Method and system for misbehavior detection report management routing

1. A method, performed by a processor of vehicle-to-everything (V2X) equipment, for managing misbehavior reports, comprising:

generating a misbehavior report identifying a misbehavior condition associated with at least one of inaccurate or corrupted data in response to the misbehavior condition being associated with an aggregated criticality value that exceeds a threshold;

storing the generated misbehavior report in response to determining whether to store the generated misbehavior report based on an assigned level of criticality; and one or more of:

classifying the misbehavior condition that is detected based on a potential safety impact of the misbehavior condition or a level of potential traffic disruption;

determining an observed length of the misbehavior condition;

determining a number of recurrences of the misbehavior condition; or

determining a number of neighboring vehicles experiencing the misbehavior condition, and

further comprising generating the aggregated criticality value based on one or more of the classification of the misbehavior condition, the observed length of the misbehavior condition, the number of recurrences of the misbehavior condition, and the number of neighboring vehicles experiencing the misbehavior condition.

2. The method of claim 1 , further comprising:

transmitting the generated misbehavior report to a misbehavior managing authority.

3. The method of either of claim 2 , further comprising analyzing sensor data using a machine learning model to determine whether a misbehavior condition is detected, wherein generating the misbehavior report identifying the misbehavior condition comprises generating a misbehavior report that includes one or more of: the machine learning model; an output of the machine learning model; a principal component analysis of the machine learning model; an intermediate representation of the machine learning model; or an identifier of the machine learning model.

4. The method of claim 1 , further comprising one or more of:

determining a confidence level of detection of the misbehavior condition that is a subject of the misbehavior report;

determining a number of additional messages from one or more neighboring vehicles available to accompany the misbehavior report; or

determining a network communication link to the misbehavior managing authority that is available to transmit the misbehavior report, or

storing the generated misbehavior report is further based on one or more of the confidence level of detection of the misbehavior condition, the number of additional messages from the one or more neighboring vehicles available to accompany the misbehavior report, or the network communication link to the misbehavior managing authority being available to transmit the misbehavior report.

5. The method of claim 4 , further comprising:

classifying the detected misbehavior condition that is a subject of the generated misbehavior report based on a potential safety impact of the misbehavior condition;

assigning an initial weight to the misbehavior report based on the classification of the misbehavior condition;

assigning a decay factor to the misbehavior report; and

determining a weight of the misbehavior report on a regular interval based on the assigned initial weight and the decay factor, wherein storing the generated misbehavior report is further based on the determined weight of the misbehavior report.

6. The method of claim 4 , further comprising:

classifying the detected misbehavior condition that is a subject of the generated misbehavior report based on a potential safety impact of a level of potential traffic disruption;

assigning an initial weight to the misbehavior report based on the classification of the misbehavior condition;

assigning a decay factor to the misbehavior report; and

determining a weight of the misbehavior report on a regular interval based on the assigned initial weight and the decay factor, wherein storing the generated misbehavior report is further based on the determined weight of the misbehavior report.

7. The method of claim 6 , further comprising:

performing a flush operation in response to determining that an available storage space falls below a storage space threshold level, wherein the flush operation deletes stored misbehavior reports based on one of: an order that the misbehavior report is stored, a classification of the misbehavior condition, a number of duplicates stored duplication, or a determined weight of the misbehavior report.

8. The method of claim 7 , further comprising transmitting the misbehavior report based on at least one of: the classification of the misbehavior condition; the order in which the misbehavior report is stored; or a fairness rule.

9. The method of claim 8 , further comprising:

receiving feedback from the misbehavior managing authority; and

performing one or more of:

adjusting generation parameters, wherein the misbehavior report is further in response to the feedback;

in response to the feedback, adjusting one or more thresholds for the confidence level of detection of the misbehavior condition, the number of additional messages from the one or more neighboring vehicles available to accompany the misbehavior report, and whether a network communication link to the misbehavior managing authority is available to transmit the misbehavior report that are used to determine whether to store the generated misbehavior report; or

adjusting transmission parameters that impact whether the misbehavior report is transmitted to the misbehavior managing authority in response to the feedback.

10. The method of claim 2 , further comprising transmitting the misbehavior report to a misbehavior preprocessing entity for preprocessing before being transmitted to the misbehavior managing authority.

11. A misbehavior management system for use in vehicle-to-everything (V2X) equipment, comprising:

a memory storage coupled to the transmitter and configured to store misbehavior reports; and

a processor coupled to the memory storage, wherein the processor is configured with processor-executable instructions to:

generate a misbehavior report identifying a misbehavior condition associated with at least one of inaccurate or corrupted data in response to the misbehavior condition being associated with an aggregated criticality value that exceeds a threshold; and

store the generated misbehavior report in response to determine whether to store the generated misbehavior report based on an assigned level of criticality;

one or more of:

classify the misbehavior condition that is detected based on a potential safety impact of the misbehavior condition or a level of potential traffic disruption;

determine an observed length of the misbehavior condition;

determine a number of recurrences of the misbehavior condition; or

determine a number of neighboring vehicles experiencing the misbehavior condition,

wherein the processor is further configured with processor-executable instructions to generate the misbehavior report to identify the misbehavior condition based on one or more of the classification of the misbehavior condition, the observed length of the misbehavior condition, the number of recurrences of the misbehavior condition, and the number of neighboring vehicles experiencing the misbehavior condition.

12. The misbehavior management system of claim 11 , further comprising a transmitter coupled to the processor and configured to wireless transmit and receive data related to misbehavior reports to and from a misbehavior managing authority, wherein the processor is further configured with processor-executable instructions to:

transmit the generated misbehavior report to a misbehavior managing authority.

13. The misbehavior management system of claim 12 , wherein the processor is further configured with processor-executable instructions to:

analyze sensor data using a machine learning model to determine whether a misbehavior condition is detected; and

generate the misbehavior report identifying the misbehavior condition by generating a misbehavior report that includes one or more of: the machine learning model; an output of the machine learning model; a principal component analysis of the machine learning model; an intermediate representation of the machine learning model; or an identifier of the machine learning model.

14. The misbehavior management system of claim 11 , wherein the processor is further configured with processor-executable instructions to perform one or more of:

determining a confidence level of detection of the misbehavior condition that is a subject of the misbehavior report;

determining a number of additional messages from one or more neighboring vehicles available to accompany the misbehavior report; or

determine a network communication link to the misbehavior managing authority that is available to transmit the misbehavior report, and

wherein the processor is further configured with processor-executable instructions to store the misbehavior report based on one or more of the confidence level of detection of the misbehavior condition, the number of additional messages from one or more neighboring vehicles available to accompany the misbehavior report, the network communication link to the misbehavior managing authority being available to transmit the misbehavior report.

15. The misbehavior management system of claim 14 , wherein the processor is further configured with processor-executable instructions to:

classify the detected misbehavior condition that is a subject of the generated misbehavior report based on a potential safety impact of the misbehavior condition;

assign an initial weight to the misbehavior report based on the classification of the misbehavior condition;

assign a decay factor to the misbehavior report; and

determine a weight of the misbehavior report on a regular interval based on the assigned initial weight and the decay factor, wherein storing the misbehavior report is further based on the determined weight of the misbehavior report.

16. The misbehavior management system of claim 15 , wherein the processor is further configured with processor-executable instructions to:

classify the detected misbehavior condition that is a subject of the generated misbehavior report based on a potential safety impact of a level of potential traffic disruption;

assign an initial weight to the misbehavior report based on the classification of the misbehavior condition;

assign a decay factor to the misbehavior report; and

determine a weight of the misbehavior report on a regular interval based on the assigned initial weight and the decay factor, wherein storing the misbehavior report is further based on the determined weight of the misbehavior report.

17. The misbehavior management system of claim 15 , wherein the processor is further configured with processor-executable instructions to:

perform a flush operation in response to determining that an available storage space falls below a storage space threshold level, wherein the flush operation deletes stored misbehavior reports based on one of: an order that the misbehavior report is stored, a classification of the misbehavior condition, a number of duplicates stored duplication, or a determined weight of the misbehavior report.

18. The misbehavior management system of claim 17 , further comprising a transmitter coupled to the processor and configured to wireless transmit and receive data related to misbehavior reports to and from a misbehavior managing authority, wherein the processor is further configured with processor-executable instructions to transmit the misbehavior report based on at least one of: the classification of the misbehavior condition, an order in which the misbehavior report is stored, or a fairness rule.

19. The misbehavior management system of claim 18 , wherein the processor is further configured with processor-executable instructions to:

receive feedback from the misbehavior managing authority; and

perform one or more of:

adjusting generation parameters, wherein generating the misbehavior report is further in response to the feedback;

in response to the feedback, adjusting one or more thresholds for the confidence level of detection of the misbehavior condition, the number of additional messages from the one or more neighboring vehicles available to accompany the misbehavior report, and whether a network communication link to the misbehavior managing authority is available to transmit the misbehavior report that are used to determine whether to store the generated misbehavior report; or

adjusting transmission parameters that impact whether the misbehavior report is transmitted to the misbehavior managing authority in response to the feedback.

20. The misbehavior management system of claim 11 , further comprising a transmitter coupled to the processor and configured to wireless transmit and receive data related to misbehavior reports to and from a misbehavior managing authority, wherein the processor is further configured with processor-executable instructions to transmit the misbehavior report to a misbehavior preprocessing entity for preprocessing before being transmitted to the misbehavior managing authority.

21. A misbehavior management system for use in Vehicle-to-Everything (V2X) equipment, comprising:

means for generating a misbehavior report identifying a misbehavior condition associated with at least one of inaccurate or corrupted data in response to the misbehavior condition being associated with an aggregated criticality value that exceeds a threshold; and

means for storing the generated misbehavior report in response to determining whether to store the generated misbehavior report based on an assigned level of criticality;

one or more of:

means for classifying the misbehavior condition that is detected based on a potential safety impact of the misbehavior condition or a level of potential traffic disruption;

means for determining an observed length of the misbehavior condition; or

means for determining a number of recurrences of the misbehavior condition; or

means for determining a number of neighboring vehicles experiencing the misbehavior condition, and

further comprising means for generating the aggregated criticality value based on one or more of the classification of the misbehavior condition, the observed length of the misbehavior condition, the number of recurrences of the misbehavior condition, or the number of neighboring vehicles experiencing the misbehavior condition.

22. The misbehavior management system of claim 21 , further comprising means for transmitting the generated misbehavior report to a misbehavior managing authority.

23. The misbehavior management system included of claim 21 , further comprising one or more of:

means for determining a confidence level of detection of the misbehavior condition that is a subject of the misbehavior report;

means for determining a number of additional messages from one or more neighboring vehicles available to accompany the misbehavior report; or

means for determining a network communication link to the misbehavior managing authority that is available to transmit the misbehavior report,

wherein means for storing the misbehavior report based on one or more of the confidence level of detection of the misbehavior condition, the number of additional messages from the one or more neighboring vehicles available to accompany the misbehavior report, the network communication link to the misbehavior managing authority being available to transmit the misbehavior report.

24. The misbehavior management system of claim 23 , further comprising:

means for classifying the detected misbehavior condition that is a subject of the generated misbehavior report based on a potential safety impact of the misbehavior condition;

means for assigning an initial weight to the misbehavior report based on the classification of the misbehavior condition;

means for assigning a decay factor to the misbehavior report; and

means for determining a weight of the misbehavior report on a regular interval based on the assigned initial weight and the decay factor, wherein storing the misbehavior report is further based on the determined weight of the misbehavior report.

25. The misbehavior management system of claim 24 , further comprising:

means for classifying the detected misbehavior condition that is a subject of the generated misbehavior report based on a potential safety impact of a level of potential traffic disruption;

means for assigning an initial weight to the misbehavior report based on the classification of the misbehavior condition;

means for assigning a decay factor to the misbehavior report; and

means for determining a weight of the misbehavior report on a regular interval based on the assigned initial weight and the decay factor, wherein storing the misbehavior report is further based on the determined weight of the misbehavior report.

26. The misbehavior management system of claim 25 , further comprising means for transmitting the generated misbehavior report to a misbehavior managing authority, wherein means for transmitting the misbehavior report comprises means for transmitting the misbehavior report based on at least one of: the classification of the misbehavior condition; an order in which the misbehavior report is stored; or a fairness rule.

27. A non-transitory processor readable medium having stored thereon processor-executable instructions configured to cause a processor of a misbehavior management system to perform operations comprising:

generating a misbehavior report identifying a misbehavior condition associated with at least one of inaccurate or corrupted data in response to the misbehavior condition being associated with an aggregated criticality value that exceeds a threshold;

storing the generated misbehavior report in response to determining whether to store the generated misbehavior report based on an assigned level of criticality; and

one or more of:

classifying the misbehavior condition that is detected based on a potential safety impact of the misbehavior condition or a level of potential traffic disruption;

determining an observed length of the misbehavior condition;

determining a number of recurrences of the misbehavior condition; or

determining a number of neighboring vehicles experiencing the misbehavior condition, and

further comprising generating the aggregated criticality value based on one or more of the classification of the misbehavior condition, the observed length of the misbehavior condition, the number of recurrences of the misbehavior condition, and the number of neighboring vehicles experiencing the misbehavior condition.