Challenges for Reliable and Large Scale Evaluation of Android Malware Analysis

Lalande, Jean-François; Tông, Valérie Viêt Triêm; Leslous, Mourad; Graux, Pierre

doi:10.1109/hpcs.2018.00173

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…Static analysis methods rely on employing several features such as application and user behaviors, resource consumption, network addresses, requested permissions, application code analysis, and system calls. This section summarizes recent published papers that have used one or more static [53] 2011-2016 3,000,000…”

Section: A Static Analysismentioning

confidence: 99%

Recent Advances in Android Mobile Malware Detection: A Systematic Literature Review

Alzubaidi¹

2021

IEEE Access

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In recent years, the global pervasiveness of smartphones has prompted the development of millions of free and commercially available applications. These applications allow users to perform various activities, such as communicating, gaming, and completing financial and educational tasks. These commonly used devices often store sensitive private information and, consequently, have been increasingly targeted by harmful malicious software. This paper focuses on the concepts and risks associated with malware, and reviews current approaches and mechanisms used to detect malware with respect to their methodology, associated datasets, and evaluation metrics.

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Section: A Static Analysismentioning

confidence: 99%

Recent Advances in Android Mobile Malware Detection: A Systematic Literature Review

Alzubaidi¹

2021

IEEE Access

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“…For solving this issue, most of authors rely on VirusTotal to decide if a sample is malicious or not. We believe that it is not a good idea, because the analysis tools used by VirusTotal has no reason to decide accurately [10], especially for recent samples.…”

Section: Designing An Experimentsmentioning

confidence: 99%

Android Malware Analysis: From Technical Difficulties to Scientific Challenges

Lalande

2019

Innovative Security Solutions for Information Technology and Communications

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Ten years ago, Google released the first version of its new operating system: Android. With an open market for third party applications, attackers started to develop malicious applications. Researchers started new works too. Inspired by previous techniques for Windows or GNU/Linux malware, a lot of papers introduced new ways of detecting, classifying, defeating Android malware. In this paper, we propose to explore the technical difficulties of experimenting with Android malware. These difficulties are encountered by researchers, each time they want to publish a solid experiment validating their approach. How to choose malware samples? How to process a large amount of malware? What happens if the experiment needs to execute dynamically a sample? The end of the paper presents the upcoming scientific challenges of the community interested in malware analysis.

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RmvDroid: Towards A Reliable Android Malware Dataset with App Metadata

Wang

et al. 2019

2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR)

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Challenges for Reliable and Large Scale Evaluation of Android Malware Analysis

Cited by 3 publications

References 16 publications

Recent Advances in Android Mobile Malware Detection: A Systematic Literature Review

Recent Advances in Android Mobile Malware Detection: A Systematic Literature Review

Android Malware Analysis: From Technical Difficulties to Scientific Challenges

RmvDroid: Towards A Reliable Android Malware Dataset with App Metadata

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