IP Library Granted Patent US 11,122,062
Granted Patent B2
US 11,122,062 · App. 16/364,219 · Granted Sep 14, 2021

Remote interference assessment and response for autonomous vehicles

Inventors: Cesar Augusto Rodriguez Bravo (Alajuela, CR); David Jaramillo (Durham, NC); Romelia H. Flores (Keller, TX); Gregory J. Boss (Saginaw, MI)
Assignee: International Business Machines Corporation
H04L63/1416
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Quick Facts
Patent No.
US 11,122,062
App. No.
16/364,219
Granted
Sep 14, 2021
Kind
B2
Abstract

Securing an autonomous vehicle against remote interference. Electronic communications are classified and rated according to communication port and package content. Communication ratings are processed to assess risk of remote interference. At-risk communications trigger interference response actions according to pre-defined ratings thresholds.

Claims (63)

1. A computer-implemented method for securing an autonomous vehicle, the method comprising:

classifying network communications received at a set of communication ports within a vehicle;

determining a risk level for network communications having target classifications;

responsive to a set of high-risk communication, determining an impact level for each high-risk communication of the set of high-risk communications;

assigning a set of suspicion scores to high-risk communications of the set of high-risk communications received during a tracking period, each suspicion score being a mathematical combination of the risk level and the impact level determined for a respective high-risk communication received during the tracking period;

determining, for the vehicle, a risk exposure score corresponding to the set of suspicion scores assigned to the high-risk communications received during the tracking period; and

taking an interference response assigned to the risk exposure score;

wherein:

the high-risk communications of the set of high-risk communications are network communications assigned risk levels meeting a threshold value.

2. The method of claim 1 , wherein the target classifications are vehicle navigation communications and vehicle operations communications.

3. The method of claim 2 , further comprising:

responsive to detecting movement of the vehicle, blocking the vehicle operations communications.

4. The method of claim 2 , further comprising:

responsive to classifying a first vehicle operations communication, prompting a user for approval to accept the first vehicle operations communication.

5. The method of claim 1 , further comprising:

identifying the set of communication ports within the vehicle; and

monitoring network communications on the identified ports;

wherein the set of communication ports are identified individually by type of data flowing through each port of the set of communication ports.

6. The method of claim 5 , wherein a target classification of the network communications is a data type mis-matching communication.

7. The method of claim 1 , further comprising:

recording the classified network communications.

8. The method of claim 1 , wherein the target classifications of the network communications include location communications.

9. The method of claim 1 , wherein the interference response is assigned to the risk exposure score according to a best-practices guide provided by a manufacturer of the vehicle.

10. A computer program product comprising a computer-readable storage medium having a set of instructions stored therein which, when executed by a processor, causes the processor to secure an autonomous vehicle by:

classifying network communications received at a set of communication ports within a vehicle;

determining a risk level for network communications having target classifications;

responsive to a set of high-risk communication, determining an impact level for each high-risk communication of the set of high-risk communications;

assigning a set of suspicion scores to high-risk communications of the set of high-risk communications received during a tracking period, each suspicion score being a mathematical combination of the risk level and the impact level determined for a respective high-risk communication received during the tracking period;

determining, for the vehicle, a risk exposure score corresponding to the set of suspicion scores assigned to the high-risk communications received during the tracking period; and

taking an interference response assigned to the risk exposure score;

wherein:

the high-risk communications of the set of high-risk communications are network communications assigned risk levels meeting a threshold value.

11. The computer program product of claim 10 , wherein the target classifications are vehicle navigation communications and vehicle operations communications.

12. The computer program product of claim 10 , further causing the processor to secure the autonomous vehicle by:

identifying the set of communication ports within the vehicle; and

monitoring network communications on the identified ports;

wherein the set of communication ports are identified individually by type of data flowing through each port of the set of communication ports.

13. The computer program product of claim 10 , further causing the processor to secure the autonomous vehicle by:

recording the classified network communications.

14. The computer program product of claim 10 , wherein the target classifications of the network communications include location communications.

15. A computer system for securing an autonomous vehicle, the computer system comprising:

a processor set; and

a computer readable storage medium;

wherein:

the processor set is structured, located, connected, and/or programmed to run program instructions stored on the computer readable storage medium; and

the program instructions which, when executed by the processor set, cause the processor set to secure the autonomous vehicle by:

classifying network communications received at a set of communication ports within a vehicle;

determining a risk level for network communications having target classifications;

responsive to a set of high-risk communication, determining an impact level for each high-risk communication of the set of high-risk communications;

assigning a set of suspicion scores to high-risk communications of the set of high-risk communications received during a tracking period, each suspicion score being a mathematical combination of the risk level and the impact level determined for a respective high-risk communication received during the tracking period;

determining, for the vehicle, a risk exposure score corresponding to the set of suspicion scores assigned to the high-risk communications received during the tracking period; and

taking an interference response assigned to the risk exposure score;

wherein:

the high-risk communications of the set of high-risk communications are network communications assigned risk levels meeting a threshold value.

16. The computer system of claim 15 , wherein the target classifications are vehicle navigation communications and vehicle operations communications.

17. The computer system of claim 15 , further causing the processor to secure the autonomous vehicle by:

identifying the set of communication ports within the vehicle; and

monitoring network communications on the identified ports;

wherein the set of communication ports are identified individually by type of data flowing through each port of the set of communication ports.

18. The computer system of claim 17 , wherein a target classification of the network communications is a data type mis-matching communication.

19. The computer system of claim 15 , further causing the processor to secure the autonomous vehicle by:

recording the classified network communications.

20. The computer system of claim 15 , wherein the target classifications of the network communications include location communications.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 18, 2021
From: INTERNATIONAL BUSINESS MACHINES CORPORATION
To: KYNDRYL, INC.
Reel/Frame 058213/0912 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 26, 2019
From: RODRIGUEZ BRAVO, CESAR AUGUSTO; JARAMILLO, DAVID; FLORES, ROMELIA H.; BOSS, GREGORY J.
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 048694/0052 →
Continuity (1)
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