Misbehavior protection for connected vehicle communication

1. For use in conjunction with a system that includes connected vehicle communications in which vehicles in the system each have an onboard processor subsystem and associated sensors, said processor subsystem controlling the generation, transmission, and receiving of messages communicated between vehicles for purposes including crash avoidance; a method for determining, by a given vehicle receiving messages, the occurrence of misbehavior comprising the steps of:

processing received messages by performing a plurality of plausibility determinations to obtain a respective number of plausibility measurements;

determining at least one context for the region at which said given vehicle is located;

weighting said plurality of plausibility measurements in accordance with values determined from said at least one context to obtain a respective plurality of plausibility indicator values; and

deriving a misbehavior confidence indicator using said plausibility indicator values.

2. The method as defined by claim 1 , wherein the steps of said method are implemented under control of at least one electronic processor subsystem.

3. The method as defined by claim 2 , wherein said at least one electronic processor subsystem comprises said onboard processor subsystem operating in conjunction with at least one special purpose processor.

4. The method as defined by claim 1 , wherein said misbehavior confidence indicator comprises an array of said plausibility indicator values.

5. The method as defined by claim 1 , wherein said misbehavior confidence indicator comprises a value derived from a count of plausibility indicator values that meet predetermined criteria.

6. The method as defined by claim 1 , wherein said misbehavior confidence indicator comprises a sum of at least a plurality of plausibility indicator values that meet predetermined criteria.

7. The method as defined by claim 1 , wherein said step of determining at least one context comprises determining a plurality of contexts.

8. The method as defined by claim 1 , wherein said step of performing a plurality of plausibility determinations comprises performing several plausibility determinations.

9. The method as defined by claim 1 , wherein said plurality of plausibility determinations are performed in parallel.

10. The method as defined by claim 1 , wherein said step of performing a plurality of plausibility determinations comprises performing several plausibility determinations in a series sequence.

11. The method as defined by claim 1 , further comprising providing a number of misbehavior detection routines, and implementing said misbehavior detection routines in conjunction with said plausibility confidence indicator to obtain an indication of misbehavior that is occurring.

12. The method as defined by claim 11 , wherein said indication of occurrence of misbehavior comprises an indication of a particular type of cyber attack that may be occurring.

13. The method as defined by claim 11 , wherein said step of providing a number of misbehavior detection routines comprises providing misbehavior detection routines which can recognize characteristics of behavior of message sources as being an indication of a particular type of cyber attack.

14. The method as defined by claim 1 , wherein said step of determining at least one context comprises determining at least one context from a group consisting of vehicle population, neighboring vehicle telemetry, time of day, weather, risk/threat model, computation overhead, communication overhead, location, and environment.

15. For use in conjunction with a system that includes connected vehicle communications in which vehicles in the system each have an onboard processor subsystem and associated sensors, said processor subsystem controlling the generation, transmission, and receiving of messages communicated between vehicles for purposes including crash avoidance; a method for determining, by a given vehicle receiving messages, the occurrence of misbehavior comprising the steps of:

processing received messages by performing a plurality of plausibility determinations to obtain a respective number of plausibility measurements from which a respective plurality of plausibility indicator values are derived;

providing a plurality of misbehavior detection routines;

implementing said misbehavior detection routines in conjunction with said plurality of plausibility indicator values; and

determining the occurrence of misbehavior from the outputs of said misbehavior detection routines.

16. The method as defined by claim 15 , wherein the steps of said method are implemented under control of at least one electronic processor subsystem.

17. The method as defined by claim 16 , wherein said at least one electronic processor subsystem comprises said onboard processor subsystem operating in conjunction with at least one special purpose processor.

18. The method as defined by claim 15 , further comprising determining at least one context for the region at which said given vehicle is located, and wherein said misbehavior detection routines are implemented in conjunction with values determined from said at least one context.

19. The method as defined by claim 15 , wherein said misbehavior detection routines are performed in parallel.

20. The method as defined by claim 15 , wherein said misbehavior detection routines are performed in a series sequence.

21. For use in conjunction with a system that includes connected vehicle communications in which vehicles in the system each have an onboard processor subsystem and associated sensors, said processor subsystem controlling the generation, transmission, and receiving of messages communicated between vehicles for purposes including crash avoidance; a method for determining, by a given vehicle receiving messages, the occurrence of misbehavior, comprising the steps of:

processing received messages by performing a plurality of plausibility determinations to obtain a respective number of plausibility measurements;

determining at least one context for the region at which said given vehicle is located;

deriving, from said at least one context, rankings of the plausibility determinations and their associated measurements, and weighting said measurements in accordance with the rankings to obtain an array of plausibility indicator values;

providing a plurality of misbehavior detection routines;

selecting at least some of the misbehavior detection routines in accordance with said at least one context;

implementing the selected misbehavior routine in conjunction with respective members of the array of plausibility indicators; and

determining occurrence of misbehavior from the outputs of the selected misbehavior detection routines.

22. For use in conjunction with a system that includes connected vehicle communications in which vehicles in the system each have an onboard processor subsystem and associated sensors, said processor subsystem controlling the generation, transmission, and receiving of messages communicated between vehicles for purposes including crash avoidance; a method for determining, by a given vehicle receiving messages, the occurrence of misbehavior, comprising the steps of:

processing received messages by performing a plurality of plausibility determinations to obtain a respective number of plausibility measurements;

determining at least one context for the region at which said given vehicle is located;

deriving, from said at least one context, rankings of the plausibility determinations and their associated measurements;

implementing plausibility determinations and weightings in accordance with values determined from said at least one context, in a sequence that depends on said rankings, and accumulating the resultant plausibility indications until said accumulation exceeds a predetermined threshold;

providing a plurality of misbehavior detection routines;

sequentially implementing each of said misbehavior detection routines in conjunction with said at least one context and said accumulation of plausibility indications to obtain a misbehavior output; and

issuing a misbehavior warning depending on said misbehavior output.