APPARATUS AND METHOD FOR DELIBERATE ATTACK SIMULATION TO EVALUATE THE PERFORMANCE OF FMCW LiDAR SENSOR

Abstract

The present invention relates to a device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor, comprising: a sensor fixing part for fixing an FMCW (Frequency Modulated Continuous Wave) lidar sensor; a light source control part for controlling the output and operation method of an attack light source; a sensor monitoring part for monitoring the signal output of the FMCW lidar sensor; and a processor for controlling the overall operation of the sensor fixing part, the light source control part, and the sensor monitoring part; wherein the processor is characterized by adjusting the alignment state and output characteristics of the attack light source for the FMCW lidar sensor in conjunction with the light source control part and the alignment control part.

Description

Technology Field

[0001] The present invention relates to an apparatus and method for simulating an intentional attack for evaluating the performance of a Frequency Modulated Continuous Wave (FMCW) lidar sensor, which enables the FMCW lidar sensor to quantitatively evaluate its performance against malicious physical attacks. Background Technology

[0003] Unlike the conventional Time of Flight (ToF) method, Frequency Modulated Continuous Wave (FMCW) LiDAR uses a method that calculates distance and relative velocity by analyzing the frequency difference of a laser beam that is emitted with continuous frequency modulation and reflected back. This provides higher distance resolution and accuracy than conventional ToF-based LiDAR and has the advantage of ensuring robust performance under various environmental conditions.

[0004] LiDAR sensors play a critical role in autonomous vehicles and security systems by detecting surrounding objects and preventing collisions. However, there have recently been reports of cases where the detection capabilities of LiDAR sensors are disrupted through deliberate physical attacks (e.g., optical interference, signal modulation, etc.). Such attacks degrade the reliability of the sensors, potentially causing malfunctions in autonomous driving and security systems.

[0005] In particular, due to the characteristics of the signal modulation method, FMCW LiDAR can be vulnerable to interference in specific frequency bands, and there is a possibility of intentional errors being caused by attacks such as spoofing (inducing false positives through signal modulation) and jamming (blocking signals).

[0006] Accordingly, there is an increasing need for systematic evaluation methods and devices capable of more quantitatively assessing the performance of LiDAR sensors and testing their robustness against malicious physical attacks.

[0007] Existing methods for evaluating LiDAR sensor performance are primarily focused on assessing detection accuracy and distance resolution (i.e., the minimum distance difference required to distinguish between two different objects in an FMCW LiDAR sensor) in general environments (i.e., environments without physical attacks), and there is a lack of standardized test environments capable of verifying performance by systematically simulating malicious attacks.

[0008] In particular, existing physical attack simulation methods are limited to simple environmental reproduction, resulting in insufficient repeatability, and the lack of precise control over attack methods limits the acquisition of reliable evaluation data. Furthermore, since response capabilities vary by sensor, detailed performance evaluations tailored to individual LiDAR models are required.

[0009] The background technology of the present invention is disclosed in Korean Patent No. 10-2594663 (registered on October 23, 2023). The problem to be solved

[0011] According to one aspect of the present invention, the present invention is created to solve the above-mentioned problems and aims to provide an apparatus and method for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor, which enables the FMCW lidar sensor to quantitatively evaluate its robustness against malicious physical attacks (e.g., optical interference, signal modulation, etc.).

[0012] According to another aspect, the present invention aims to provide an apparatus and method for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor, which enables the construction of a repeatable environment by precisely controlling the output and operation method of an attack light source.

[0013] According to another aspect, the present invention aims to provide an apparatus and method for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor, which analyzes the output data of the sensor to quantitatively measure the impact of the attack and enables a highly reliable performance evaluation based thereon. means of solving the problem

[0015] A device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor according to one aspect of the present invention comprises: a sensor fixing part for fixing a Frequency Modulated Continuous Wave (FMCW) lidar sensor; a light source control part for controlling the output and operation method of an attack light source; a sensor monitoring part for monitoring the signal output of the FMCW lidar sensor; and a processor for controlling the overall operation of the sensor fixing part, the light source control part, and the sensor monitoring part; wherein the processor is characterized by adjusting the alignment state and output characteristics of the attack light source for the FMCW lidar sensor in conjunction with the light source control part and the alignment control part.

[0016] In the present invention, the processor is characterized by setting the output intensity, frequency, and modulation method of the attack light source in conjunction with the light source control unit before performing an attack on the FMCW lidar sensor, and selecting a Pulse Wave or Continuous Wave mode according to the characteristics of the FMCW lidar sensor.

[0017] In the present invention, the alignment control unit adjusts the relative position and angle of the attack light source and the FMCW lidar sensor so that the attack light source is aligned within the detection range of the FMCW lidar sensor, and the processor stores the alignment state of the attack light source and the FMCW lidar sensor to maintain test conditions for repeated reproduction.

[0018] In the present invention, the light source control unit is characterized by adjusting the frequency band of the attack light source in accordance with the signal processing characteristics of the FMCW lidar sensor so that the FMCW lidar sensor can perform an attack in a vulnerable frequency range.

[0019] In the present invention, the sensor monitoring unit collects point cloud data output from the FMCW lidar sensor, analyzes changes before and after the execution of an attack, and determines whether a jamming attack has occurred based on whether a distance value is not detected or whether a distance value is returned infinitely.

[0020] In the present invention, the sensor monitoring unit is characterized by analyzing the difference between the distance value detected by the FMCW lidar sensor and the actual distance value to determine whether a spoofing attack has occurred.

[0021] The present invention further comprises a light source fixing part having a rotating stage to which the attack light source is fixed; and the processor is characterized by adjusting the rotation angle of the attack light source through the rotation of the rotating stage to perform an attack on the FMCW lidar sensor at various angles.

[0022] In the present invention, the processor is characterized by generating a performance evaluation report of the FMCW lidar sensor by comparing data before and after an attack based on the analysis results of the sensor monitoring unit.

[0023] In the present invention, the sensor fixing part is designed to allow the FMCW lidar sensor to be evaluated to be positioned at various heights and angles, and is characterized by increasing the repeatability of the test by adjusting the mounting environment of the FMCW lidar sensor to a specified height and angle.

[0024] In the present invention, the attack light source is formed to include an attack confirmation light source and a LiDAR attack light source, wherein the attack confirmation light source is a light source that emits light in the visible light band to enable visual confirmation of the location of the attack light source, and the LiDAR attack light source is characterized by including a laser light source in the infrared band that performs an actual attack affecting the FMCW LiDAR sensor.

[0026] A method for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor according to another aspect of the present invention comprises: a step in which a processor of an intentional attack simulation device, wherein an FMCW lidar sensor is fixed to a sensor fixing part and an attack light source is fixed to a light source fixing part, controls the output and operation method of the attack light source through a light source control part; a step in which the processor adjusts the alignment state and output characteristics of the attack light source for the FMCW lidar sensor in conjunction with the light source control part and the alignment control part; and a step in which the processor monitors the signal output of the FMCW lidar sensor through a sensor monitoring part.

[0027] In the present invention, in the step of controlling the output and operation method of the attack light source, the processor is characterized by setting the output intensity, frequency, and modulation method of the attack light source in conjunction with the light source control unit before performing an attack of the FMCW lidar sensor, and selecting a Pulse Wave or Continuous Wave mode according to the characteristics of the FMCW lidar sensor.

[0028] In the present invention, in the step of adjusting the alignment state and output characteristics of the attack light source, the alignment control unit adjusts the relative position and angle of the attack light source and the FMCW lidar sensor so that the attack light source is aligned within the detection range of the FMCW lidar sensor, and the processor stores the alignment state of the attack light source and the FMCW lidar sensor to maintain test conditions for repeated reproduction.

[0029] In the present invention, in the step of controlling the output and operation method of the attack light source, the light source control unit adjusts the frequency band of the attack light source in accordance with the signal processing characteristics of the FMCW lidar sensor so that the FMCW lidar sensor can perform an attack in a vulnerable frequency range.

[0030] In the present invention, in the step of monitoring the signal output of the FMCW lidar sensor, the sensor monitoring unit collects point cloud data output from the FMCW lidar sensor, analyzes changes before and after the execution of an attack, and determines whether a jamming attack has occurred based on whether a distance value is not detected or whether a distance value is returned infinitely.

[0031] In the present invention, in the step of monitoring the signal output of the FMCW lidar sensor, the sensor monitoring unit is characterized by analyzing the difference between the distance value detected by the FMCW lidar sensor and the actual distance value to determine whether a spoofing attack has occurred.

[0032] In the present invention, in the step of adjusting the alignment state and output characteristics of the attack light source, the processor adjusts the rotation angle of the attack light source through the rotation of the rotation stage of the light source fixing part to which the attack light source is fixed, thereby performing an attack on the FMCW lidar sensor at various angles.

[0033] In the present invention, after the step of monitoring the signal output of the FMCW lidar sensor, the processor generates a performance evaluation report of the FMCW lidar sensor by comparing data before and after the execution of an attack based on the analysis results of the sensor monitoring unit. Effects of the invention

[0035] According to one aspect, the present invention enables the evaluation of the robustness of a sensor by precisely simulating a malicious physical attack on an FMCW lidar sensor.

[0036] According to one aspect, the present invention enables the establishment of a repeatable performance evaluation environment by controlling the output and operation method of an attack light source.

[0037] According to one aspect, the present invention enables the quantitative evaluation of the impact of attacks such as jamming and spoofing by analyzing the output data of a sensor.

[0038] According to one aspect, the present invention enables verification of performance in various environments by applying attack scenarios tailored to the signal characteristics of each LiDAR sensor.

[0039] According to one aspect, the present invention improves the reliability of LiDAR sensors used in autonomous driving and security systems, thereby enhancing safety. Brief explanation of the drawing

[0041] FIG. 1 is an exemplary diagram showing the schematic configuration of a deliberate attack simulation device for evaluating the performance of an FMCW lidar sensor according to one embodiment of the present invention. FIG. 2 is a flowchart illustrating a control method for a deliberate attack simulation device for evaluating the performance of an FMCW lidar sensor according to an embodiment of the present invention. FIG. 3 is an exemplary diagram schematically showing the structure of a sensor fixing part that fixes a lidar sensor to be evaluated in a device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor according to one embodiment of the present invention. FIG. 4 is an exemplary diagram schematically showing the mounting structure of a lidar sensor to be evaluated in a device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor according to one embodiment of the present invention. FIG. 5 is an exemplary diagram shown to explain the structure and operation of a light source fixing part that fixes an attack light source in a device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor according to one embodiment of the present invention. FIG. 6 is an exemplary diagram showing the configuration of an attack light source in a device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor according to one embodiment of the present invention. FIG. 7 is an example diagram for explaining the operation of the light source control unit in FIG. 1. FIG. 8 is an exemplary diagram showing the response of an FMCW LiDAR sensor according to the operating method of an attack light source in a device for simulating an intentional attack for evaluating the performance of an FMCW LiDAR sensor according to one embodiment of the present invention. FIG. 9 is an exemplary diagram illustrating the rotational movement of an attack light source and the process of performing an attack on a sensor in a device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor according to one embodiment of the present invention. FIG. 10 is an example diagram illustrating the comparison of frequency changes when normal signal processing and jamming attacks are performed in a device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor according to one embodiment of the present invention. FIG. 11 is an example diagram for comparing and explaining frequency changes when normal signal processing and spoofing attacks are performed in a device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor according to one embodiment of the present invention. Specific details for implementing the invention

[0042] Hereinafter, an embodiment according to the present invention will be described with reference to the attached drawings.

[0043] In this process, the thickness of lines or the size of components depicted in the drawings may be exaggerated for the sake of clarity and convenience of explanation. Furthermore, the terms described below are defined considering their functions in the present invention, and these may vary depending on the intent or convention of the user or operator. Therefore, the definitions of these terms should be based on the content throughout this specification.

[0044] Embodiments of the present invention are described below with reference to the attached drawings so that those skilled in the art can easily implement them. However, the present invention may be embodied in various different forms and is not limited to the embodiments described herein. Furthermore, in order to clearly explain the present invention in the drawings, parts unrelated to the explanation have been omitted, and similar parts throughout the specification are denoted by similar reference numerals.

[0045] Throughout the specification, when a part is described as "including" a certain component, this means that, unless specifically stated otherwise, it does not exclude other components but may include additional components.

[0046] Terms and words used in this specification and claims should not be interpreted as being limited to their ordinary or dictionary meanings, but should be interpreted in a meaning and concept consistent with the technical spirit of the invention, based on the principle that the inventor can appropriately define the concept of the terms to best describe his invention.

[0047] Accordingly, the embodiments described in this specification and the configurations illustrated in the drawings are merely some of the most preferred embodiments of the invention and do not represent all of the technical spirit of the invention; therefore, it should be understood that various equivalents and modifications capable of replacing them may exist at the time of filing this application. Furthermore, as used herein, "comprise" or "include" and / or "comprising" or "including" specify the presence of the mentioned features, numbers, steps, actions, parts, elements, and / or groups thereof, and do not exclude the presence or addition of one or more other features, numbers, actions, parts, elements, and / or groups. Additionally, when describing embodiments of the invention, "may" or "may be" may include "one or more embodiments of the invention."

[0048] Additionally, to aid in understanding the invention, the attached drawings are not drawn to actual scale, and the dimensions of some components may be exaggerated. Furthermore, the same reference numerals may be assigned to identical components in different embodiments.

[0049] The statement that two subjects of comparison are 'identical' means that they are 'substantially identical.' Therefore, substantial identity may include deviations considered low in the industry, for example, deviations within 5%. Additionally, the statement that a parameter is uniform in a given area may mean that it is uniform from an average perspective.

[0050] Although terms such as "first," "second," etc., are used to describe various components, it goes without saying that these components are not limited by these terms. These terms are used merely to distinguish one component from another, and unless specifically stated otherwise, the first component may also be the second component.

[0051] Throughout the specification, unless specifically stated otherwise, each component may be singular or plural.

[0052] The fact that any configuration is placed on the “upper (or lower)” of a component or on the “upper (or lower)” of a component may mean not only that the any configuration is placed in contact with the upper (or lower) surface of said component, but also that another configuration may be interposed between said component and any configuration placed on (or below) said component.

[0053] Furthermore, where it is stated that one component is “connected,” “coupled,” or “joined” to another component, it should be understood that while said components may be directly connected or joined to one another, another component may be “interposed” between each component, or that each component may be “connected,” “coupled,” or “joined” through another component. Additionally, when it is stated that a part is electrically coupled to another part, this includes not only cases where they are directly connected but also cases where they are connected with an intermediate element in between.

[0054] Throughout the specification, “A and / or B” means A, B, or A and B unless specifically stated otherwise. That is, “and / or” includes any combination or any combination of the enumerated items. “C to D” means C or more and D or less, unless specifically stated otherwise.

[0056] FIG. 1 is an exemplary diagram showing the schematic configuration of a deliberate attack simulation device for evaluating the performance of an FMCW lidar sensor according to one embodiment of the present invention.

[0057] Referring to FIG. 1, the intentional attack simulation device for evaluating the performance of an FMCW lidar sensor according to the present embodiment may include a processor (110), a light source control unit (120), an alignment control unit (130), and a sensor monitoring unit (140).

[0058] The processor (110) is a central computing unit (i.e., main controller) that controls the overall operation of the intentional attack simulation device for evaluating the performance of the FMCW lidar sensor.

[0059] The processor (110) can control the output and operation method of the attack light source by adjusting the operation of the light source control unit (120).

[0060] The processor (110) can communicate with the alignment control unit (130) to adjust the alignment state of the attack light source and the FMCW lidar sensor.

[0061] The processor (110) can collect data from the sensor monitoring unit (140), analyze the response of the LiDAR sensor, and evaluate the impact of the attack.

[0062] The light source control unit (120) can implement various attack scenarios by controlling the output and operation method of the attack light source.

[0063] The light source control unit (120) can receive a control command from the processor (110) and adjust the output intensity of the attack light source.

[0064] The light source control unit (120) can perform an attack in a pulse wave or continuous wave manner according to the signal processing characteristics of the FMCW lidar sensor.

[0065] The light source control unit (120) can adjust the frequency band of the attack light source to perform an attack in a frequency range where a specific sensor is vulnerable.

[0066] The alignment control unit (130) can optimize the evaluation environment by precisely aligning the attack light source and the FMCW lidar sensor.

[0067] The alignment control unit (130) can receive a control signal from the processor (110) and adjust the direction and placement of the attack light source.

[0068] The alignment control unit (130) can adjust the position and height so that the LiDAR sensor targeted for attack and the attack light source can cause optimal interference in a straight line.

[0069] The alignment control unit (130) can simulate the mounting environment in an actual autonomous vehicle by adjusting the fixing device of the sensor.

[0070] The sensor monitoring unit (140) can collect output data from the FMCW lidar sensor and analyze the impact of the attack.

[0071] The sensor monitoring unit (140) can collect Point Cloud Data output from the FMCW LiDAR sensor and analyze changes before and after the attack.

[0072] The sensor monitoring unit (140) can detect whether the distance value appears as infinite in the output data of the sensor to determine whether jamming (signal interference) is occurring.

[0073] The sensor monitoring unit (140) can analyze how much the distance value detected by the sensor differs from the actual value in order to determine whether there is spoofing (signal modulation).

[0074] The sensor monitoring unit (140) quantitatively measures the impact of an attack and transmits it to the processor (110), enabling the robustness of the FMCW lidar sensor to be evaluated based on this.

[0075] Meanwhile, in FIG. 1, each component (110 to 140) is described as operating separately, but this is not intended to be limited, and depending on the embodiment, each component (110 to 140) may be integrated into the processor (110).

[0076] FIG. 2 is a flowchart illustrating a control method for a deliberate attack simulation device for evaluating the performance of an FMCW lidar sensor according to an embodiment of the present invention.

[0077] Referring to FIG. 2, in the FMCW lidar sensor and attack light source alignment step (S101), the alignment control unit (130) can align the position of the attack light source within the detection range of the FMCW lidar sensor. The alignment control unit (130) can set test conditions by adjusting the height and angle of the attack light source and the FMCW lidar sensor. Additionally, the processor (110) can save the initial alignment state before performing the attack.

[0078] In the step (S102) for setting attack light source control parameters (e.g., output intensity, frequency, modulation method), the light source control unit (120) can set the output intensity and frequency of the light source to be used for the attack. The processor (110) can select a Pulse Wave or Continuous Wave mode by considering the characteristics of the FMCW LiDAR sensor. Additionally, the light source control unit (120) can set an appropriate bandwidth and modulation method according to the signal processing characteristics of each sensor.

[0079] In the step (S103) of performing the operation of the attack light source (e.g., Pulse Wave / Continuous Wave), the light source control unit (120) can receive a control signal from the processor (110) and execute a set attack mode. The light source control unit (120) can emit a signal that affects the FMCW lidar sensor according to the set frequency and modulation method. The alignment control unit (130) can verify whether the attack light source is accurately aimed at a set position.

[0080] In the step of collecting and analyzing sensor response data (Point Cloud Data) (S104), the sensor monitoring unit (140) can collect LiDAR sensor outputs before and after an attack and store Point Cloud Data. The sensor monitoring unit (140) can evaluate the impact of the attack by analyzing information such as distance values, reflectance, and data density detected by the sensor. The processor (110) can compare and analyze the normal state and the post-attack state based on the collected data.

[0081] In the attack impact assessment (analysis of whether jamming or spoofing occurs) step (S105), the sensor monitoring unit (140) can check for data where distance cannot be detected (infinite distance value) to determine whether jamming is occurring. The sensor monitoring unit (140) can analyze the difference between the actual distance and the measured distance value to determine whether spoofing is occurring. The processor (110) quantitatively analyzes the attack results and evaluates the robustness of the FMCW lidar sensor by comparing it with performance evaluation criteria.

[0082] In the result storage and performance evaluation report generation step (S106), the processor (110) can generate a performance evaluation report by storing the attack execution results and analysis data. The processor (110) can calculate robustness evaluation indicators for each sensor and provide performance evaluation results of the LiDAR sensor based thereon. The sensor monitoring unit (140) can visualize and analyze data changes that occurred during the attack execution.

[0083] As such, this embodiment systematically executes attack scenarios to quantitatively evaluate the performance of the FMCW lidar sensor, and can automate the entire process from attack impact assessment to report generation.

[0084] FIG. 3 is an exemplary diagram schematically showing the structure of a sensor fixing part that fixes a lidar sensor to be evaluated in a device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor according to one embodiment of the present invention.

[0085] Referring to FIG. 3, the sensor fixing part (210) according to the present embodiment is implemented in a form that stably fixes the lidar sensor to be evaluated and enables performance evaluation to be performed at various angles and heights.

[0086] The sensor fixing part (210) includes a fixing plate, and allows the LiDAR sensor to be evaluated to be mounted on the fixing plate so as to be fixed without shaking in a test environment.

[0087] The sensor fixing part (210) includes a mounting height adjustment function, allowing the height of the lidar sensor to be adjusted according to the test environment.

[0088] The sensor fixing part (210) includes an angle adjustment function using an electric motor (not shown), allowing the LiDAR sensor to be adjusted so that it can be aligned with an attack light source from various directions.

[0089] The sensor fixing part (210) is configured to reproduce conditions similar to the sensor mounting position in an actual autonomous vehicle, and to increase the precision of the test conditions.

[0090] In this embodiment, the sensor fixing part (210) ensures that the sensor is stably maintained at a constant position when performing a performance evaluation of the FMCW lidar sensor, and allows for the establishment of a more reliable test environment by adjusting the alignment with the attack light source.

[0091] FIG. 4 is an exemplary diagram schematically showing the mounting structure of a lidar sensor to be evaluated in a device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor according to one embodiment of the present invention.

[0092] Referring to FIG. 4, the mounting structure of the lidar sensor to be evaluated according to the present embodiment includes a bracket and an adjustment device for stably fixing the lidar sensor to be evaluated in a test environment and facilitating alignment with an attack light source.

[0093] In the front structure, the lidar sensor under evaluation is mounted on a bracket, allowing the placement status of the lidar sensor under evaluation to be checked from the front.

[0094] The rear structure includes an interface and wiring connected to the rear of the lidar sensor under evaluation, enabling real-time monitoring of the lidar sensor's output.

[0095] The bracket (220) serves to support the lidar sensor under evaluation and is designed to allow height and angle adjustment, thereby optimizing alignment with the attack light source.

[0096] The joint between the lidar sensor to be evaluated and the bracket (220) is configured to stably fix the sensor, thereby minimizing positional changes of the lidar sensor to be evaluated during testing.

[0097] FIG. 5 is an exemplary diagram shown to explain the structure and operation of a light source fixing part that fixes an attack light source in a device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor according to one embodiment of the present invention.

[0098] Referring to FIG. 5, the attack light source according to the present embodiment is mounted on a rotating stage and is configured to perform attacks at various angles and heights.

[0099] The attack light source (320) is mounted on a rotating stage and can be aligned in a specific direction according to the operation of the rotating stage.

[0100] The rotating stage can adjust the direction of the attack light source (320) and allow the attack to be performed at a specific angle.

[0101] The attack light source (320) is designed to be height-adjustable, allowing for the configuration of an optimal attack scenario according to the mounting position of the FMCW lidar sensor being evaluated.

[0102] When performing an attack, the attack light source (320) emits light at a set output and frequency band and can operate in a manner that affects the detection performance of the FMCW lidar sensor.

[0103] The operation of the attack light source (320) is controlled by the light source control unit (120) and can be modulated in a pulse wave or continuous wave manner.

[0104] The light source control unit (120) moves the attack light source (320) within a predefined attack execution range and enables sequential repeated attacks to be performed.

[0105] The attack light source (320) is placed at an optimal location (designated location) where the FMCW lidar sensor can recognize it, and allows the sensor performance in various environments to be evaluated while adjusting the angle.

[0106] The light source fixing part (310) includes a rotating stage and can precisely adjust the rotation angle of the attack light source. The rotating stage is equipped with a digital level (not shown) to measure and record the movement angle of the attack light source (320) in real time. This configuration ensures repeatability, allowing the attack to be performed in the same environment.

[0107] Since the FMCW lidar sensor under evaluation operates in a specific signal band for each sensor, the light source fixing part (310) may use an appropriate attack light source (320) in accordance with the specifications of the FMCW lidar sensor under evaluation.

[0108] The attack light source (320) can have its frequency and output strength adjusted to match the signal processing characteristics of the lidar sensor, and can evaluate performance in a specific band.

[0109] In order to perform a spoofing attack, the light source fixing part (310) can analyze the light source information (bandwidth, band variable period) of the FMCW lidar sensor in advance.

[0110] The attack light source (320) emits a modulated signal in a band that matches the signal frequency of the FMCW lidar sensor being evaluated, so that the FMCW lidar sensor being evaluated can recognize an incorrect distance value.

[0111] The light source control unit (120) adjusts the wavelength of the attack light source (320) to enable an effective spoofing attack.

[0112] FIG. 6 is an exemplary diagram showing the configuration of an attack light source in a device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor according to one embodiment of the present invention.

[0113] Referring to FIG. 6, the attack light source (320) according to the present embodiment is composed of an 'attack confirmation light source (321)' and a 'LiDAR attack light source (322)', and their respective roles are distinguished.

[0114] The attack confirmation light source (321) emits light in the visible light band to allow the location of the attack light source to be visually confirmed. The attack confirmation light source (321) can be used as a reference point when adjusting alignment with the FMCW lidar sensor before performing an attack. This is because the attack light source in the infrared band cannot be seen with the naked eye, so a visible light confirmation light source is added to increase the accuracy of the light source alignment.

[0115] The LiDAR attack light source (322) includes a laser light source in the infrared band that performs an actual attack affecting the FMCW LiDAR sensor. The LiDAR attack light source (322) emits infrared light of a specific wavelength band according to the signal processing method of the LiDAR sensor to cause signal interference.

[0116] The LiDAR attack light source (322) has its output intensity and modulation method controlled by the light source control unit (120), enabling performance evaluation in various environments.

[0117] FIG. 7 is an example diagram for explaining the operation of the light source control unit in FIG. 1.

[0118] Referring to FIG. 7, the light source control unit (120) according to the present embodiment can perform various types of intentional attacks by adjusting the output and operation method of the attack light source (320).

[0119] The light source control unit (120) can set two main parameters for performing an attack.

[0120] First, through the output control parameter, the light source control unit (120) can adjust the intensity of the attack by controlling the output of the attack light source (320).

[0121] After adjusting the output, the light source control unit (120) can set the range for performing the attack.

[0122] When setting the attack execution range, the light source control unit (120) can set the spatial range to which the attack is applied so that signal interference or modulation can be performed only in a specific area.

[0123] Through the following operation mode (Pulse / CW selection) parameter, the light source control unit (120) can perform an attack in a Pulse Wave or Continuous Wave manner.

[0124] After setting the operation method, the light source control unit (120) can select (determine) the type of intentional attack to be performed.

[0125] For example, in selecting the type of intentional attack, various attack types such as Jamming and Spoofing can be selected.

[0126] FIG. 8 is an exemplary diagram showing the response of an FMCW LiDAR sensor according to the operating method of an attack light source in a device for simulating an intentional attack for evaluating the performance of an FMCW LiDAR sensor according to one embodiment of the present invention.

[0127] Referring to FIG. 8, the attack light source (320) according to the present embodiment can operate in a pulse wave or continuous wave manner, and accordingly, the FMCW LiDAR sensor can react differently.

[0128] When performing a pulse wave attack, the FMCW LiDAR sensor is designed to be primarily affected by jamming.

[0129] Jamming attacks can operate by interfering with a sensor's ability to measure normal distance values. For instance, a jamming attack can emit interference signals at a specific frequency to prevent the sensor from receiving signals or to cause it to return infinite distance values. In other words, a jamming attack can neutralize the receiver's function by transmitting a jamming signal to the receiver of an FMCW LiDAR sensor, thereby significantly lowering the Signal-to-Noise Ratio (SNR) of the original carrier signal that should be detected by the receiver.

[0130] When a Continuous Wave attack is performed, the FMCW LiDAR sensor may be affected by spoofing or jamming.

[0131] Spoofing attacks can distort distances, causing FMCW LiDAR sensors to recognize distance values ​​different from the actual ones. Continuous waves can cause continuous interference in the sensor's signal band, preventing the sensor from interpreting normal reflected signals. For example, if the sensor detects spoofing, it may output incorrect measurements indicating a distance that is closer or farther than the actual distance. In other words, spoofing attacks can cause non-existent objects to be perceived as present or existing objects to be perceived as being farther or closer by transmitting fake signals that do not actually exist to the receiver of the FMCW LiDAR sensor.

[0132] For reference, depending on the purpose and performance of each LiDAR sensor, an attack light source may be used to match the band of another sensor. If a specific wavelength band is insufficient, an artificial sunlight light source can be used to carry out the attack. To perform spoofing, wavelength information must be verified using the LiDAR light source information (e.g., bandwidth, band-variable period).

[0133] FIG. 9 is an exemplary diagram illustrating the rotational movement of an attack light source and the process of performing an attack on a sensor in a device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor according to one embodiment of the present invention.

[0134] Referring to FIG. 9, the attack light source (320) is mounted on the rotating stage of the light source fixing part (310), thereby allowing attacks to be performed from various angles.

[0135] The attack light source (320) is placed on a rotating stage and can perform a deliberate attack on the FMCW lidar sensor while rotating at a constant angle.

[0136] The rotating stage rotates according to the command of the light source control unit (120) and can emit a signal aimed in a specific direction.

[0137] The laser emitted from the attack light source (320) is directed toward the FMCW lidar sensor being evaluated and may cause interference in the sensor's signal collection process.

[0138] The sensor fixing part (210) stably fixes the FMCW lidar sensor to be evaluated and enables repetitive performance evaluation at a fixed position.

[0139] The sensor fixing part (210) maintains alignment with the attack light source (320) so that the test can be performed in a uniform environment.

[0140] The impact of an attack can be analyzed by comparing data in an environment where the FMCW lidar sensor being evaluated operates normally and in an environment where the attack light source (320) operates.

[0141] The rotating stage of the light source fixing part (310) can adjust the direction of the attack light source (320) and allows the change in performance at a specific angle to be measured for the FMCW lidar sensor under evaluation.

[0142] By using a digital level (not shown) mounted on the light source fixing part (310), the angle of the attack light source (320) can be precisely measured and recorded.

[0143] This embodiment enables the evaluation of signal interference effects based on the position and alignment of the FMCW LiDAR sensor to be evaluated by performing attacks from various angles using the light source fixing part (310) and the sensor fixing part (210).

[0144] FIG. 10 is an example diagram illustrating the comparison of frequency changes when normal signal processing and jamming attacks are performed in a device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor according to one embodiment of the present invention.

[0145] Referring to Figure 10, the left graph (Normal) shows the frequency change process of a normal FMCW lidar signal, and the right graph (Jamming) shows the process in which the frequency signal of the FMCW lidar sensor being evaluated is interfered with by an attack signal.

[0146] In the state of transmitting a normal FMCW lidar signal (Normal), the FMCW lidar sensor emits a transmitted signal (TX) by linearly modulating the frequency over time, and the reflected signal (RX) is measured as a received signal.

[0147] Under normal circumstances, distance measurement is performed based on the frequency difference between the TX and RX signals.

[0148] The difference between the transmitted signal (TX) and the received signal (RX) maintains a constant ratio, which enables the FMCW lidar sensor to calculate the accurate distance to an object.

[0149] If a jamming attack is performed, the jamming signal may be additionally inserted into the signal band of the FMCW lidar sensor, interfering with normal distance measurement.

[0150] At this time, the attack signal can be inserted in two ways (e.g., swept frequency, fixed frequency).

[0151] First, the Swept Frequency method varies the frequency in a manner similar to the transmitted signal, making it difficult for FMCW lidar sensors to distinguish normal reflected signals.

[0152] The following Fixed Frequency method continuously inserts a fixed frequency signal to induce the FMCW lidar sensor to malfunction in a specific frequency band.

[0153] If such a jamming attack is performed, the FMCW lidar sensor is highly likely to fail to recognize normal reflected signals (RX) or calculate incorrect distance values.

[0154] When such a jamming attack occurs, the FMCW lidar sensor may perceive the distance value as infinite or output a random distance value; by experimentally reproducing this attack, this supports the development of a defense algorithm that enables the FMCW lidar sensor to operate normally even in environments with signal interference.

[0155] The intentional attack simulation device according to the present embodiment enables the analysis of the robustness of the FMCW lidar sensor by quantitatively evaluating such jamming attacks.

[0156] FIG. 11 is an example diagram for comparing and explaining frequency changes when normal signal processing and spoofing attacks are performed in a device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor according to one embodiment of the present invention.

[0157] Referring to Figure 11, the left graph (Normal) shows the frequency change process of a normal FMCW lidar signal, and the right graph (Spoofing) shows the process in which the distance measurement of the FMCW lidar sensor is distorted by an attack signal.

[0158] In the state of transmitting a normal FMCW lidar signal (Normal), the FMCW lidar sensor emits a transmitted signal (TX) with a frequency that is linearly modulated over time, and the reflected signal (RX) is measured as a received signal.

[0159] Under normal circumstances, distance measurement is performed based on the frequency difference between the TX and RX signals.

[0160] The difference between the transmitted signal (TX) and the received signal (RX) maintains a constant ratio, which enables the FMCW lidar sensor to calculate the accurate distance to an object.

[0161] If a spoofing attack is performed, the spoofing signal is additionally inserted into the signal band of the FMCW lidar sensor, which can distort distance measurements.

[0162] Attack signals can be inserted using the Swept Frequency method, which is modulated into a form similar to a normal RX signal to confuse the FMCW lidar sensor.

[0163] FMCW lidar sensors may misidentify attack signals as actual reflected signals (RX) and output incorrect distance values.

[0164] As the frequency of the attack signal continuously changes, the sensor may measure the location of an object differently from the actual location.

[0165] As a result, FMCW lidar sensors are more likely to detect non-existent objects or perceive the location of actual objects at incorrect distances.

[0166] When a spoofing attack occurs in this way, the FMCW lidar sensor fails to provide normal distance data and may output distorted information.

[0167] By experimentally reproducing such attacks, it is possible to develop defense algorithms that enable FMCW lidar sensors to provide accurate data even in signal modulation environments.

[0168] The intentional attack simulation device of the present invention enables the analysis of the robustness of the FMCW lidar sensor by quantitatively evaluating such spoofing attacks.

[0169] Referring to FIGS. 10 and 11, the sensor monitoring unit (140) according to the present embodiment monitors the output data of the FMCW lidar sensor in real time when Jamming and Spoofing attacks are performed, and performs the role of analyzing the signal distortion phenomenon of the sensor.

[0170] In the analysis of the Jamming attack illustrated in FIG. 10, the sensor monitoring unit (140) can detect the effect of the Jamming signal in the received signal (RX) of the FMCW lidar sensor and analyze the data distortion caused by signal interference.

[0171] When a jamming attack is performed, the sensor monitoring unit (140) can determine whether swept frequency or fixed frequency interference occurs in the signal band of the FMCW lidar sensor. That is, the sensor monitoring unit (140) can determine whether the FMCW lidar sensor returns an infinite distance value due to jamming, or whether normal signal reception becomes impossible. Based on this data, the robustness of the FMCW lidar sensor against jamming attacks can be evaluated.

[0172] In the analysis of the spoofing attack illustrated in FIG. 11, the sensor monitoring unit (140) can analyze the impact of the spoofing attack by comparing the distance value detected by the sensor with the actual distance value.

[0173] When a spoofing signal is inserted by modulating it to resemble the normal receiving signal (RX) of the FMCW lidar sensor, the sensor monitoring unit (140) can determine whether the FMCW lidar sensor mistakes it for an actual reflected signal. That is, the sensor monitoring unit (140) can analyze whether the FMCW lidar sensor detects a non-existent object or distorts the distance of an actual object when measuring it.

[0174] The sensor monitoring unit (140) monitors the continuity of data output by the FMCW lidar sensor and can detect patterns that fluctuate abnormally due to spoofing attacks.

[0175] The sensor monitoring unit (140) can quantitatively evaluate the impact of the attack on the performance of the FMCW lidar sensor by comparing and analyzing data before and after the attack.

[0176] The sensor monitoring unit (140) can verify the performance of the defense algorithm by analyzing the accuracy and reliability of the data output by the FMCW lidar sensor after Jamming and Spoofing attacks are performed.

[0177] The sensor monitoring unit (140) can quantify the level of performance degradation by measuring factors such as the distance value error rate, data loss rate, and response time delay of the FMCW lidar sensor.

[0178] The sensor monitoring unit (140) can evaluate the limits that the FMCW lidar sensor can withstand for each type of attack and provide criteria for strengthening the security of the FMCW lidar sensor.

[0179] This embodiment enables the evaluation of the sensor's robustness by precisely simulating a malicious physical attack on an FMCW lidar sensor, and also enables the establishment of a repeatable performance evaluation environment by controlling the output and operation method of the attack light source.

[0180] This embodiment enables the quantitative evaluation of the impact of attacks such as jamming and spoofing by analyzing the output data of an FMCW LiDAR sensor, and enables the verification of performance in various environments by applying attack scenarios tailored to the signal characteristics of each LiDAR sensor.

[0181] This embodiment improves the reliability of LiDAR sensors used in autonomous driving and security systems, thereby enhancing safety.

[0182] The implementations described herein may be implemented, for example, as methods or processes, devices, software programs, data streams, or signals. Even if discussed only in the context of a single form of implementation (e.g., discussed only as a method), the implementation of the discussed features may also be implemented in other forms (e.g., devices or programs). Devices may be implemented in appropriate hardware, software, and firmware, etc. Methods may be implemented in devices such as processors, which generally refer to processing devices including, for example, computers, microprocessors, integrated circuits, or programmable logic devices. Processors also include communication devices such as computers, cell phones, portable / personal digital assistants ("PDAs"), and other devices that facilitate the communication of information between end-users.

[0183] Although the present invention has been described above by limited embodiments and drawings, the present invention is not limited thereto, and it is obvious that various modifications and variations are possible within the scope of the technical spirit of the present invention and the equivalent scope of the claims described below by those skilled in the art to which the present invention belongs. Explanation of the symbols

[0185] 110 : Processor 120 : Light source control unit 130 : Alignment control unit 140 : Sensor monitoring unit 210: Sensor fixing part 220 : Bracket 310 : Light source fixing part 320 : Attack Light Source 321: Attack confirmation light source 322 : LiDAR attack light source

Claims

Claim 1 An intentional attack simulation device for evaluating the performance of an FMCW (Frequency Modulated Continuous Wave) lidar sensor, comprising: a sensor fixing part for fixing an FMCW lidar sensor; a light source control part for controlling the output and operation method of an attack light source; a sensor monitoring part for monitoring the signal output of the FMCW lidar sensor; and a processor for controlling the overall operation of the sensor fixing part, the light source control part, and the sensor monitoring part; wherein the processor is characterized by adjusting the alignment state and output characteristics of the attack light source for the FMCW lidar sensor in conjunction with the light source control part and the alignment control part. Claim 2 A device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor according to claim 1, wherein the processor, in conjunction with the light source control unit, sets the output intensity, frequency, and modulation method of the attack light source before performing an attack on the FMCW lidar sensor, and selects a Pulse Wave or Continuous Wave mode according to the characteristics of the FMCW lidar sensor. Claim 3 A device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor, characterized in that, in claim 1, the alignment control unit adjusts the relative position and angle of the attack light source and the FMCW lidar sensor so that the attack light source is aligned within the detection range of the FMCW lidar sensor, and the processor stores the alignment state of the attack light source and the FMCW lidar sensor to maintain test conditions for repeated reproduction. Claim 4 In claim 1, the light source control unit is characterized by adjusting the frequency band of the attack light source to match the signal processing characteristics of the FMCW lidar sensor so that the FMCW lidar sensor can perform an attack in a vulnerable frequency range. Claim 5 In claim 1, the sensor monitoring unit collects point cloud data output from the FMCW lidar sensor, analyzes changes before and after the execution of an attack, and determines whether a jamming attack has occurred based on whether a distance value is not detected or whether the distance value returns infinity; the device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor. Claim 6 A device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor, characterized in that, in claim 1, the sensor monitoring unit analyzes the difference between the distance value detected by the FMCW lidar sensor and the actual distance value to determine whether a spoofing attack has occurred. Claim 7 A device for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor, wherein, in claim 1, it further comprises a light source fixing part equipped with a rotating stage to which the attack light source is fixed, and the processor adjusts the rotation angle of the attack light source through the rotation of the rotating stage to perform an attack targeting the FMCW lidar sensor at various angles. Claim 8 In claim 1, the intentional attack simulation device for evaluating the performance of an FMCW lidar sensor is characterized in that the processor generates a performance evaluation report of the FMCW lidar sensor by comparing data before and after the attack execution based on the analysis results of the sensor monitoring unit. Claim 9 In claim 1, the sensor fixing part is designed to allow the FMCW lidar sensor to be evaluated to be positioned at various heights and angles, and the mounting environment of the FMCW lidar sensor is adjusted to a specified height and angle to increase the repeatability of the test, thereby forming an intentional attack simulation device for evaluating the performance of an FMCW lidar sensor. Claim 10 A device for simulating an intentional attack for evaluating the performance of an FMCW LiDAR sensor, characterized in that, in claim 1, the attack light source is formed to include an attack confirmation light source and a LiDAR attack light source, the attack confirmation light source is a light source that emits light in the visible light band to enable visual confirmation of the location of the attack light source, and the LiDAR attack light source includes a laser light source in the infrared band that performs an actual attack affecting the FMCW LiDAR sensor. Claim 11 A method for simulating an intentional attack for evaluating the performance of an FMCW LiDAR sensor, characterized by comprising: a step in which a processor of an intentional attack simulation device controls the output and operation method of an attack light source through a light source control unit, wherein an FMCW LiDAR sensor is fixed to a sensor fixing unit and the attack light source is fixed to a light source fixing unit in the intentional attack simulation device; a step in which the processor adjusts the alignment state and output characteristics of the attack light source for the FMCW LiDAR sensor in conjunction with the light source control unit and the alignment control unit; and a step in which the processor monitors the signal output of the FMCW LiDAR sensor through a sensor monitoring unit. Claim 12 A method for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor, characterized in that, in the step of controlling the output and operation method of the attack light source, the processor, in conjunction with the light source control unit, sets the output intensity, frequency, and modulation method of the attack light source before performing an attack on the FMCW lidar sensor, and selects a Pulse Wave or Continuous Wave mode according to the characteristics of the FMCW lidar sensor. Claim 13 A method for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor, characterized in that, in the step of adjusting the alignment state and output characteristics of the attack light source, the alignment control unit adjusts the relative position and angle of the attack light source and the FMCW lidar sensor so that the attack light source is aligned within the detection range of the FMCW lidar sensor, and the processor stores the alignment state of the attack light source and the FMCW lidar sensor to maintain test conditions for repeated reproduction. Claim 14 A method for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor, characterized in that, in the step of controlling the output and operation method of the attack light source, the light source control unit adjusts the frequency band of the attack light source to match the signal processing characteristics of the FMCW lidar sensor so that the FMCW lidar sensor can perform an attack in a vulnerable frequency range. Claim 15 A method for simulating an intentional attack for evaluating the performance of an FMCW LiDAR sensor, characterized in that, in the step of monitoring the signal output of the FMCW LiDAR sensor, the sensor monitoring unit collects point cloud data output from the FMCW LiDAR sensor, analyzes changes before and after the execution of an attack, and determines whether a jamming attack has occurred based on whether a distance value is not detected or whether a distance value is returned to infinity. Claim 16 A method for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor, characterized in that, in the step of monitoring the signal output of the FMCW lidar sensor, the sensor monitoring unit analyzes the difference between the distance value detected by the FMCW lidar sensor and the actual distance value to determine whether a spoofing attack has occurred. Claim 17 A method for simulating an intentional attack for evaluating the performance of an FMCW LiDAR sensor, characterized in that, in the step of adjusting the alignment state and output characteristics of the attack light source, the processor adjusts the rotation angle of the attack light source through the rotation of a rotation stage of a light source fixing part to which the attack light source is fixed, thereby performing an attack on the FMCW LiDAR sensor at various angles. Claim 18 A method for simulating an intentional attack for evaluating the performance of an FMCW lidar sensor, characterized in that, in claim 11, after the step of monitoring the signal output of the FMCW lidar sensor, the processor generates a performance evaluation report of the FMCW lidar sensor by comparing data before and after the attack execution based on the analysis results of the sensor monitoring unit.

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