PermDroid: automatically testing permission-related behaviour of Android applications

Yang, Shuaihao; Zeng, Zigang; Song, Wei

doi:10.1145/3533767.3534221

Cited by 5 publications

(2 citation statements)

References 52 publications

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“…5.98% papers utilised some sort of similarity score [22] or rule based techniques [17] to analyse or detect Android malware. Lastly, 6.52% and 3.26% of the comprehensive studies used graph-based [185], [186], and some other techniques, respectively. For instance, in [31], the authors mapped the permissions on the x-y plane using their corresponding protection level, whereas in [45], they utilized app descriptions to deduce the permissions required by an application.…”

Section: Techniques Usedmentioning

confidence: 99%

“…Malware datasets used Smmarwar et al [167] CICInvesAndMal2019 Arif et al [168] AndroZoo, Drebin Manzanares et al [169] Drebin, AMD, VirusTotal, VirusShare Bhat et al [170] Virustotal, VirusShare, Drebin Elayan et al [171] CICAndMal2017 Syrris et al [172] Drebin Idrees et al [173] Contagiodump, Genome, Virus Total, theZoo, MalShare, VirusShare Rehman et al [174] M0DROID Martin et al [175] Koodous, AndroZoo Navarro et al [176] AndroZoo, [217] , VirusShare, AndroMalShare Milosevic et al [177] M0Droid Alzaylaee et al [178] McAfee Cai et al [179] AMD, Drebin Badhani et al [180] Andro-DumpSys, AndroZoo, Contagio , AndroMalShare , AMD, VirusTotal Hijawi et al [181] [218] Sheen et al [182] Genome Nisha et al [183] AndroZoo, VirusShare, Andro-MalShare, PRAGuard[226] Song et al [184] Not mentioned Zhang et al [185] Genome Yang et al [186] No malware Thiyagarajan et al [187] AndroZoo Qaisar et al [188] Android PRAGuard, Drebin, Open-source apps, Kharon, Androzoo, CICAAGM Appice et al [189] Alternative Chinese and Russian Markets, Android websites, malware forums, security blogs, Genome Zhu et al [190] VirusShare A. Altaher [191] Genome Su et al [192] Drebin, Genome, Contagio Mahindru et al [193] Genome , AndroMalShare, [218] Dehkordy et al [194] Drebin, AMD Nguyen et al [195] AMD, Drebin Taheri et al [196] Drebin, Contagio, Genome Mahesh et al [197] Private companies Firdaus et al [198] Drebin, Genome Shrivastava et al [199] Third-party applications Varsha et al [20...…”

Section: Related Workmentioning

confidence: 99%

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A comprehensive review on permissions-based Android malware detection

Sharma,

Arora

2024

Int. J. Inf. Secur.

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The first Android-ready "G1" phone debuted in late October 2008. Since then, the growth of Android malware has been explosive analogous to the rise in the popularity of Android. The major positive aspect of Android has been its open-source nature, which empowers app developers to expand their work. But at the same time, authors with malicious intentions pose grave threats to users. In the presence of such threats, Android malware detection is the need of an hour. Consequently, researchers have proposed various techniques involving static, dynamic, and hybrid analysis to address such threats using numerous features in the last decade. But the feature that most researchers have extensively used to perform malware analysis and detection in Android security is Android permission. Hence, to provide a clarified overview of the latest and past work done in Android malware analysis and detection, we perform a comprehensive literature review using permissions as a central feature or in combination with other components by collecting and analyzing 200 studies from January 2009 to February 2023. We extracted information such as the choice opted by researchers between analysis or detection, techniques used to select or rank the permissions feature set, features used along with permissions, detection models employed, the malware datasets used by researchers, and lastly, the limitations and challenges in the field of Android malware detection to propose some future research directions. Additionally, based on the information extracted, we answer the six research questions designed considering the above factors.

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Section: Techniques Usedmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A comprehensive review on permissions-based Android malware detection

Sharma,

Arora

2024

Int. J. Inf. Secur.

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A systematic mapping study for graphical user interface testing on mobile apps

Nie

Said²,

et al. 2023

IET Software

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Mobile apps with tested Graphical User Interface (GUI) tend to have higher downloads in the apps store. In recent years, few efforts were made to analyse the research community and research status of the literature for GUI testing on mobile apps, which brings an obstacle to characterise and understand this field. In this study, the authors propose a systematic mapping study to gain insights into the field. First, the authors conduct an extensive search of relevant literature over seven popular digital libraries. From 4427 candidate studies, 114 primary studies published between January 2011 and September 2022 were selected. Next, the authors analyse these primary studies from the perspectives of bibliometric and qualitative analysis. For the bibliometric analysis, first, the authors analyse the popular research topics and their relationships. Second, the authors study the authors' community. For the qualitative analysis, the authors analyse the objectives, approaches and evaluation metrics employed in these primary studies. Their investigation reports several major findings: (1) there are relatively more studies on two topics, that is, test case generation and the automated test; (2) the most productive authors tend to collaborate and often have relatively broad research interests; (3) the functionality is the main objective of GUI testing; the model-based approach is the most widely used.

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