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

Volume 14, Number 5, May 2018, pp. 1014-1022
DOI: 10.23940/ijpe.18.05.p20.10141022

Zhenliu Zhoua, Xiaoming Zhoub, Weichun Geb, Yueming Panc, and Yu Guc

aShenyang Key Laboratory of Information Security for Power System, Shenyang Institute of Engineering, Shenyang, 110136, China
bState Grid Liaoning Electric Power Co., Ltd, Shenyang, 110004, China
cState Grid Liaoning Electric Power Co., Ltd, Jinzhou, 121000, China

(Submitted on February 21, 2018; Revised on March 26, 2018; Accepted on April 29, 2018)


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.


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