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DroidDissection: A Hybrid Analysis Framework for Android Malware Detection and Analysis

ilker Kara1✉
1Department of Medical Services and Techniques, Eldivan Medical Services Vocational School Çankırı, Karatekin University
Received:Aug 3, 2025→Accepted:Sep 10, 2025→Published:September 17, 2025
DOI: 10.56038/ejrnd.v5i1.655
Vol. 5, No. 1
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A new framework called DroidDissection helps detect Android malware, particularly those targeting banking transactions, by combining static and dynamic analysis.

DroidDissection is a tool designed to identify Android malware, focusing on threats related to banking transactions. It combines two methods: analyzing the app's code and permissions before it runs, and observing its behavior while it's running. This hybrid approach was tested on a real malware sample and found to be more accurate than using either method alone.

Abstract

The Android operating system dominates the mobile ecosystem due to its flexibility, large application market, and open-source architecture. However, these same characteristics make Android an attractive platform for attackers who distribute malicious applications, particularly those designed to intercept banking transactions and steal confidential information. Existing security mechanisms mostly rely on either static or dynamic inspection, and these isolated techniques often fail to reveal concealed or runtime-triggered malicious behavior.

In this study, we present DroidDissection, a framework designed specifically for Android malware detection with an emphasis on banking-related threats. The framework combines static code and permission inspection with controlled dynamic execution, enabling deeper observation of behavior that only emerges during runtime. A real malware sample was examined to validate the approach. The experimental results show that the hybrid inspection strategy increases the accuracy of malware identification and helps uncover behaviors that traditional individual methods may overlook. These findings indicate that the proposed framework can strengthen defense mechanisms against evolving cyber threats targeting Android devices.

Keywords
Android Malware DetectionBanking MalwareHybrid AnalysisStatic and Dynamic AnalysisMobile SecurityCyber ThreatsThreat Intelligence

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Cite This Article
Kara, i. (2025). DroidDissection: A Hybrid Analysis Framework for Android Malware Detection and Analysis. *The European Journal of Research and Development*, 5(1), 130-148. https://doi.org/10.56038/ejrnd.v5i1.655

Bibliographic Info

JournalThe European Journal of Research and Development
Volume5
Issue1
Pages130–148
PublishedSeptember 17, 2025
eISSN2822-2296

Indexing & License

Open AccessCC BY 4.0CrossRef DOIORCIDOAI-PMH

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