Communication of navigation data spoofing between unmanned vehicles

• US 9,847,033 B1
• Filed: 09/25/2015
• Issued: 12/19/2017
• Est. Priority Date: 09/25/2015
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Carmack, Scott Gerard, Lakkakula, Narasimha Rao, Sharifi Mehr, Nima
• Primary Examiner(s): Edwards, Jerrah
• Assistant Examiner(s): Williams, Kelly D
• Application Number:
  US14/866,745
• Time in Patent Office: 816 Days
• CPC Class Codes: G01S 19/03 Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers
• CPC Class Codes: G01S 19/215 issues related to spoofing
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G05D 1/104 involving a plurality of aircrafts, e.g. formation flying traffic control systems for aircraft G08G5/00
• CPC Class Codes: G06Q 10/083 Shipping
• CPC Class Codes: G06Q 10/08355 Routing methods
• CPC Class Codes: G08G 5/0008 with other aircraft
• CPC Class Codes: G08G 5/0013 with a ground station
• CPC Class Codes: G08G 5/0021 located in the aircraft
• CPC Class Codes: G08G 5/0026 located on the ground
• CPC Class Codes: G08G 5/0039 Modification of a flight plan
• CPC Class Codes: G08G 5/0052 for cruising combined instruments indicating more than one navigational value G01C23/00
• CPC Class Codes: G08G 5/0056 in an emergency situation, e.g. hijacking
• CPC Class Codes: G08G 5/0069 specially adapted for an unmanned aircraft
• CPC Class Codes: H04K 2203/22 for communication related to vehicles
• CPC Class Codes: H04K 2203/36 including means for exchanging jamming data between transmitter and receiver, e.g. in forward or backward direction
• CPC Class Codes: H04K 3/22 including jamming detection and monitoring
• CPC Class Codes: H04K 3/65 using deceptive jamming or spoofing, e.g. transmission of false signals for premature triggering of RCIED, for forced connection or disconnection to/from a network or for generation of dummy target signal
• CPC Class Codes: H04K 3/90 related to allowing or preventing navigation or positioning, e.g. GPS
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04W 4/00 : Services specially adapted for wireless communication networks; Facilities therefor
• CPC Class Codes: H04W 4/02 : Services making use of location information
• CPC Class Codes: H04W 4/38 : for collecting sensor information

Abstract

Techniques for determining whether data associated with an autonomous operation of a first unmanned vehicle may be trusted. For example, the first unmanned vehicle may receive an indication related to the data and originating from a second unmanned vehicle over a network. For instance, the indication may indicate that similar data for a similar autonomous operation of the second unmanned vehicle may be untrusted. Based on a level of trust accorded to the indication, the first unmanned vehicle may determine that the data may be untrusted and the autonomous navigation may be directed independently of the data.

Claims

1. A computer-implemented method, comprising:

receiving, by a computer system of an unmanned aerial vehicle (UAV), global positioning system (GPS) data associated with an area, the computer system configured to direct a flight of the UAV to deliver an item from a source to a destination based at least in part on the GPS data;

receiving, by the computer system and over a network, a token from a second UAV;

establishing, by the computer system, a communication channel between the UAV and the second UAV over the network based at least in part on the token;

receiving, by the computer system and over the communication channel, an indication of GPS data spoofing detected in the area from the second UAV;

determining, by the computer system, that the GPS data is spoofed based at least in part on an identifier of the second UAV and on the indication of GPS data spoofing; and

directing, by the computer system, a portion of the flight independently of the GPS data that is spoofed.

2. The computer-implemented method of claim 1, wherein the indication of GPS data spoofing is received from the second UAV over a peer-to-peer network between the UAV and the second UAV.

3. The computer-implemented method of claim 2, wherein the indication of GPS data spoofing is routed to the UAV from the second UAV through a central station.

4. The computer-implemented method of claim 1, wherein determining that the GPS data is spoofed comprises:

determining a level of trust associated with the indication of the GPS data spoofing, wherein the level of trust is determined based at least in part on one or more of;

the identifier of the second UAV, a service provider of the second UAV, a spatial proximity between the UAV and the second UAV, or a time when the indication of GPS data spoofing was generated; and

determining that the GPS data is spoofed based at least in part on the level of trust.

19. The computer-implemented method of claim 1, wherein the communication channel is established based at least in part on an authentication of the second UAV, wherein the authentication uses the token.

20. The computer-implemented method of claim 19, wherein the authentication comprises a determination of a level of trust based at least in part on the token, and wherein determining that the GPS data is spoofed is based at least in part on the level of trust.

5. One or more non-transitory computer readable media comprising instructions that, when executed with a computer system of a first unmanned vehicle, cause the computer system to at least:

access first navigation data of a source external to the first unmanned vehicle, the first navigation data associated with directing an autonomous navigation of the first unmanned vehicle within an area;

receive, over a network, a token from a second unmanned vehicle;

establish a communication channel between the first unmanned vehicle and the second unmanned vehicle over the network based at least in part on the token;

receive, from the second unmanned vehicle over the communication channel, an indication that second navigation data of the second unmanned vehicle is untrusted within the area;

determine that the first navigation data is untrusted based at least in part on the indication that the second navigation data is untrusted; and

direct the autonomous navigation of the first unmanned vehicle independently of the first navigation data based at least in part on the first navigation data being untrusted.

6. The one or more non-transitory computer readable media of claim 5, wherein the first unmanned vehicle is configured to deliver an item available from an electronic marketplace, wherein the source external to the first unmanned vehicle comprises a global positioning system (GPS), and wherein the first navigation data comprises GPS data.

7. The one or more non-transitory computer readable media of claim 6, wherein the first navigation data indicates a first location of the first unmanned vehicle, wherein the second navigation data indicates a second location of the second unmanned vehicle, and wherein determining that the first navigation data is untrusted comprises determining that the first location and the second location are associated with the area.

8. The one or more non-transitory computer readable media of claim 7, wherein the first navigation data is associated with a first time frame, wherein the second navigation data is associated with a second time frame, and wherein determining that the first navigation data is untrusted comprises determining that the first time frame is within a predefined time range of the second time frame.

9. The one or more non-transitory computer readable media of claim 8, wherein the first unmanned vehicle is configured to deliver an item, and wherein the predefined time range is based at least in part on at least one characteristic of the item.

10. The one or more non-transitory computer readable media of claim 5, wherein determining that the first navigation data is untrusted comprises:

determining a level of trust associated with the indication that the second navigation data is untrusted, the level of trust determined based at least in part on a history of untrusted navigation data of the second unmanned vehicle; and

determining that the first navigation data is untrusted based at least in part on the level of trust.

11. The one or more non-transitory computer readable media of claim 5, wherein determining that the first navigation data is untrusted comprises:

determining a level of trust associated with the indication that the second navigation data is untrusted, the level of trust determined based at least in part on an identity of an operator of the second unmanned vehicle; and

determining that the first navigation data is untrusted based at least in part on the level of trust.

12. The one or more non-transitory computer readable media of claim 5, wherein determining that the first navigation data is untrusted comprises determining that a number of additional indications of untrusted navigation data associated with the area exceeds a threshold.

13. A system installed at a central station and configured to communicate with a plurality of unmanned vehicles over a network, the system comprising:

one or more processors; and

one or more computer readable media comprising instructions that, when executed with the one or more processors, cause the system to at least;

access, over the network, first navigation data of a source external to a first unmanned vehicle, the first navigation data associated with directing an autonomous navigation of the first unmanned vehicle within an area;

generate a map associating locations with indications of untrusted navigation data;

access, based at least in part on the map, an indication that second navigation data of a second unmanned vehicle is untrusted within the area;

determine that the first navigation data is untrusted based at least in part on the indication that the second navigation data is untrusted; and

generate a corrective action associated with directing the autonomous navigation of the first unmanned vehicle independently of the first navigation data that is untrusted.

14. The system of claim 13, wherein the corrective action comprises:

requesting sensor data from navigation sensors of the first unmanned vehicle;

confirming that the first navigation data is untrusted based at least in part on the sensor data; and

directing the autonomous navigation of the first unmanned vehicle based at least in part on the sensor data.

15. The system of claim 13, wherein the corrective action comprises:

requesting image data of a location of the first unmanned vehicle from an imaging sensor installed on the first unmanned vehicle;

comparing the image data and known image data corresponding to the location; and

confirming that the first navigation data is untrusted based at least in part on the comparing of the image data and the known image data.

16. The system of claim 13, wherein the corrective action comprises:

analyzing the first navigation data to determine that the first navigation data indicates an operation that is associated with the autonomous navigation and that is unsupported by the first unmanned vehicle; and

confirming that the first navigation data is untrusted based at least in part on the operation.

17. The system of claim 13, wherein the corrective action comprises:

reporting that the first navigation data is untrusted to a central station; and

facilitating remote control over the first unmanned vehicle from the central station.

18. The system of claim 13, wherein the corrective action comprises:

causing the first unmanned vehicle to park; and

reporting that the first unmanned vehicle is parked to a central station.