A Method of Dynamically Associating Behavior Risks based on Time Thread in Smartphones

doi:10.23940/ijpe.18.05.p20.10141022

Abstract

Abstract:

Behavior associated risks are analyzed and detected based on a series of software behaviors and user behaviors in a smartphone. Based on time threads, a method of dynamically associating and analyzing risks of behaviors is proposed. According to the time sequence of the behavior occurrence, the behaviors are organized into a behavior associated graph with time threads. Associated analysis and detection of risks among behaviors are achieved through matching association rules. The advantage of this method is that it cannot only realize dynamic analysis while behavior occurs, but can also realize static postmortem analysis using collected data sets. The dynamic association of behavior risk based on time thread improves behavior risk analysis and realizes the real-time risk detection in smartphones. Formalized definitions of behavior and behavior associated graphs are presented. Algorithms of behavior risk associating are described, and the results of the experimental analysis are given.

Submitted on February 21, 2018; Revised on March 26, 2018; Accepted on April 29, 2018
References: 17

Zhenliu Zhou, Xiaoming Zhou, Weichun Ge, Yueming Pan, and Yu Gu. A Method of Dynamically Associating Behavior Risks based on Time Thread in Smartphones [J]. Int J Performability Eng, 2018, 14(5): 1014-1022.

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References 0

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