Abstract: A method for processing user interaction information by an electronic device, includes: executing an application in an unsecure area of the electronic device; instantiating an object of the application; recognizing a user interface of the application, converting a user reaction between a pseudo-event and the instantiated object into data, and transmitting the data to a secure area of the electronic device; mirroring the application to the secure area by using the data; based on a user input being detected, inferring an event to be recognized by a graphical user interface (GUI) framework of the electronic device; and interpreting, in the secure area, the user reaction to the instantiated object corresponding to the inferred event

Abstract: According to an embodiment of the disclosure, an electronic device includes a processor and a memory operationally connected to the processor and configured to store instructions that, when executed by the processor, cause the processor to configure a time period comprising multiple unit durations, check for utilization of the processor for each of the multiple unit durations of the time period, collect at least one variation of the utilization of the processor based on the utilization of the processor for each of the multiple unit durations, acquire a temporal probability density function based on the at least one collected variation, determine a probability density function corresponding to the temporal probability density function based on a previously stored probability density function table, and determine an operating frequency for a next unit duration based on at least part of the identified probability density function. Various other embodiments are possible.

Abstract: According to an embodiment of the disclosure, an electronic device includes a processor and a memory operationally connected to the processor and configured to store instructions that, when executed by the processor, cause the processor to configure a time period comprising multiple unit durations, check for utilization of the processor for each of the multiple unit durations of the time period, collect at least one variation of the utilization of the processor based on the utilization of the processor for each of the multiple unit durations, acquire a temporal probability density function based on the at least one collected variation, determine a probability density function corresponding to the temporal probability density function based on a previously stored probability density function table, and determine an operating frequency for a next unit duration based on at least part of the identified probability density function. Various other embodiments are possible.