System, apparatus, and method for adaptive observation of mobile device behavior
First Claim
1. A method of adaptively observing device behaviors in a computing device, comprising:
- computing, via a processor of the computing device, probability values that each indicate a likelihood of a high-level behavior negatively impacting a performance characteristic or a battery consumption level of the computing device over time;
identifying, via the processor, high-level behaviors that have a high probability of negatively impacting the performance characteristic or the battery consumption level of the computing device over time based on a comparison of the computed probability values to a predetermined threshold value;
generating, via the processor, a first behavior vector after the comparison of the computed probability values to the predetermined threshold value, the generated first behavior vector including at least one value for each of the identified high-level behaviors;
using a result of applying the generated first behavior vector to a classifier model to determine a number of lower-level device behaviors that are to be observed in the computing device, select the determined number of lower-level device behaviors for observation, and determine a level of detail for each of the selected lower-level device behaviors; and
observing, via the processor, the determined number of selected lower-level device behaviors at their corresponding determined level of detail to collect behavior information.
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Accused Products
Abstract
Methods, devices and systems for detecting suspicious or performance-degrading mobile device behaviors intelligently, dynamically, and/or adaptively determine computing device behaviors that are to be observed, the number of behaviors that are to be observed, and the level of detail or granularity at which the mobile device behaviors are to be observed. The various aspects efficiently identify suspicious or performance-degrading mobile device behaviors without requiring an excessive amount of processing, memory, or energy resources. Various aspects may correct suspicious or performance-degrading mobile device behaviors. Various aspects may prevent identified suspicious or performance-degrading mobile device behaviors from degrading the performance and power utilization levels of a mobile device over time. Various aspects may restore an aging mobile device to its original performance and power utilization levels.
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Citations
26 Claims
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1. A method of adaptively observing device behaviors in a computing device, comprising:
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computing, via a processor of the computing device, probability values that each indicate a likelihood of a high-level behavior negatively impacting a performance characteristic or a battery consumption level of the computing device over time; identifying, via the processor, high-level behaviors that have a high probability of negatively impacting the performance characteristic or the battery consumption level of the computing device over time based on a comparison of the computed probability values to a predetermined threshold value; generating, via the processor, a first behavior vector after the comparison of the computed probability values to the predetermined threshold value, the generated first behavior vector including at least one value for each of the identified high-level behaviors; using a result of applying the generated first behavior vector to a classifier model to determine a number of lower-level device behaviors that are to be observed in the computing device, select the determined number of lower-level device behaviors for observation, and determine a level of detail for each of the selected lower-level device behaviors; and observing, via the processor, the determined number of selected lower-level device behaviors at their corresponding determined level of detail to collect behavior information. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A computing device, comprising:
a processor configured with processor-executable instructions to perform operations comprising; computing probability values that each indicate a likelihood of a high-level behavior negatively impacting a performance characteristic or a battery consumption level of the computing device over time; identifying high-level behaviors that have a high probability of negatively impacting the performance characteristic or the battery consumption level of the computing device over time based on a comparison of the computed probability values to a predetermined threshold value; generating a first behavior vector after the comparison of the computed probability values to the predetermined threshold value, the generated first behavior vector including at least one value for each of the identified high-level behaviors; using a result of applying the generated first behavior vector to a classifier model to determine a number of lower-level device behaviors that are to be observed in the computing device, select the determined number of lower-level device behaviors for observation, and determine a level of detail for each of the selected lower-level device behaviors; and observing the determined number of selected device lower-level behaviors at their corresponding determined level of detail to collect behavior information. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A non-transitory computer readable storage medium having stored thereon processor-executable software instructions configured to cause a processor of a computing device to perform operations comprising:
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computing probability values that each indicate a likelihood of a high-level behavior negatively impacting a performance characteristic or a battery consumption level of the computing device over time; identifying high-level behaviors that have a high probability of negatively impacting the performance characteristic or the battery consumption level of the computing device over time based on a comparison of the computed probability values to a predetermined threshold value; generating a first behavior vector after the comparison of the computed probability values to the predetermined threshold value, the generated first behavior vector including at least one value for each of the identified high-level behaviors; using a result of applying the generated first behavior vector to a classifier model to determine a number of lower-level device behaviors that are to be observed in the computing device, select the determined number of lower-level device behaviors for observation, and determine a level of detail for each of the selected lower-level device behaviors; and observing the determined number of selected lower-level device behaviors at their corresponding determined level of detail to collect behavior information. - View Dependent Claims (16, 17, 18, 19, 20, 21)
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22. A computing device, comprising:
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means for computing probability values that each indicate a likelihood of a high-level behavior negatively impacting a performance characteristic or a battery consumption level of the computing device over time; means for identifying high-level behaviors that have a high probability of negatively impacting the performance characteristic or the battery consumption level of the computing device over time based on a comparison of the computed probability values to a predetermined threshold value; means for generating a first behavior vector after the comparison of the computed probability values to the predetermined threshold value, the generated first behavior vector including at least one value for each of the identified high-level behaviors that have the high probability; means for using a result of applying the generated first behavior vector to a classifier model to determine a number of lower-level device behaviors that are to be observed in the computing device, select the determined number of lower-level device behaviors for observation, and determine a level of detail for each of the selected lower-level device behaviors; and means for observing the determined number of selected lower-level device behaviors at their corresponding determined level of detail to collect behavior information. - View Dependent Claims (23, 24, 25, 26)
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Specification