# US 11,310,269 B2 · Methods to detect spoofing attacks on automated driving systems

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- Number: US 11,310,269 B2
- Document ID: US11310269B2
- Status: Granted
- Kind: B2
- Application number: 16/653,711
- Filed: 2019-10-15
- Published: 2021-04-15
- Granted: 2022-04-19
- Earliest claimed: 2019-10-15
- Assignees: Baidu USA LLC
- Applicants: Baidu USA LLC
- Inventors: Xiaodong Liu; Ning Qu
- Web page: https://patentgrep.com/patent/US11310269B2

## CPC

- H04L 63/1483: {service impersonation, e.g. phishing, pharming or web spoofing (detection of rogue wireless access points H04W12/12)}
- B60W 50/0225: {Failure correction strategy}
- B60W 50/045: {Monitoring control system parameters}
- G01C 21/3415: {Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents}
- G06F 21/554: {involving event detection and direct action}
- G06V 20/58: Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
- H04L 63/1425: {Traffic logging, e.g. anomaly detection}
- H04L 63/1466: {Active attacks involving interception, injection, modification, spoofing of data unit addresses, e.g. hijacking, packet injection or TCP sequence number attacks}
- H04W 4/40: for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W 12/121: Wireless intrusion detection systems [WIDS]; Wireless intrusion prevention systems [WIPS]
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)
- B60W: CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S)
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72)

## Abstract

Systems and methods are disclosed for an ADV to leverage pre-defined static objects along a planned route of travel to detect and counter attacks that attempt to change the destination or the planned route. The ADV may detect updates to the static objects if the planned route is changed. Based on the updated static objects, the ADV determines if there is an abnormal re-routing of the planned route or if there is a new route due to a suspicious destination change. The ADV may also leverage the static objects to detect spoofing attacks against the sensor system. The ADV may evaluate if sensors of the sensor system are able to detect and identify the static objects to identify an impaired sensor. The ADV may perform cross-check on the ability of the sensors to detect and identify dynamic objects to gain confidence that the impaired sensor is due to spoofing attacks.

## Claims

### Claim 1

A computer-implemented method for detecting a spoofing attack against an autonomous driving vehicle (ADV), the method comprising:
determining a planned route from a starting location to a destination, the planned route to the destination being updatable as the ADV travels on the planned route;
obtaining a plurality of pre-defined static objects along the planned route from a map database, the plurality of pre-defined static objects being updatable when the planned route is updated;
detecting an update to the plurality of pre-defined static objects;
determining that a re-routing of the planned route is associated with the spoofing attack based on a frequency of past re-routings of the planned route, and a distance of the planned route in response to detecting the update to the plurality of pre-defined static objects;
determining a change to the destination by analyzing a new route traced by a plurality of updated pre-defined static objects;
confirming that a passenger in the ADV does not request the change to the destination to determine that the re-routinq is associated with the spoofinq attack;
confirming that there is the passenger in the ADV;
prompting the passenger in the ADV to request stopping the ADV; and
sending a report that the re-routing of the planned route is associated with the spoofing attack.

### Claim 2 (depends on 1)

The method of claim 1, further comprising : analyzing one or more of a traffic condition, a difference in distances between the abnormal re-routing and the planned route, a travel time of the planned route, or a difference in travel times between the abnormal re-routing and the planned route to determine that the re-routing of the planned route is associated with the spoofing attack.

### Claim 3 (depends on 1)

The method of claim 1, further comprising: verifying that an updated pre-defined static object is identified to confirm that the planned route is re-routed.

### Claim 4 (depends on 1)

The computer-implemented of claim 1, further comprising:
evaluating if each of a plurality of sensors of the ADV is able to identify one of the plurality of pre-defined static objects from the map when the ADV is at a location corresponding to a pre-defined static object;
evaluating if each of the plurality of sensors is able to identify a dynamic object along the planned route; and
identifying one or more impaired sensors based on evaluations of the one or more impaired sensors not being able to identify the pre-defined static object or the dynamic object; and
excluding the one or more impaired sensors from a perception function of the ADV.

### Claim 5 (depends on 1)

The computer-implemented method of claim 1, wherein the determining that the re-routing of the planned route is associated with the spoofing attack is based on a difference in the distance from a previous route.

### Claim 6 (depends on 1)

The computer-implemented method of claim 1, wherein the determining that the re-routing of the planned route is associated with the spoofing attack is based on a travel time of the new route.

### Claim 7 (depends on 1)

The computer-implemented method of claim 1, wherein the determining that the re-routing of the planned route is associated with the spoofing attack is based on a traffic condition.

### Claim 8

A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor, cause the processor to perform operations for detecting a spoofing attack against an autonomous driving vehicle (ADV), the operations comprising:
determining a planned route from a starting location to a destination, the planned route to the destination being updatable as the ADV travels on the planned route;
obtaining a plurality of pre-defined static objects along the planned route from a map database, the plurality of pre-defined static objects being updatable when the planned route is updated;
detecting an update to the plurality of pre-defined static objects;
determining that a re-routing of the planned route is associated with the spoofing attack based on a frequency of past re-routings of the planned route, and a distance of the planned route in response to detecting the update to the plurality of pre-defined static objects;
determining a change to the destination by analyzing a new route traced by a plurality of updated pre-defined static objects; and
confirming that a passenger in the ADV does not request the change to the destination to determine that the re-routing is associated with the spoofing attack;
confirming that there is the passenger in the ADV;
prompting the passenger in the ADV to request stopping the ADV; and
sending a report that the re-routing of the planned route is associated with the spoofing attack.

### Claim 9 (depends on 8)

The non-transitory machine-readable medium of claim 8, further comprising instructions, which when executed by the processor, cause the processor to perform operations comprising:
analyzing one or more of a traffic condition, a difference in distances between the abnormal re-routing and the planned route, a travel time of the planned route, or a difference in travel times between the abnormal re-routing and the planned route to determine that the re-routing of the planned route is associated with the spoofing attack.

### Claim 10 (depends on 8)

The non-transitory machine-readable medium of claim 8, further comprising instructions, which when executed by the processor, cause the processor to perform operations comprising :
verifying that an updated pre-defined static object is identified to confirm the planned route is re-routed.

### Claim 11 (depends on 8)

The non-transitory machine-readable medium of claim 8, further comprising instructions, which when executed by the processor, cause the processor to perform operations comprising:
evaluating if each of a plurality of sensors of the ADV is able to identify one of the plurality of pre-defined static objects from the map when the ADV is at a location corresponding to a pre-defined static object;
evaluating if each of the plurality of sensors is able to identify a dynamic object along the planned route; and
identifying one or more impaired sensors based on evaluations of the one or more impaired sensors not being able to identify the pre-defined static object or the dynamic object; and
excluding the one or more impaired sensors from a perception function of the ADV.

### Claim 12 (depends on 8)

The non-transitory machine-readable medium of claim 8, wherein the determining that the re-routing of the planned route is associated with the spoofing attack is based on a difference in the distance from a previous route.

### Claim 13 (depends on 8)

The non-transitory machine-readable medium of claim 8, wherein the determining that the re-routing of the planned route is associated with the spoofing attack is based on a difference in the distance from a previous route.

### Claim 14 (depends on 8)

The non-transitory machine-readable medium of claim 8, wherein the determining that the re-routing of the planned route is associated with the spoofing attack is based on a traffic condition.

### Claim 15

A system to detect a spoofing attack against an autonomous driving vehicle (ADV), comprising:
a memory; and
a processor coupled to the memory, wherein the processor is configured to: determine a planned route from a starting location to a destination, the planned route to the destination being updatable as the ADV travels on the planned route;
obtain a plurality of pre-defined static objects along the planned route from a map database, the plurality of pre-defined static objects being updatable when the planned route is updated;
detect an update to the plurality of pre-defined static objects;
determine that a re-routing of the planned route is associated with the spoofing attack based on a frequency of past re-routings of the planned route, and a distance of the planned route in response to detecting the update to the plurality of pre-defined static objects;
determine a change to the destination by analyzing a new route traced by a plurality of updated pre-defined static objects;
confirm that a passenger in the ADV does not request the change to the destination to determine that the re-routing is associated with the spoofing attack;
confirm that there is the passenger in the ADV;
prompt the passenger in the ADV to request stopping the ADV; and
send a report that the re-routing of the planned route is associated with the spoofing attack.

### Claim 16 (depends on 15)

The system of claim 15, wherein the processor is further configured to:
analyze one or more of a traffic condition, a difference in distances between the abnormal re-routing and the planned route, a travel time of the planned route, or a difference in travel times between the abnormal re-routing and the planned route to determine that the re-routing of the planned route is associated with the spoofing attack.

### Claim 17 (depends on 15)

The system of claim 15, wherein the processor is further configured to:
verify that an updated pre-defined static object is identified to confirm that the planned route is re-routed.

### Claim 18 (depends on 15)

The system of claim 15, wherein the processor is further configured to:
evaluate if each of a plurality of sensors of the ADV is able to identify one of the plurality of pre-defined static objects from the map when the ADV is at a location corresponding to a pre-defined static object;
evaluate if each of the plurality of sensors is able to identify a dynamic object along the planned route; and
identify one or more impaired sensors based on evaluations of the one or more impaired sensors not being able to identify the pre-defined static object or the dynamic object; and
exclude the one or more impaired sensors from a perception function of the ADV.

### Claim 19 (depends on 15)

The system of claim 15, wherein the processor is further configured to:
determine that the re-routing of the planned route is associated with the spoofing attack based on a difference in the distance from a previous route.

### Claim 20 (depends on 15)

The system of claim 15, wherein the processor is further configured to:
determine that the re-routing of the planned route is associated with the spoofing attack based on at least one of a difference in the distance from a previous route or a traffic condition.