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Published in: Cluster Computing 1/2019

24-11-2017

Enhancing the accuracy of static analysis for detecting sensitive data leakage in Android by using dynamic analysis

Authors: Ly Hoang Tuan, Nguyen Tan Cam, Van-Hau Pham

Published in: Cluster Computing | Special Issue 1/2019

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Abstract

One approach of Android security is the analysis for detecting potential information leaks. The current technical analyses (as static analysis, dynamic analysis, hybrid of static and dynamic analysis) only focus on action within a single application, while the coordinated action of several applications for the malicious purpose is becoming popular. This study proposes a hybrid approach that combines static and dynamic analysis to detect information leak as a result of the coordinated action of multiple applications. In this text, we call it inter-application malware. The analysis takes place in two stages. The first stage uses static analysis to indicate the chains of sensitive actions on multiple applications. The second stage validates whether the chain of sensitive actions indeed leaks user’s data by using the dynamic analysis. In fact, the applications in question are forced to execute after the chains of sensitive actions detected in the first stage. The sensitive actions are monitored and analyzed to determine which actions are the causes of information leakage. And we have implemented an analysis tool, named eDSDroid. We have evaluated our tool on the famous Toyapps test case. The test result shows the correctness and effectiveness of our tool.

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Metadata
Title
Enhancing the accuracy of static analysis for detecting sensitive data leakage in Android by using dynamic analysis
Authors
Ly Hoang Tuan
Nguyen Tan Cam
Van-Hau Pham
Publication date
24-11-2017
Publisher
Springer US
Published in
Cluster Computing / Issue Special Issue 1/2019
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-1364-8

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