Systematic Review on Various Techniques of Android Malware Detection

Dave, Dharmesh; Rathod, Digvijaysinh

doi:10.1007/978-3-031-10551-7_7

Cited by 4 publications

(2 citation statements)

References 75 publications

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“…Android malware analysis. There have been several systematic literature reviews about different aspects of Android malware detection techniques [16], [100], [17], [112], [112], [113], [114], [115], [116], [117], [118]. For instance, Senanayake et al [16] wrote about ML techniques in general, whereas Liue et al [100] and Qiu et al [112] focused on comparing deep learning detection techniques.…”

Section: Related Workmentioning

confidence: 99%

“…In addition, the paper analysed as well the used ML algorithms and compared their performance over the years on the Drebin dataset. Similarly, Dave and Rathod [115] reviewed articles from 2017 to 2020 and assessed which features were mainly used in previous studies and Acharya et al [118] studied malware articles with an emphasis on stealth techniques.…”

Section: Related Workmentioning

confidence: 99%

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Dynamic Security Analysis on Android: A Systematic Literature Review

Sutter,

Kehrer,

Rennhard

et al. 2024

IEEE Access

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Dynamic analysis is a technique that is used to fully understand the internals of a system at runtime. On Android, dynamic security analysis involves real-time assessment and active adaptation of an app's behaviour, and is used for various tasks, including network monitoring, system-call tracing, and taint analysis. The research on dynamic analysis has made significant progress in the past years. However, to the best of our knowledge, there is a lack in secondary studies that analyse the novel ideas and common limitations of current security research. The main aim of this work is to understand dynamic security analysis research on Android to present the current state of knowledge, highlight research gaps, and provide insights into the existing body of work in a structured and systematic manner. We conduct a systematic literature review (SLR) on dynamic security analysis for Android. The systematic review establishes a taxonomy, defines a classification scheme, and explores the impact of advanced Android app testing tools on security solutions in software engineering and security research. The study's key findings centre on tool usage, research objectives, constraints, and trends. Instrumentation and network monitoring tools play a crucial role, with research goals focused on app security, privacy, malware detection, and software testing automation. Identified limitations include code coverage constraints, security-related analysis obstacles, app selection adequacy, and non-deterministic behaviour. Our study results deepen the understanding of dynamic analysis in Android security research by an indepth review of 43 publications. The study highlights recurring limitations with automated testing tools and concerns about detecting or obstructing dynamic analysis.

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