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

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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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Acknowledgements

This research is funded by Vietnam National University HoChiMinh City (VNU-HCM) under Grant Number B2016-26-01.

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Authors and Affiliations

  1. Information Security Lab, University of Information Technology, Vietnam National University, Ho Chi Minh City, Vietnam

    Ly Hoang Tuan, Nguyen Tan Cam & Van-Hau Pham

  2. Faculty of Science and Engineering, Hoa Sen University, Ho Chi Minh City, Vietnam

    Nguyen Tan Cam

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  1. Ly Hoang Tuan
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  2. Nguyen Tan Cam
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  3. Van-Hau Pham
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Correspondence to Ly Hoang Tuan.

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Tuan, L.H., Cam, N.T. & Pham, VH. Enhancing the accuracy of static analysis for detecting sensitive data leakage in Android by using dynamic analysis. Cluster Comput 22 (Suppl 1), 1079–1085 (2019). https://doi.org/10.1007/s10586-017-1364-8

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