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政大典藏 > College of Commerce > Department of MIS > Periodical Articles > Item 140.119/129122

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/129122

Title:	AppBeach: A Static Behavior Checker for iOS Mobile Applications
Authors:	郁方* Yu, Fang Tai, Steven Shao, Tang-Wei Wang, Wei-Ren
Contributors:	資管系
Date:	2015-04
Issue Date:	2020-03-06 10:50:54 (UTC+8)
Abstract:	AppBeach standing on App Behavior Checker is a new service to reconstruct and report behaviors of iOS mobile applications, using static binary analysis to reveal embedded functions within the executables. AppBeach adopts a distributed algorithm on call sequence counting via the hadoop framework, achieving a scalable static syntax analysis on executables of modern apps. The main idea is syntactically counting call sequences that are embedded in iOS executable. This is done by distributing routines to mappers with the assembly tool that resolves explicit and implicit system method calls that are embedded in the iOS executables. The reducer then collects the counting from mappers to characterize the behaviors of apps. We learn patterns of malicious behaviors from the difference of pairs of normal and malicious apps, and report the probability of potential behaviors of commercial apps by matching these patterns to their call sequence counts.
Relation:	Communications of the CCISA, Vol.21, No.2, pp.41-51
Data Type:	article
Appears in Collections:	[Department of MIS] Periodical Articles

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