Extracting Android Applications Data for Anomaly-based Malware Detection

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Extracting Android Applications Data for Anomaly-based Malware Detection

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Abstract

In order to apply any machine learning algorithm or classifier, it is fundamentally important to first and foremost collect relevant features. This is most important in the field of dynamic analysis approach to anomaly malware detection systems. In this approach, the behaviour patterns of applications while in execution are analysed. The behaviour features that Android as a system allows access permissions to depend on the type of device; either rooted or not. Android is based on the Linux kernel at the bottom layer, all layers on top of the kernel run without privileged mode. Thus, if a behaviour feature vector is created from features of Android (Application Programming Interface) API in unrooted mode, then only system information made available by Android can be used. In this paper, a Device Monitoring system for an unrooted device is developed and used to collect Android application data. The application data is used to build feature vectors that describes the Android application behaviour for Anomaly malware detection.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Waziri O.V., J. Aba, Abdullahi M.B, Ume U.A, Adewale O.S. 2015. "Extracting Android Applications Data for Anomaly-based Malware Detection". Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 15 (GJCST Volume 15 Issue E5).

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords
Classification
GJCST-E Classification C.1.3 D.4.6
Version of record

v1.2

Issue date
September 5, 2015

Language
English
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Extracting Android Applications Data for Anomaly-based Malware Detection

Waziri O.V.
Waziri O.V. University of Technology Minna
J. Aba
J. Aba <p>University of Technology Minna</p>
Abdullahi M.B
Abdullahi M.B <p>University of Technology Minna</p>
Ume U.A
Ume U.A <p>University of Technology Minna</p>
Adewale O.S
Adewale O.S <p>University of Technology Minna</p>