Using normalized confidence values for classifying mobile device behaviors
First Claim
1. A method of analyzing behaviors in a computing device, comprising:
- receiving, in a processor of the computing device from a server computing device, a full classifier model and sigmoid parameters;
determining, via the processor, a normalized confidence value based on the received sigmoid parameters; and
classifying, via the processor, a device behavior of the computing device based on a combination of;
an analysis result generated by applying a behavior vector information structure to a lean classifier model; and
the normalized confidence value determined based on the received sigmoid parameters.
1 Assignment
0 Petitions
Accused Products
Abstract
Methods and systems for classifying mobile device behavior include generating a full classifier model that includes a finite state machine suitable for conversion into boosted decision stumps and/or which describes all or many of the features relevant to determining whether a mobile device behavior is benign or contributing to the mobile device'"'"'s degradation over time. A mobile device may receive the full classifier model along with sigmoid parameters and use the model to generate a full set of boosted decision stumps from which a more focused or lean classifier model is generated by culling the full set to a subset suitable for efficiently determining whether mobile device behavior are benign. Results of applying the focused or lean classifier model may be normalized using a sigmoid function, with the resulting normalized result used to determine whether the behavior is benign or non-benign.
220 Citations
30 Claims
-
1. A method of analyzing behaviors in a computing device, comprising:
-
receiving, in a processor of the computing device from a server computing device, a full classifier model and sigmoid parameters; determining, via the processor, a normalized confidence value based on the received sigmoid parameters; and classifying, via the processor, a device behavior of the computing device based on a combination of; an analysis result generated by applying a behavior vector information structure to a lean classifier model; and the normalized confidence value determined based on the received sigmoid parameters. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
-
-
9. A computing device, comprising:
-
means for receiving from a server computing device a full classifier model and sigmoid parameters; means for determining a normalized confidence value based on the received sigmoid parameters; and means for classifying a device behavior of the computing device based on a combination of; an analysis result generated by applying a behavior vector information structure to a lean classifier model; and the normalized confidence value determined based on the received sigmoid parameters. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
-
-
17. A computing device, comprising:
a processor configured with processor-executable instructions to; receive from a server computing device a full classifier model and sigmoid parameters; determine a normalized confidence value based on the received sigmoid parameters; and classify a device behavior of the computing device based on a combination of; an analysis result generated by applying a behavior vector information structure to a lean classifier model; and the normalized confidence value determined based on the received sigmoid parameters. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24)
-
25. A non-transitory computer readable storage medium having stored thereon processor-executable software instructions configured to cause a processor of a of a computing device to perform operations comprising:
-
receiving from a server computing device a full classifier model and sigmoid parameters; determining a normalized confidence value based on the received sigmoid parameters; and classifying a device behavior of the computing device based on a combination of; an analysis result generated by applying a behavior vector information structure to a lean classifier model; and the normalized confidence value determined based on the received sigmoid parameters the normalized confidence value. - View Dependent Claims (26, 27, 28, 29, 30)
-
Specification