COLLABORATIVE LEARNING FOR EFFICIENT BEHAVIORAL ANALYSIS IN NETWORKED MOBILE DEVICE
First Claim
1. A method of classifying mobile device behaviors of a mobile device, comprising:
- monitoring mobile device behaviors in a first mobile device to generate a behavior vector;
applying the behavior vector to a first classifier model in the first mobile device to obtain a first determination of whether a mobile device behavior is benign or not benign;
sending the behavior vector to a second mobile device, the second mobile device applying the behavior vector to a second classifier model to obtain a second determination of whether the mobile device behavior is benign or not benign and sending the second determination to the first mobile device;
collating the first determination and the second determination in the first mobile device to generate collated results; and
determining whether the mobile device behavior is benign or not benign based on the collated results.
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Accused Products
Abstract
Methods, systems and devices for classifying mobile device behaviors of a first mobile device may include the first mobile device monitoring mobile device behaviors to generate a behavior vector, and applying the behavior vector to a first classifier model to obtain a first determination of whether a mobile device behavior is benign or not benign. The first mobile device may also send the behavior vector to a second mobile device, which may receive and apply the behavior vector to a second classifier model to obtain a second determination of whether the mobile device behavior is benign or not benign. The second mobile device may send the second determination to the first mobile device, which may receive the second determination, collate the first determination and the second determination to generate collated results, and determine whether the mobile device behavior is benign or not benign based on the collated results.
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Citations
34 Claims
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1. A method of classifying mobile device behaviors of a mobile device, comprising:
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monitoring mobile device behaviors in a first mobile device to generate a behavior vector; applying the behavior vector to a first classifier model in the first mobile device to obtain a first determination of whether a mobile device behavior is benign or not benign; sending the behavior vector to a second mobile device, the second mobile device applying the behavior vector to a second classifier model to obtain a second determination of whether the mobile device behavior is benign or not benign and sending the second determination to the first mobile device; collating the first determination and the second determination in the first mobile device to generate collated results; and determining whether the mobile device behavior is benign or not benign based on the collated results. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A mobile device comprising:
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a processor; means for monitoring mobile device behaviors to generate a behavior vector; means for applying the behavior vector to a first classifier model to obtain a first determination of whether a mobile device behavior is benign or not benign; means for sending the behavior vector to a second mobile device; means for receiving a second determination of whether the mobile device behavior is benign or not benign from the second mobile device in response to sending the behavior vector to the second mobile device; means for collating the first determination and the second determination to generate collated results; and means for determining whether the mobile device behavior is benign or not benign based on the collated results. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A mobile computing device, comprising:
a processor configured with processor-executable instructions to perform operations comprising; monitoring mobile device behaviors to generate a behavior vector; applying the behavior vector to a first classifier model to obtain a first determination of whether a mobile device behavior is benign or not benign; sending the behavior vector to a second mobile device; receiving a second determination of whether the mobile device behavior is benign or not benign from the second mobile device in response to sending the behavior vector to the second mobile device; collating the first determination and the second determination to generate collated results; and determining whether the mobile device behavior is benign or not benign based on the collated results. - View Dependent Claims (14, 15, 16, 17, 18)
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19. A non-transitory computer readable storage medium having stored thereon processor-executable software instructions configured to cause a mobile device processor to perform operations comprising:
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monitoring mobile device behaviors to generate a behavior vector; applying the behavior vector to a first classifier model to obtain a first determination of whether a mobile device behavior is benign or not benign; sending the behavior vector to a second mobile device; receiving a second determination of whether the mobile device behavior is benign or not benign from the second mobile device in response to sending the behavior vector to the second mobile device; collating the first determination and the second determination to generate collated results; and determining whether the mobile device behavior is benign or not benign based on the collated results. - View Dependent Claims (20, 21, 22, 23, 24)
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25. A system comprising:
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a first mobile device; and a second mobile device, wherein the first mobile device comprises; a processor; means for monitoring mobile device behaviors to generate a behavior vector; means for applying the behavior vector to a first classifier model to obtain a first determination of whether a mobile device behavior is benign or not benign; and means for sending the behavior vector to the second mobile device; wherein the second mobile device comprises; means for receiving the behavior vector from the first mobile device; means for applying the behavior vector to a second classifier model to obtain a second determination of whether the mobile device behavior is benign or not benign; and means for sending the second determination of whether the mobile device behavior is benign or not benign to the first mobile device; wherein the first mobile device further comprises; means for collating the first determination and the second determination to generate collated results; and means for determining whether the mobile device behavior is benign or not benign based on the collated results. - View Dependent Claims (26, 27, 28, 29)
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30. A system, comprising:
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a first mobile device; and a second mobile device, wherein the first mobile device comprises; a first processor configured with processor-executable instructions to perform operations comprising; monitoring mobile device behaviors to generate a behavior vector; applying the behavior vector to a first classifier model to obtain a first determination of whether a mobile device behavior is benign or not benign; and sending the behavior vector to the second mobile device, wherein the second mobile device comprises; a second processor configured with processor-executable instructions to perform operations comprising; receiving the behavior vector from the first mobile device; applying the behavior vector to a second classifier model to obtain a second determination of whether the mobile device behavior is benign or not benign; and sending the second determination of whether the mobile device behavior is benign or not benign to the first mobile device, and wherein the first processor is configured with processor-executable instructions to perform operations further comprising; collating the first determination and the second determination to generate collated results; and determining whether the mobile device behavior is benign or not benign based on the collated results. - View Dependent Claims (31, 32, 33, 34)
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Specification