based on over-limit and cross-field conditions.

[0068] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements a method for out-of-band vulnerability analysis of sensors based on over-limit and cross-field conditions.

[0069] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 4As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and databases. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a sensor out-of-band vulnerability analysis method based on over-limit and cross-field conditions.

[0070] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0071] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile 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 many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0072] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0073] 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, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0074] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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 specification.

[0075] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for analyzing the out-of-band vulnerability of sensors based on exceeding limits and crossing fields, characterized in that, The sensor out-of-band vulnerability analysis method based on exceeding limits and crossing fields includes: Define a sensor out-of-band vulnerability model; the sensor out-of-band vulnerability model is used to describe the sensor out-of-band mapping, which includes overlimit mapping and cross-field mapping; the overlimit mapping is the mapping between the input signal and the output signal when the sensor's input signal is the expected input physical field signal but exceeds the overlimit parameter; the cross-field mapping is the mapping between the input signal and the output signal when the sensor's input signal is an unexpected input physical field signal. Based on the sensor out-of-band vulnerability model, the sensor's out-of-band vulnerability is analyzed and tested to obtain the sensor's out-of-band vulnerability analysis results; the out-of-band vulnerability analysis results include over-limit vulnerability analysis results and cross-field vulnerability analysis results.

2. The sensor out-of-band vulnerability analysis method based on over-limit and cross-field conditions according to claim 1, characterized in that, Based on the aforementioned sensor out-of-band vulnerability model, the sensor's out-of-band vulnerability is analyzed and tested, yielding the sensor's out-of-band vulnerability analysis results, including: Based on the aforementioned over-limit mapping, the over-limit vulnerability of the sensor is analyzed and tested, and the over-limit vulnerability analysis results are obtained. Based on the cross-field mapping, the cross-field vulnerability of the sensor is analyzed and tested, and the cross-field vulnerability analysis results are obtained.

3. The sensor out-of-band vulnerability analysis method based on over-limit and cross-field conditions according to claim 2, characterized in that, The results of the vulnerability analysis beyond the limits include: sub-results of amplitude vulnerability analysis and sub-results of frequency vulnerability analysis; The sensor's vulnerability beyond its limits was analyzed and tested, and the results of the vulnerability analysis were obtained, including: Obtain the sensor's out-of-limit parameters; the out-of-limit parameters include: the upper limit of the amplitude and the upper limit of the frequency of the input signal; Based on the aforementioned out-of-limit parameters, the amplitude out-of-limit signal and the frequency out-of-limit signal are determined; The sensor was subjected to injection tests using amplitude over-limit signals and frequency over-limit signals respectively, and the results of the amplitude over-limit vulnerability analysis and the frequency over-limit vulnerability analysis were determined.

4. The sensor out-of-band vulnerability analysis method based on over-limit and cross-field conditions according to claim 3, characterized in that, Based on the aforementioned out-of-limit parameters, the amplitude out-of-limit signal and the frequency out-of-limit signal are determined, including: The input signal that does not exceed the frequency limit but exceeds the amplitude limit is defined as the amplitude over-limit signal; An input signal that exceeds the frequency limit but does not exceed the amplitude limit is defined as a frequency over-limit signal.

5. The sensor out-of-band vulnerability analysis method based on over-limit and cross-field conditions according to claim 3, characterized in that, Injection tests were performed on the sensor using amplitude and frequency out-of-limit signals, respectively, to determine the sub-results of amplitude and frequency out-of-limit vulnerability analysis, including: An amplitude over-limit signal injection test is performed on the sensor. If the sensor's output signal exhibits saturation during the injection test, the amplitude over-limit vulnerability analysis result of the sensor is determined to be that amplitude over-limit vulnerability exists. The sensor is subjected to frequency over-limit signal injection test. If the sensor output signal exhibits nonlinearity or aliasing effect during the injection test, the frequency over-limit vulnerability analysis result of the sensor is determined to be that frequency over-limit vulnerability exists.

6. The sensor out-of-band vulnerability analysis method based on over-limit and cross-field conditions according to claim 2, characterized in that, The cross-field vulnerability analysis results include at least one of the following: acoustic cross-field vulnerability analysis sub-results, optical cross-field vulnerability analysis sub-results, electromagnetic cross-field vulnerability analysis sub-results, mechanical cross-field vulnerability analysis sub-results, and thermal cross-field vulnerability analysis sub-results; The cross-field vulnerability of the sensor was analyzed and tested, and the cross-field vulnerability analysis results were obtained, including: When the expected input physical field signal of the sensor does not include the acoustic signal, the sensor is subjected to acoustic cross-field vulnerability analysis test to obtain the acoustic cross-field vulnerability analysis sub-results; When the expected input physical field signal of the sensor does not include the optical signal, the sensor is subjected to optical cross-field vulnerability analysis test to obtain the optical cross-field vulnerability analysis sub-results; When the expected input physical field signal of the sensor does not include electromagnetic signals, an electromagnetic cross-field vulnerability analysis test is performed on the sensor to obtain the electromagnetic cross-field vulnerability analysis sub-results. When the expected input physical field signal of the sensor does not include mechanical signals, a mechanical cross-field vulnerability analysis test is performed on the sensor to obtain the mechanical cross-field vulnerability analysis sub-results; When the expected input physical field signal of the sensor does not include the thermal signal, a thermal cross-field vulnerability analysis test is performed on the sensor to obtain the thermal cross-field vulnerability analysis sub-result.

7. The sensor out-of-band vulnerability analysis method based on over-limit and cross-field conditions according to claim 6, characterized in that, The sensor underwent acoustic cross-field vulnerability analysis, yielding sub-results, including: Set up multiple sets of sound signals; the multiple sets of sound signals include sound signals with different frequencies and amplitudes; Multiple sets of acoustic signal injection tests were performed on the sensor. If the sensor's output signal exhibited abnormal resonance or an acoustic signal was present during the injection test, the acoustic cross-field vulnerability analysis result of the sensor was determined to be that acoustic cross-field vulnerability exists.

8. The sensor out-of-band vulnerability analysis method based on over-limit and cross-field conditions according to claim 6, characterized in that, Optical cross-field vulnerability analysis was performed on the sensor, and the sub-results of the optical cross-field vulnerability analysis were obtained, including: Set up multiple sets of optical signals; the multiple sets of optical signals include optical signals with different frequencies and amplitudes; Multiple sets of optical signal injection tests were performed on the sensor. If the sensor's output signal exhibited abnormal resonance, bias, or the presence of optical signals during the injection test, the result of the optical cross-field vulnerability analysis of the sensor was determined to be that optical cross-field vulnerability exists.

9. The sensor out-of-band vulnerability analysis method based on over-limit and cross-field conditions according to claim 6, characterized in that, Electromagnetic cross-field vulnerability analysis was performed on the sensor, and the sub-results of the electromagnetic cross-field vulnerability analysis were obtained, including: Set up multiple sets of electromagnetic signals; these multiple sets of electromagnetic signals include electromagnetic signals with different frequencies and amplitudes. Multiple sets of electromagnetic signal injection tests were performed on the sensor. If the sensor's output signal showed an abnormal response or electromagnetic signal was present during the injection test, the electromagnetic cross-field vulnerability analysis result of the sensor was determined to be electromagnetic cross-field vulnerability.

10. The sensor out-of-band vulnerability analysis method based on over-limit and cross-field conditions according to claim 6, characterized in that, Mechanical cross-field vulnerability analysis was performed on the sensor, and the sub-results of the mechanical cross-field vulnerability analysis were obtained, including: Set multiple sets of mechanical signals; these multiple sets of mechanical signals include mechanical signals with different frequencies and amplitudes. Multiple sets of mechanical signal injection tests were performed on the sensor. If the sensor's output signal showed an abnormal response or mechanical signal was present during the injection test, the mechanical cross-field vulnerability analysis result of the sensor was determined to be that mechanical cross-field vulnerability exists.

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