Methods and systems for utilizing information collected from multiple sensors to protect a vehicle from malware and attacks

1. A method of analyzing sensor information to identify an abnormal vehicle behavior, comprising:

monitoring, via a processor, a plurality of sensors in close proximity to a vehicle to collect sensor information;

activating a monitoring and analysis system to collect and analyze the sensor information from the plurality of sensors, the plurality of sensors including one or more of a closely-integrated vehicle sensor, a loosely-integrated vehicle sensor, or a non-vehicle sensor;

analyzing the collected sensor information to generate an analysis result, wherein the analyzing comprises:

applying a generated behavior vector to a machine learning classifier model to generate the analysis result, wherein the generated behavior vector is based on the collected sensor information; and

using the generated analysis result to determine whether a behavior of the vehicle is abnormal.

2. The method of claim 1 , further comprising:

generating a communication message in response to determining that the behavior of the vehicle is abnormal; and

sending the generated communication message to an external entity.

3. The method of claim 1 , wherein the analyzing the collected sensor information to generate the analysis result further comprises comparing sensor information collected from a mobile device sensor to sensor information collected from a vehicle sensor.

4. The method of claim 1 , wherein the analyzing the collected sensor information to generate the analysis result further comprises comparing sensor information collected from two or more of:

the closely-integrated vehicle sensor;

the loosely-integrated vehicle sensor; or

the non-vehicle sensor.

5. The method of claim 1 , wherein the analyzing the collected sensor information to generate the analysis result further comprises comparing sensor information collected from a first sensor to sensor information collected from a second sensor, wherein the first sensor is different from the second sensor.

6. The method of claim 1 , wherein the processor is a mobile device processor in a mobile device, the method further comprising:

determining by the mobile device processor whether the mobile device is inside the vehicle.

7. The method of claim 1 , wherein the processor is a vehicle processor in the vehicle, the method further comprising:

determining by the vehicle processor whether a mobile device is inside the vehicle;

establishing a communication link to the mobile device in response to determining that the mobile device is inside the vehicle; and

receiving mobile device sensor information via the communication link.

8. A computing device, comprising:

a processor configured with processor-executable instructions to perform operations comprising:

monitoring a plurality of sensors in close proximity to a vehicle to collect sensor information;

activating a monitoring and analysis system to collect and analyze the sensor information from the plurality of sensors, the plurality of sensors including one or more of a closely-integrated vehicle sensor, a loosely-integrated vehicle sensor, or a non-vehicle sensor;

analyzing the collected sensor information to generate an analysis result, wherein the analyzing comprises:

applying a generated behavior vector to a machine learning classifier model to generate the analysis result, wherein the generated behavior vector is based on the collected sensor information; and

using the generated analysis result to determine whether a behavior of the vehicle is abnormal.

9. The computing device of claim 8 , wherein the processor is configured with processor-executable instructions to perform operations further comprising:

generating a communication message in response to determining that the behavior of the vehicle is abnormal; and

sending the generated communication message to an external entity.

10. The computing device of claim 8 , wherein the processor is configured with processor-executable instructions to perform operations such that the analyzing the collected sensor information to generate the analysis result further comprises comparing sensor information collected from a mobile device sensor to sensor information collected from a vehicle sensor.

11. The computing device of claim 8 , wherein the processor is configured with processor-executable instructions to perform operations such that the analyzing the collected sensor information to generate the analysis result further comprises comparing sensor information collected from two or more of:

the closely-integrated vehicle sensor;

the loosely-integrated vehicle sensor; or

the non-vehicle sensor.

12. The computing device of claim 8 , wherein the processor is configured with processor-executable instructions to perform operations such that the analyzing the collected sensor information to generate the analysis result further comprises comparing sensor information collected from a first sensor to sensor information collected from a second sensor, wherein the first sensor is different from the second sensor.

13. The computing device of claim 8 , wherein:

the computing device is a mobile device; and

the processor is configured with processor-executable instructions to perform operations further comprising

determining whether the mobile device is inside the vehicle.

14. The computing device of claim 8 , wherein:

the computing device is embedded in the vehicle; and

the processor is configured with processor-executable instructions to perform operations further comprising:

determining whether a mobile device is inside the vehicle;

establishing a communication link to the mobile device in response to determining that the mobile device is inside the vehicle; and

receiving mobile device sensor information via the communication link.

15. A non-transitory computer readable storage medium having stored thereon processor-executable software instructions configured to cause a computing device processor to perform operations for analyzing sensor information to identify an abnormal vehicle behavior, the operations comprising:

monitoring a plurality of sensors in close proximity to a vehicle to collect the sensor information;

activating a monitoring and analysis system to collect and analyze the sensor information from the plurality of sensors, the plurality of sensors including one or more of a closely-integrated vehicle sensor, a loosely-integrated vehicle sensor, and a non-vehicle sensor;

analyzing the collected sensor information to generate an analysis result, wherein analyzing comprises:

applying a generated behavior vector to a machine learning classifier model to generate an analysis result, wherein the generated behavior vector is based on the collected sensor information; and

using the generated analysis result to determine whether a behavior of the vehicle is abnormal.

16. The non-transitory computer readable storage medium of claim 15 , wherein the stored processor-executable instructions are configured to cause the computing device processor to perform operations further comprising:

generating a communication message in response to determining that the behavior of the vehicle is abnormal; and

sending the generated communication message to an external entity.

17. The non-transitory computer readable storage medium of claim 15 , wherein the stored processor-executable instructions are configured to cause the computing device processor to perform operations such that the analyzing the collected sensor information to generate the analysis result further comprises comparing sensor information collected from a mobile device sensor to sensor information collected from a vehicle sensor.

18. The non-transitory computer readable storage medium of claim 15 , wherein the stored processor-executable instructions are configured to cause the computing device processor to perform operations such that the analyzing the collected sensor information to generate the analysis result further comprises comparing sensor information collected from two or more of:

the closely-integrated vehicle sensor;

the loosely-integrated vehicle sensor; or

the non-vehicle sensor.

19. The non-transitory computer readable storage medium of claim 15 , wherein the stored processor-executable instructions are configured to cause the computing device processor to perform operations such that the analyzing the collected sensor information to generate the analysis result further comprises comparing sensor information collected from a first sensor to sensor information collected from a second sensor, wherein the first sensor is different from the second sensor.

20. The non-transitory computer readable storage medium of claim 15 , wherein the stored processor-executable instructions are configured to cause a mobile device processor in a mobile device to perform operations comprising:

determining whether the mobile device is inside the vehicle.

21. The non-transitory computer readable storage medium of claim 15 , wherein the stored processor-executable instructions are configured to cause a vehicle processor in the vehicle to perform operations comprising:

determining whether a mobile device is inside the vehicle;

establishing a communication link to the mobile device in response to determining that the mobile device is inside the vehicle; and

receiving mobile device sensor information via the communication link.

22. A computing device, comprising:

means for monitoring a plurality of sensors in close proximity to a vehicle to collect sensor information;

means for activating a monitoring and analysis system to collect and analyze the sensor information from the plurality of sensors, the plurality of sensors including one or more of a closely-integrated vehicle sensor, a loosely-integrated vehicle sensor, and a non-vehicle sensor;

means for analyzing the collected sensor information to generate an analysis result, wherein means for analyzing comprises:

means for applying a generated behavior vector to a machine learning classifier model to generate an analysis result, wherein the generated behavior vector is based on the collected sensor information; and

means for using the generated analysis result to determine whether a behavior of the vehicle is abnormal.

23. The computing device of claim 22 , further comprising:

means for generating a communication message in response to determining that the behavior of the vehicle is abnormal; and

means for sending the generated communication message to an external entity.

24. The computing device of claim 22 , wherein the means for analyzing the collected sensor information to generate the analysis result further comprises means for comparing sensor information collected from a mobile device sensor to sensor information collected from a vehicle sensor.

25. The computing device of claim 22 , wherein the means for analyzing the collected sensor information to generate the analysis result further comprises means for comparing sensor information collected from two or more of:

the closely-integrated vehicle sensor;

the loosely-integrated vehicle sensor; or

the non-vehicle sensor.

26. The computing device of claim 22 , wherein the means for analyzing the collected sensor information to generate the analysis result further comprises means for comparing sensor information collected from a first sensor to sensor information collected from a second sensor, wherein the first sensor is different from the second sensor.

27. The computing device of claim 22 , wherein the computing device is a mobile device, the mobile device further comprising:

means for determining whether the mobile device is inside the vehicle.

28. The computing device of claim 22 , wherein the computing device is built into the vehicle, the computing device further comprising:

means for determining whether a mobile device is inside the vehicle;

means for establishing a communication link to the mobile device in response to determining that the mobile device is inside the vehicle; and

means for receiving mobile device sensor information via the communication link.