KR20220071169A - Congestion attack detection system in autonomous cooperative driving environment using received signal strength measurement - Google Patents

Abstract

According to an embodiment of the present disclosure, disclosed is a method for detecting a congestion attack through a processor of a computing device in an autonomous cooperative driving environment. The method includes the steps of: receiving a wireless signal transmitted when an external device recognizes that a road is congested through a network unit; and determining wireless signal strength of the wireless signal, and determining whether a congestion attack exists based on the wireless signal strength.

Description

{CONGESTION ATTACK DETECTION SYSTEM IN AUTONOMOUS COOPERATIVE DRIVING ENVIRONMENT USING RECEIVED SIGNAL STRENGTH MEASUREMENT}

The present disclosure relates to a system and a computing device for detecting a congestion attack in an autonomous cooperative driving environment, and more particularly, to a method of determining whether currently received road information is incorrect information.

Although it is known that the sensor recognition range of autonomous vehicles is up to 200m, in the case of small facilities (such as rubber cones) installed in construction sites, sudden braking is unavoidable by recognizing them from about several tens of meters. Since the range is limited, smooth autonomous driving is difficult.

In order to compensate for these shortcomings of autonomous vehicles, autonomous cooperative driving technology provides connectivity based on V2X communication to vehicles that were driving in the existing stand-alone mode, thereby providing connectivity to surrounding cars, road infrastructure, pedestrians, and all elements of daily life. It is possible to provide safe driving, traffic congestion prevention, and various services through two-way communication with people. By giving the vehicle connectivity and enabling two-way communication, data can be exchanged with all elements around the vehicle in real time, thereby preventing traffic accidents and enhancing safety, as well as providing platooning and various services. .

However, in an autonomous cooperative driving environment, a congestion attack in which a malicious vehicle transmits malicious information that a specific road is congested may exist. Accordingly, there is a need for a system and method capable of responding to a congestion attack.

Republic of Korea Patent Registration No. 10-2064222

The present disclosure has been made in response to the above-described background technology, and is intended to provide a system and a computing device for detecting a congestion attack in an autonomous cooperative driving environment.

The technical problems of the present disclosure are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the following description.

According to an embodiment of the present disclosure for realizing the above-described problem, a method for detecting a congestion attack through a processor of a computing device in an autonomous cooperative driving environment is disclosed. The method includes: receiving a wireless signal transmitted through a network unit when an external device recognizes that the road is congested; and determining a radio signal strength of the radio signal, and determining whether a congestion attack exists based on the radio signal strength.

Alternatively, the autonomous cooperative driving environment includes one or more participating nodes, and the wireless signal recognizes that the road is congested by the external device based on a signal received from the one or more participating nodes by the external device In this case, it may be a signal generated and transmitted by the external device.

Alternatively, determining whether a congestion attack exists based on the wireless signal strength includes determining that the congestion attack exists when recognizing that the wireless signal strength falls within a low signal strength range can do.

Alternatively, the busy signal strength range is determined based on at least one first signal transmitted from the external device in the autonomous cooperative driving environment of the busy road, and the busy road is a predetermined congestion level determination criterion It may be a road that does not fall under

Alternatively, the limited signal strength range may be calculated using a first average value of the signal strengths of each of the at least one first signal.

Alternatively, the signal strength range may have a minimum value obtained by subtracting a preset value from the first average value, and a maximum value obtained by adding the preset value to the average value.

Alternatively, when it is determined that the congestion attack exists, the method may further include transmitting at least one of participating node information and road information related to the congestion attack to a server of an external organization.

Alternatively, determining whether a congestion attack exists based on the wireless signal strength may further include determining that the congestion attack does not exist when the wireless signal strength falls within a congestion signal strength range. can

Alternatively, the congested signal strength range is determined based on at least one second signal transmitted from the external device in the autonomous cooperative driving environment of the congested road, and the congested road includes a predetermined congestion level It may be a road corresponding to the decision criterion.

Alternatively, the congestion signal strength range may be calculated using a second average value of the signal strengths of each of the at least one second signal.

Alternatively, the congestion signal strength range may have a minimum value obtained by subtracting a preset value from the second average value, and may have a maximum value obtained by adding the preset value to the average value.

Alternatively, the computing device and the external device may be installed on both sides of the road.

A computing device for detecting a congestion attack in an autonomous cooperative driving environment is disclosed according to another embodiment of the present disclosure for realizing the above-described problem. The computing device may include: a network unit configured to receive a wireless signal transmitted from an external device through the network unit when the road is congested; and a processor for determining a radio signal strength of the radio signal, and determining whether a congestion attack exists based on the radio signal strength.

According to an embodiment of the present disclosure, it is possible to provide a system and a computing device for detecting a congestion attack in an autonomous cooperative driving environment.

Effects obtainable in the present disclosure are not limited to the above-mentioned effects, and other effects not mentioned will be clearly understood by those of ordinary skill in the art to which the present disclosure belongs from the description below. .

Various aspects are now described with reference to the drawings, wherein like reference numbers are used to refer to like elements throughout. In the following example, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more aspects. It will be evident, however, that such aspect(s) may be practiced without these specific details.
1 is an exemplary block diagram of a computing device for detecting a congestion attack in an autonomous cooperative driving environment according to an embodiment of the present disclosure.
2 is a flowchart exemplarily illustrating a method of detecting a congestion attack in an autonomous cooperative driving environment according to an embodiment of the present disclosure.
3 is an exemplary diagram schematically illustrating an example of implementing a method for detecting a congestion attack through a computing device in an autonomous cooperative driving environment according to an embodiment of the present disclosure.
FIG. 4 is a flowchart exemplarily illustrating a method for determining a signal strength range of a low peak according to an embodiment of the present disclosure.
5 is an exemplary diagram schematically illustrating an example of implementing a method for determining a signal strength range in busy conditions in an autonomous cooperative driving environment on a busy road according to an embodiment of the present disclosure.
6 is a flowchart exemplarily illustrating a method of determining a congestion signal strength range according to an embodiment of the present disclosure.
7 is an exemplary diagram schematically illustrating an example of implementing a method for determining a congestion signal strength range in an autonomous cooperative driving environment on a congested road according to an embodiment of the present disclosure.
8 depicts a simplified, general schematic diagram of an exemplary computing environment in which an embodiment of the present disclosure may be implemented;

Various embodiments and/or aspects are now disclosed with reference to the drawings. In the following description, for purposes of explanation, numerous specific details are set forth to provide a thorough understanding of one or more aspects. However, it will also be appreciated by one of ordinary skill in the art that such aspect(s) may be practiced without these specific details. The following description and accompanying drawings set forth in detail certain illustrative aspects of one or more aspects. These aspects are illustrative, however, and some of various methods may be employed in the principles of the various aspects, and the descriptions set forth are intended to include all such aspects and their equivalents. Specifically, as used herein, “embodiment”, “example”, “aspect”, “exemplary”, etc. are not to be construed as advantageous or advantageous over any aspect or design described herein. It may not be.

Hereinafter, the same or similar components are assigned the same reference numerals regardless of reference numerals, and overlapping descriptions thereof will be omitted. In addition, in describing the embodiments disclosed in the present specification, if it is determined that detailed descriptions of related known technologies may obscure the gist of the embodiments disclosed in the present specification, the detailed description thereof will be omitted. In addition, the accompanying drawings are only for easy understanding of the embodiments disclosed in the present specification, and the technical ideas disclosed in the present specification are not limited by the accompanying drawings.

Although the first, second, etc. are used to describe various elements or elements, these elements or elements are not limited by these terms, of course. These terms are only used to distinguish one element or component from another. Accordingly, it goes without saying that the first element or component mentioned below may be the second element or component within the spirit of the present invention.

Unless otherwise defined, all terms (including technical and scientific terms) used herein may be used with the meaning commonly understood by those of ordinary skill in the art to which the present invention belongs. In addition, terms defined in a commonly used dictionary are not to be interpreted ideally or excessively unless clearly defined in particular.

In addition, the term “or” is intended to mean an inclusive “or” rather than an exclusive “or.” That is, unless otherwise specified or clear from context, "X employs A or B" is intended to mean one of the natural implicit substitutions. That is, X employs A; X employs B; or when X employs both A and B, "X employs A or B" may apply to either of these cases. It should also be understood that the term “and/or” as used herein refers to and includes all possible combinations of one or more of the listed related items.

Also, the terms "comprises" and/or "comprising" mean that the feature and/or element is present, but excludes the presence or addition of one or more other features, elements, and/or groups thereof. should be understood as not Also, unless otherwise specified or unless it is clear from context to refer to a singular form, the singular in the specification and claims should generally be construed to mean “one or more”.

When a component is referred to as being “connected” or “connected” to another component, it is understood that it may be directly connected or connected to the other component, but other components may exist in between. it should be On the other hand, when it is said that a certain element is "directly connected" or "directly connected" to another element, it should be understood that there is no other element present in the middle.

The suffixes “module” and “part” for components used in the following description are given or mixed in consideration of only the ease of writing the specification, and do not have distinct meanings or roles by themselves.

Objects and effects of the present disclosure, and technical configurations for achieving them will become clear with reference to the embodiments described below in detail in conjunction with the accompanying drawings. In describing the present disclosure, if it is determined that a detailed description of a well-known function or configuration may unnecessarily obscure the subject matter of the present disclosure, the detailed description thereof will be omitted. In addition, the terms described below are terms defined in consideration of functions in the present disclosure, which may vary according to intentions or customs of users and operators.

However, the present disclosure is not limited to the embodiments disclosed below and may be implemented in various different forms. Only the present embodiments are provided so that the present disclosure is complete, and to fully inform those of ordinary skill in the art to which the present disclosure belongs, the scope of the disclosure, and the present disclosure is only defined by the scope of the claims . Therefore, the definition should be made based on the content throughout this specification.

The autonomous cooperative driving environment 1000 of the present disclosure may refer to a network environment for one or more vehicles 300 traveling on a predetermined road. Specifically, the predetermined road may be a road of a predetermined length or size. For example, the predetermined road may be a partial area of a 10 km-long highway, and accordingly, the autonomous cooperative driving environment 1000 provides a network environment for one or more vehicles 300 passing through a partial area of a 10 km-long highway. can mean

The above-described predetermined road is merely an example and should not be interpreted as being limited to the autonomous cooperative driving environment 1000 or the predetermined road of the present disclosure due to the above-described example.

A road of the present disclosure may mean a region through which one or more vehicles 300 may pass. For the road of the present disclosure, for example, it may be a five-lane one-way road, a three-lane road, a signal intersection, a dirt road, a highway, etc., but the road of the present disclosure is not limited to the above-described examples.

The vehicle 300 of the present disclosure may be various types of transportation means, and more specifically, may refer to an autonomous vehicle, a self-driving car, and the like. The vehicles 300 in the autonomous cooperative driving environment 1000 of the present disclosure receive at least one of external signals or information through at least one of wired and wireless communication, or signals generated by the vehicles 300 themselves. Alternatively, at least one of the information may be transmitted to the outside. Specifically, the vehicles 300 may transmit/receive at least one of signals or information to and from the external device 200 through Vehicle-to-Everything (V2X) communication.

V2X communication of the present disclosure includes communication between vehicles (V2V), communication between vehicles and infrastructure (V2I, Vehicle-to-Infrastructure), communication between vehicles and pedestrians (V2P, Vehicle-to-Pedestrian), and communication between vehicles and cloud networks It means communication including (V2N, Vehicle-to-Network) and the like. Here, infrastructure means infrastructure and infrastructure, and V2I means communication between infrastructure-related things and vehicles. For example, it may be a communication between a vehicle and a traffic light.

The autonomous cooperative driving environment 1000 of the present disclosure includes at least one of the external device 200 , the computing device 100 , and one or more participating nodes, and the participating node of the present disclosure is the V2X of the autonomous cooperative driving environment 1000 . It may mean a node participating in communication. Also, at least one vehicle 300 of the autonomous cooperative driving environment 1000 of the present disclosure may be included in the autonomous cooperative driving environment 1000 as a participating node. That is, each of the vehicles 300 of the autonomous cooperative driving environment 1000 of the present disclosure may be a participating node of the present disclosure.

The external device 200 of the present disclosure may be another external computing device including the network unit 110 , the memory 130 , and the processor 120 , and among the signals or information of the autonomous cooperative driving environment 1000 . It may be a second computing device capable of receiving at least one. Specifically, the external device 200 of the present disclosure may receive the road information 10 from at least one of the vehicles 300 that are participating nodes of the autonomous cooperative driving environment 1000 . Also, the external device 200 of the present disclosure may analyze the received road information 10 to determine a predetermined road condition. The description of the external device 200 of the present disclosure will be described in detail later with reference to the drawings.

The road information 10 of the present disclosure may be information on a predetermined road related to the autonomous cooperative driving environment 1000 . Specifically, the road information 10 of the present disclosure may include situation information and detailed information. The situation information may be information on the road condition at the time when the road information 10 is generated, and the detailed information may be detailed information on a predetermined road condition related to the autonomous cooperative driving environment 1000 .

For the situation information of the present disclosure, for example, it may be one of congestion situation information indicating a condition of a congested road or busy situation information indicating a situation of a quiet road. not limited to one of

For detailed information of the present disclosure, for example, it may be information about the average speed of vehicles 300 traveling on a predetermined road or the number of vehicles 300 . The detailed information described above is merely an example, and detailed information that may be included in the road information 10 of the present disclosure is not limited to information on the speed or number of vehicles 300 .

The quiet road of the present disclosure means a road in a quiet situation because there are not many vehicles 300 on the predetermined road of the autonomous cooperative driving environment 1000 . In addition, the congested road of the present disclosure means a road in a congested situation because there are many vehicles 300 on a predetermined road. Specifically, the empty road and the congested road may be determined based on the congestion level determination criterion of the present disclosure. Accordingly, the busy road of the present disclosure may be a road that does not correspond to a predetermined congestion level determination criterion. Also, the congested road of the present disclosure may be a road corresponding to a predetermined congestion level determination criterion.

The congestion level determination criterion of the present disclosure may be a criterion based on the average speed of the vehicles 300 . Accordingly, the congestion level determination criterion of the present disclosure may include different criteria according to the type of road.

For example, when the road is a highway, the congestion level determination criterion may be less than the average speed of 40 km/h of the vehicles 300 , and when the road is an arterial road, the congestion level determination criterion is the average speed of the vehicles 300 less than 15 km/h can That is, the congestion level determination criterion for determining whether the highway is a congested road may be that the average speed of the vehicles 300 is less than 30 km/h, and when the average speed of the vehicles 300 on the highway is 30 km/h, the highway is It does not meet the criteria for determining the congestion level and may be a quiet road. In addition, when the average speed of the vehicles 300 on the highway is 29 km/h, the corresponding highway corresponds to the congestion level determination criterion and may be a congested road. The above-described average speed of the vehicles 300 is only an example, and the average speed of the vehicles 300 based on the congestion level determination criterion is limited and should not be interpreted due to the above-described examples.

In addition, the congestion level determination criterion of the present disclosure may be the congestion level determination criterion disclosed in Attached Table 2 of the Enforcement Decree of the Urban Traffic Improvement Promotion Act.

The congestion attack of the present disclosure may mean that incorrect road information is received by the external device 200 of the present disclosure. Here, the incorrect road information may mean the road information 10 including situation information that does not correspond to the predetermined actual situation of the road. Specifically, when the situation information included in the road information 10 of the vehicle 300 is information indicating a road in a situation different from the actual road situation, the road information 10 may be incorrect road information.

That is, the external device 200 of the present disclosure receives the road information 10 generated by an arbitrary vehicle 300 traveling on a predetermined road in a quiet situation, and the external device includes the road information 10 included in the road information 10 . When it is determined that the predetermined road situation is congested based on the situation information, the road information 10 is incorrect road information 10, and it can be seen that a congestion attack exists.

The presence or absence of a congestion attack of the present disclosure may be determined in the computing device 100 of the present disclosure that is distinguished from the external device 200, and operations of the computing device 100 implementing a method of determining whether a congestion attack exists will be described in detail with reference to the following drawings.

The signal strength of the present disclosure is the strength of a radio/RF reception signal including noise, and may be the strength of a received radio signal or a received signal strength indicator (RSSI). RSSI is generally used to estimate the distance between devices, and as RSSI passes through an obstacle, the attenuation occurs. Accordingly, the present disclosure determines whether the actual road is congested due to the vehicles 300 according to the RSSI that decreases due to the vehicles 300 on the road, and determines whether a congestion attack exists in the autonomous cooperative driving environment 1000 . The method for determining is described as follows.

The server of an external institution of the present disclosure may mean a server of a public institution related to traffic safety or traffic law or a server of a research institution. For example, the external institution may be a server of a higher level institution of the road transportation system or a server of a public institution related to cybercrime, but the external institution server of the present disclosure is not limited thereto.

Hereinafter, the computing device 100 for detecting a congestion attack in the autonomous cooperative driving environment 1000 will be described.

1 is an exemplary block diagram of a computing device for detecting a congestion attack in an autonomous cooperative driving environment according to an embodiment of the present disclosure.

According to an embodiment of the present disclosure, the computing device 100 may be a device for detecting a congestion attack in the autonomous cooperative driving environment 1000 . Here, detecting a congestion attack may be determining whether a congestion attack exists.

According to an embodiment of the present disclosure, the computing device 100 may include a network unit 110 , a memory 130 , and a processor 120 . However, the present invention is not limited thereto, and the computing device 100 may include more or fewer components than the above-described components.

The processor 120 may include one or more cores, and a central processing unit (CPU), a general purpose graphics processing unit (GPGPU), and a tensor processing unit (TPU) of the computing device 100 . : tensor processing unit) may include any type of processor 120 for detecting a congestion attack in the autonomous cooperative driving environment 1000 by executing instructions stored in the memory 130 .

The processor 120 may read a computer program stored in the memory 130 to detect a congestion attack in the autonomous cooperative driving environment 1000 according to some embodiments of the present disclosure.

The processor 120 may control overall operations of components of the computing device 100 to detect a congestion attack in the autonomous cooperative driving environment 1000 .

The computing device 100 of the present disclosure may further include a memory 130 . The memory 130 may store a program for the operation of the processor 120 , and may temporarily or permanently store input/output data. The memory 130 may include a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (eg, SD or XD memory, etc.), RAM (Random Access Memory, RAM), SRAM (Static Random Access Memory), ROM (Read-Only Memory, ROM), EEPROM (Electrically Erasable Programmable Read-Only Memory), PROM (Programmable Read-Only Memory), magnetic memory, magnetic It may include at least one type of storage medium among disks and optical disks.

The memory may be operated under the control of the processor 120 . Also, in the present disclosure, a memory and a storage unit may be used interchangeably with each other.

The network unit 110 included in the computing device 100 of the present disclosure may include a wired/wireless Internet module for network connection. The network unit 110 may communicate with the external device 200 or the vehicles 300 which are nodes participating in the autonomous driving environment.

Also, although not shown in FIG. 1 , the external device 200 according to an embodiment of the present disclosure may include a memory 130 , a network unit 110 , and a processor 120 . The computing device 100 and the external device 200 of the present disclosure may be different individual devices, and may be able to communicate through each network unit 110 .

Also, according to an embodiment of the present disclosure, the computing device 100 and the external device 200 may be installed on both sides of a road. Specifically, the computing device 100 and the external device 200 may be configured as a Road Side Unit (RSU), and are determined in advance in the autonomous cooperative driving environment 1000 between the computing device 100 and the external device 200 . It may be installed so that a road is located. For example, as shown in each of FIGS. 3, 5, and 7 , the external device 200 and the computing device 100 may be installed on both sides of a predetermined road related to the autonomous cooperative driving environment 1000 . .

The above-described components are exemplary, and the scope of the present disclosure is not limited to the above-described components. That is, additional components may be included or some of the above-described components may be omitted depending on implementation aspects for the embodiments of the present disclosure.

Hereinafter, a method for detecting a congestion attack through the processor 120 of the computing device 100 in the autonomous cooperative driving environment 1000 will be described with reference to FIGS. 2 to 3 according to an embodiment of the present disclosure.

2 is a flowchart exemplarily illustrating a method for detecting a congestion attack in an autonomous cooperative driving environment according to an embodiment of the present disclosure.

3 is an exemplary diagram schematically illustrating an example of implementing a method for detecting a congestion attack through a computing device in an autonomous cooperative driving environment according to an embodiment of the present disclosure.

Referring to FIG. 2 , according to an embodiment of the present disclosure, the processor 120 receives ( 2100 ) the wireless signal 23 transmitted when the external device 200 recognizes that the road is congested through the network unit 110 . )can do.

Specifically, the autonomous cooperative driving environment 1000 may include one or more participating nodes. In addition, the wireless signal 23 is a wireless signal generated and transmitted by the external device 200 when the external device 200 recognizes that the road is congested based on a signal received from one or more participating nodes. It could be a signal.

Referring to FIG. 3 , road information 10 may be transmitted from one of the vehicles 300 that are participating nodes of the autonomous cooperative driving environment 1000 to the external device 200 . The external device 200 of the present disclosure may determine whether the situation information is congestion information on a congested road based on the situation information included in the received road information 10 . When the external device 200 of the present disclosure determines that the situation information of the road information 10 is the congestion situation information, the external device 200 may generate the wireless signal 23 . Also, the external device 200 may transmit the wireless signal 23 to the computing device 100 .

Referring to FIG. 2 , the processor 120 may determine ( 2200 ) whether a congestion attack exists based on the signal strength of the wireless signal 23 .

Referring to FIG. 3 , the processor 120 of the computing device 100 may receive a wireless signal 23 from the external device 200 . The processor 120 may determine a wireless signal strength based on the wireless signal 23 , and the wireless signal strength may be a signal strength of the wireless signal 23 .

The processor 120 of the present disclosure may determine whether the wireless signal strength is included in the limited signal strength range. When recognizing that the wireless signal strength is included in the low signal strength range, the processor 120 may determine that a congestion attack exists. That is, when the wireless signal strength related to the congested road condition is included in the low signal strength range related to the busy road condition, the processor indicates that the wireless signal 23 is a signal generated based on incorrect road information, and a congestion attack exists can decide to

In addition, when it is determined that a congestion attack exists, the processor 120 of the present disclosure transmits at least one of participating node information or road information 10 related to the congestion attack to the server 400 of an external organization as shown in FIG. 3 . can be transmitted Specifically, when it is determined that a congestion attack exists, the processor 120 may transmit situation information and detailed information included in incorrect road information of a related wireless signal to the server 400 of an external organization. In addition, the processor 120 may generate participation node information related to incorrect road information and transmit it to a server of an external organization. The participating node information may be detailed information about the vehicle 300 that has transmitted incorrect road information to the external device 200 . For example, the participating node information may include identification information of the vehicle 300 and a time at which the vehicle 300 generates road information.

The busy signal strength range of the present disclosure may be determined by the processor 120 based on the at least one first signal 21 transmitted from the external device 200 in the autonomous cooperative driving environment 1000 on a busy road. Specifically, the signal strength range is the range of the first signals 21 that are wireless signals transmitted from the external device 200 to the network unit 110 of the computing device 100 in the autonomous cooperative driving environment 1000 on a busy road. can be The narrow signal strength range of the present disclosure may be calculated using a first average value of the signal strengths of each of the at least one first signal 21 .

Hereinafter, a method of determining a low signal strength range according to an embodiment of the present disclosure will be described with reference to FIGS. 4 to 5 .

FIG. 4 is a flowchart exemplarily illustrating a method for determining a signal strength range of a low peak according to an embodiment of the present disclosure.

FIG. 5 is an exemplary diagram schematically illustrating an example of implementing a method for determining a signal strength range in a busy environment in an autonomous cooperative driving environment on a busy road according to an embodiment of the present disclosure.

As shown in FIG. 4 , the processor 120 of the present disclosure transmits at least one first signal 21 transmitted from the external device 200 in the autonomous cooperative driving environment 1000 on a quiet road to the network unit 110 . It can be received (3100) through.

Referring to FIG. 5 , in the autonomous cooperative driving environment 1000 on a quiet road, the external device 200 generates one or more first signals 21 , and transmits the generated first signals 21 to the computing device 100 . ) can be transmitted.

According to some embodiments of the present disclosure, the external device 200 may generate the first signal 21 when receiving the first signal generation command from the external terminal. For example, the user may transmit the first signal generation command to the external device 200 through an external terminal such as a personal computer to intentionally set a busy signal strength range for a busy road. The external terminal of the present disclosure is not limited to the personal computer described in the above-described example.

Referring back to FIG. 4 , the processor 120 of the present disclosure may determine the signal strength of each of the at least one first signal 21 and calculate a first average value ( 3200 ).

Specifically, referring to FIG. 5 , the processor 120 of the computing device 100 may receive one or more first signals 21 from the external device 200 . The processor 120 may determine a first signal strength of each of the received first signals 21 . The first signal strength may be the signal strength of the first signal 21 . Also, the processor 120 may determine the first average value by calculating an average value of the determined first signal strengths. That is, the first average value may be an average of signal strengths of the first signals 21 .

As shown in FIG. 4 , the processor 120 of the present disclosure may determine ( 3300 ) a narrow signal strength range based on the first average value. Specifically, the processor 120 may determine a signal intensity range having a minimum value obtained by subtracting a preset value from the first average value and a maximum value obtained by adding a preset value to the average value as a maximum value.

For example, the Hansan signal intensity range may be expressed as follows.

는 제 1 평균값이고,

는 혼잡 공격 탐지에 사용되는 무선 신호의 무선 신호 강도이고, 그리고

는 기 설정된 값이다. in the above expression

is the first average value,

is the radio signal strength of the radio signal used for congestion attack detection, and

is a preset value.

Meanwhile, the above-mentioned low signal strength range may be determined in advance before detecting a congestion attack. However, the present invention is not limited thereto.

Hereinafter, a method of determining a congestion signal strength range according to an embodiment of the present disclosure will be described with reference to FIGS. 6 to 7 .

6 is a flowchart exemplarily illustrating a method for determining a congestion signal strength range according to an embodiment of the present disclosure.

7 is an exemplary diagram schematically illustrating an example of implementing a method of determining a congestion signal strength range in an autonomous cooperative driving environment on a congested road according to an embodiment of the present disclosure.

Referring to FIG. 6 , the processor 120 of the present disclosure transmits at least one second signal 22 transmitted from the external device 200 to the network unit 110 in the autonomous cooperative driving environment 1000 on a congested road. It can be received (4100) through.

Referring to FIG. 7 , in the autonomous cooperative driving environment 1000 on a congested road, the external device 200 may generate the second signal 22 and transmit it to the computing device 100 .

According to some embodiments of the present disclosure, the external device 200 may generate the second signal 22 when receiving a second signal generation command from the external terminal. For example, the user may transmit a second signal generation command to the external device 200 through an external terminal such as a personal computer to intentionally set a complex signal strength range for a complicated road. The external terminal of the present disclosure is not limited to the personal computer described in the above-described example.

Referring to FIG. 6 , the processor 120 of the present disclosure may determine the second signal strength of each of the at least one second signal 22 and calculate a second average value ( 4200 ).

Referring to FIG. 7 , the processor 120 of the computing device 100 may determine the second signal strength of each of the at least one second signal 22 . The second signal strength may be the signal strength of the second signal 22 . Also, the processor 120 may calculate an average of the determined second signal strengths to determine the second average value.

Referring to FIG. 6 , the processor 120 of the present disclosure may determine a congestion signal strength range based on the second average value ( 4300 ).

Specifically, the processor 120 may determine a congestion signal intensity range having a minimum value obtained by subtracting a preset value from the second average value and a maximum value obtained by adding a preset value to an average value.

For example, the congestion signal strength range may be expressed as follows.

는 제 2 평균값이고,

는 혼잡 공격 탐지에 사용되는 무선 신호의 무선 신호 강도이고, 그리고

는 기 설정된 값이다. in the above expression

is the second average value,

is the radio signal strength of the radio signal used for congestion attack detection, and

is a preset value.

The preset value for the above-described limited signal strength range and the preset value for the congestion signal strength range may be different from each other.

Meanwhile, the aforementioned congestion signal strength range may be determined in advance before detecting a congestion attack. However, the present invention is not limited thereto.

According to an embodiment of the present disclosure, the processor 120 may determine that a congestion attack does not exist when the wireless signal strength is included in the congestion signal strength range.

Specifically, as described above with reference to FIGS. 6 to 7 , the congested signal strength range is at least one second signal 22 transmitted from the external device 200 in the autonomous cooperative driving environment 1000 on a congested road. It may be determined by the processor 120 based on The congestion signal strength range of the present disclosure may be calculated by the processor 120 using a second average value of the signal strengths of each of the at least one second signal 22 .

When the wireless signal strength for a congested road condition is included in the congestion signal strength range, the processor 120 of the present disclosure may determine that road information related to the wireless signal is correct information and that a congestion attack does not exist.

As described above, according to an embodiment of the present disclosure, there is an advantage that it is possible to simply check a congestion attack of road information using the received signal strength. In addition, the external device 200 and the computing device 100 of the present disclosure may be configured to be included in various installations such as street lights, bollards, or traffic lights installed next to the road, so there is no need to configure a separate server or equipment. That is, at least one of the external device 200 or the computing device 100 of the present disclosure can be installed in a roadside installation or equipment without separately configuring separate equipment for the external device 200 and the computing device 100 of the present disclosure. It can be configured by including one.

8 depicts a simplified, general schematic diagram of an exemplary computing environment in which an embodiment of the present disclosure may be implemented.

The computer 1102 illustrated in FIG. 8 may correspond to at least one of the computing device 100 and the external device 200 .

Although the present disclosure has been described above generally in the context of computer-executable instructions that may be executed on one or more computers, those skilled in the art will appreciate that the present disclosure may be implemented as a combination of hardware and software and/or in combination with other program modules. you will know

Generally, modules herein include routines, procedures, programs, components, data structures, etc. that perform particular tasks or implement particular abstract data types. In addition, those skilled in the art will appreciate that the methods of the present disclosure can be applied to single-processor or multiprocessor computer systems, minicomputers, mainframe computers as well as personal computers, handheld computing devices, microprocessor-based or programmable consumer electronics, etc. (each of which is It will be appreciated that other computer system configurations may be implemented, including those that may operate in connection with one or more associated devices.

The described embodiments of the present disclosure may also be practiced in distributed computing environments where certain tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

Computers typically include a variety of computer-readable media. Media accessible by a computer includes volatile and nonvolatile media, transitory and non-transitory media, removable and non-removable media. By way of example, and not limitation, computer-readable media may include computer-readable storage media and computer-readable transmission media.

Computer readable storage media includes volatile and nonvolatile media, temporary and non-transitory media, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. includes media. A computer-readable storage medium may be RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital video disk (DVD) or other optical disk storage device, magnetic cassette, magnetic tape, magnetic disk storage device, or other magnetic storage device. device, or any other medium that can be accessed by a computer and used to store the desired information.

A computer readable transmission medium typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and the like. Includes all information delivery media. The term modulated data signal means a signal in which one or more of the characteristics of the signal is set or changed so as to encode information in the signal. By way of example, and not limitation, computer-readable transmission media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared, and other wireless media. Combinations of any of the above are also intended to be included within the scope of computer-readable transmission media.

An example environment 1100 implementing various aspects of the disclosure is shown including a computer 1102 , the computer 1102 including a processing unit 1104 , a system memory 1106 , and a system bus 1108 . do. A system bus 1108 couples system components, including but not limited to system memory 1106 , to the processing device 1104 . The processing device 1104 may be any of a variety of commercially available processors. Dual processor and other multiprocessor architectures may also be used as processing unit 1104 .

The system bus 1108 may be any of several types of bus structures that may further interconnect a memory bus, a peripheral bus, and a local bus using any of a variety of commercial bus architectures. System memory 1106 includes read only memory (ROM) 1110 and random access memory (RAM) 1112 . A basic input/output system (BIOS) is stored in non-volatile memory 1110, such as ROM, EPROM, EEPROM, etc., the BIOS is the basic input/output system (BIOS) that helps transfer information between components within computer 1102, such as during startup. contains routines. RAM 1112 may also include high-speed RAM, such as static RAM, for caching data.

The computer 1102 may also include an internal hard disk drive (HDD) 1114 (eg, EIDE, SATA) - this internal hard disk drive 1114 may also be configured for external use within a suitable chassis (not shown). Yes—a magnetic floppy disk drive (FDD) 1116 (eg, for reading from or writing to removable diskette 1118), and an optical disk drive 1120 (eg, a CD-ROM) for reading from, or writing to, disk 1122, or other high capacity optical media, such as DVD. The hard disk drive 1114 , the magnetic disk drive 1116 , and the optical disk drive 1120 are connected to the system bus 1108 by the hard disk drive interface 1124 , the magnetic disk drive interface 1126 , and the optical drive interface 1128 , respectively. ) can be connected to Interface 1124 for external drive implementation includes, for example, at least one or both of Universal Serial Bus (USB) and IEEE 1394 interface technologies.

These drives and their associated computer-readable media provide non-volatile storage of data, data structures, computer-executable instructions, and the like. In the case of computer 1102, drives and media correspond to storing any data in a suitable digital format. Although the description of computer-readable storage media above refers to HDDs, removable magnetic disks, and removable optical media such as CDs or DVDs, those skilled in the art will use zip drives, magnetic cassettes, flash memory cards, cartridges, It will be appreciated that other tangible computer-readable storage media and the like may also be used in the exemplary operating environment and any such media may include computer-executable instructions for performing the methods of the present disclosure. .

A number of program modules may be stored in the drive and RAM 1112 , including an operating system 1130 , one or more application programs 1132 , other program modules 1134 , and program data 1136 . All or portions of the operating system, applications, modules, and/or data may also be cached in RAM 1112 . It will be appreciated that the present disclosure may be implemented in various commercially available operating systems or combinations of operating systems.

A user may enter commands and information into the computer 1102 via one or more wired/wireless input devices, for example, a pointing device such as a keyboard 1138 and a mouse 1140 . Other input devices (not shown) may include a microphone, IR remote control, joystick, game pad, stylus pen, touch screen, and the like. Although these and other input devices are connected to the processing unit 1104 through an input device interface 1142 that is often connected to the system bus 1108, parallel ports, IEEE 1394 serial ports, game ports, USB ports, IR interfaces, It may be connected by other interfaces, etc.

A monitor 1144 or other type of display device is also coupled to the system bus 1108 via an interface, such as a video adapter 1146 . In addition to the monitor 1144, the computer typically includes other peripheral output devices (not shown), such as speakers, printers, and the like.

Computer 1102 may operate in a networked environment using logical connections to one or more remote computers, such as remote computer(s) 1148 via wired and/or wireless communications. Remote computer(s) 1148 may be workstations, server computers, routers, personal computers, portable computers, microprocessor-based entertainment devices, peer devices, or other common network nodes, and are generally Although including many or all of the components described, only memory storage device 1150 is shown for simplicity. The logical connections shown include wired/wireless connections to a local area network (LAN) 1152 and/or a larger network, eg, a wide area network (WAN) 1154 . Such LAN and WAN networking environments are common in offices and companies, and facilitate enterprise-wide computer networks, such as intranets, all of which can be connected to a worldwide computer network, for example, the Internet.

When used in a LAN networking environment, the computer 1102 is coupled to the local network 1152 through a wired and/or wireless communication network interface or adapter 1156 . Adapter 1156 may facilitate wired or wireless communication to LAN 1152 , which LAN 1152 also includes a wireless access point installed therein for communicating with wireless adapter 1156 . When used in a WAN networking environment, the computer 1102 may include a modem 1158 , connected to a communication server on the WAN 1154 , or otherwise establishing communications over the WAN 1154 , such as over the Internet. is having the means. A modem 1158 , which may be internal or external and a wired or wireless device, is coupled to the system bus 1108 via a serial port interface 1142 . In a networked environment, program modules described for computer 1102 , or portions thereof, may be stored in remote memory/storage device 1150 . It will be appreciated that the network connections shown are exemplary and other means of establishing a communication link between the computers may be used.

The computer 1102 may be associated with any wireless device or object that is deployed and operates in wireless communication, for example, a printer, scanner, desktop and/or portable computer, portable data assistant (PDA), communication satellite, wireless detectable tag. It operates to communicate with any device or place, and phone. This includes at least Wi-Fi and Bluetooth wireless technologies. Accordingly, the communication may be a predefined structure as in a conventional network or may simply be an ad hoc communication between at least two devices.

Wi-Fi (Wireless Fidelity) makes it possible to connect to the Internet, etc. without a wired connection. Wi-Fi is a wireless technology such as cell phones that allows these devices, eg, computers, to transmit and receive data indoors and outdoors, ie anywhere within range of a base station. Wi-Fi networks use a radio technology called IEEE 802.11 (a, b, g, etc) to provide secure, reliable, and high-speed wireless connections. Wi-Fi can be used to connect computers to each other, to the Internet, and to wired networks (using IEEE 802.3 or Ethernet). Wi-Fi networks may operate in unlicensed 2.4 and 5 GHz radio bands, for example, at 11 Mbps (802.11a) or 54 Mbps (802.11b) data rates, or in products that include both bands (dual band). have.

The description of the presented embodiments is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the scope of the present disclosure. Thus, the present disclosure is not intended to be limited to the embodiments presented herein, but is to be construed in the widest scope consistent with the principles and novel features presented herein.

The scope of the rights to the method in the claims of the present disclosure is generated by the functions and features described in each step, and unless the precedence of the order is specified in each step constituting the method, the claims It is not affected by the order of description of each step in For example, in a claim described as a method comprising steps A and B, even if step A is stated before step B, the scope of the rights is not limited that step A must precede step B.

The description of the presented embodiments is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the scope of the present disclosure. Thus, the present disclosure is not intended to be limited to the embodiments presented herein, but is to be construed in the widest scope consistent with the principles and novel features presented herein.

Claims (7)

A method for detecting a congestion attack through a processor of a computing device in an autonomous cooperative driving environment, the method comprising:
receiving, through a network unit, a wireless signal transmitted when an external device recognizes that the road is congested; and
determining a wireless signal strength of the wireless signal, and determining that the congestion attack does not exist when the wireless signal strength is included in a congestion signal strength range based on the wireless signal strength;
containing,
A method for detecting congestion attacks in an autonomous cooperative driving environment.
The method of claim 1,
The autonomous cooperative driving environment is
one or more participating nodes, and
The radio signal is
When the external device recognizes that the road is congested based on the signal received from the one or more participating nodes, the external device is a wireless signal generated and transmitted by the external device,
A method for detecting congestion attacks in an autonomous cooperative driving environment.
The method of claim 1,
The congestion signal strength range is
is determined based on the at least one second signal transmitted from the external device in the autonomous cooperative driving environment of a congested road, and
The congested road
A road that meets a predetermined congestion level determination criterion;
A method for detecting congestion attacks in an autonomous cooperative driving environment.
4. The method of claim 3,
The congestion signal strength range is
calculated using a second average value of the signal strength of each of the at least one second signal;
A method for detecting congestion attacks in an autonomous cooperative driving environment.
5. The method of claim 4,
The congestion signal strength range is
Having a value obtained by subtracting a preset value from the second average value as a minimum value, and having a value obtained by adding the preset value to the average value as a maximum value,
A method for detecting congestion attacks in an autonomous cooperative driving environment.
The method of claim 1,
The computing device and the external device,
installed on both sides of the road,
A method for detecting congestion attacks in an autonomous cooperative driving environment.
A computing device for detecting a congestion attack in an autonomous cooperative driving environment, the computing device comprising:
a network unit for receiving a wireless signal transmitted from an external device through the network unit when the road is congested; and
a processor for determining a wireless signal strength of the wireless signal, and determining that the congestion attack does not exist when the wireless signal strength is included in a congestion signal strength range based on the wireless signal strength;
containing,
computing device.

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