4.5 Article

Android application behavioural analysis for data leakage

期刊

EXPERT SYSTEMS
卷 38, 期 1, 页码 -

出版社

WILEY
DOI: 10.1111/exsy.12468

关键词

android app analysis; android permission; data leakage assessment; machine learning; malware data analysis; reverse engineering

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An android application requires specific permissions to access resources, but malware apps can exploit this to access private data. A novel algorithm is proposed to detect malware based on permission patterns with around 90% efficiency.
An android application requires specific permissions from the user to access the system resources and perform required functionalities. Recently, the android market has experienced exponential growth, which leads to malware applications. These applications are purposefully developed by hackers to access private data of the users and adversely affect the application usability. A suitable tool to detect malware is urgently needed, as malware may harm the user. As both malware and clean applications require similar types of permissions, so it becomes a very challenging task to differentiate between them. A novel algorithm is proposed to identify the malware-based applications by probing the permission patterns. The proposed method uses the k-means algorithm to quarantine the malware application by obtaining permission clusters. An efficiency of 90% (approx.) is attained for malicious behaviour, which validates this work. This work substantiates the use of application permissions for potential applications in android malware detection.

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