A survey of mobile malware in the wild

By Adrienne Porter Felt, Matthew Finifter, Erika Chin, Steve Hanna, David A. Wagner. Security and Privacy in Smartphones and Mobile Devices, 2011

883 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/b444e56f31694b3ba4b14f91b4b3d1a8ebc19830

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Citations in the corpus

A Survey on Security for Mobile Devices (2013, background): “For a complete list of mobile malware in the period 2000-2008 see [14]; see [15] for mobile malware that spread from January 2009 to June 2011.”
The Evolution of Android Malware and Android Analysis Techniques (2017, methodology): “As the manifest is easy to obtain statically, many frameworks, such as PScout [Au et al. 2012], Whyper [Pandita et al. 2013], and [Felt et al. 2011; Wei et al. 2012a], use static analysis to evaluate the risks of the Android permission system and individual apps.”
Measuring user confidence in smartphone security and privacy (2012, background): “Although there have been few samples of iPhone malware, there is plenty of grayware and jailbreaking applications [23].”
DroidDetector: Android Malware Characterization and Detection Using Deep Learning (2016, background): “However, the openness of Android makes these markets hot targets for malware attacks [2, 3] and causes countless instances of malware being hidden behind a large number of benign apps that seriously threatens users’ security and privacy.”
Information Flow Analysis of Android Applications in DroidSafe (2015, background): “Sensitive information leaks, as implemented by malicious or misused code (such as advertising libraries) in Android applications, constitute one of the most prominent security threats to the Android ecosystem [1, 2].”
MARVIN: Efficient and Comprehensive Mobile App Classification through Static and Dynamic Analysis (2015, methodology): “[27] also determined that those three permissions were characteristic of malware.”
WHYPER: Towards Automating Risk Assessment of Mobile Applications (2013, background): “Previous work has looked at permissions [2–5], code [6–10], and run-time behavior [11–13].”
Mobile-sandbox: having a deeper look into android applications (2013, background): “[8], mobile applications pose the following three types of threats – Malware, Personal Spyware and Grayware.”
Vetting undesirable behaviors in android apps with permission use analysis (2013, background): “A survey on current Android malware characteristics was presented in [59] and [29].”
FM 99.9, Radio Virus: Exploiting FM Radio Broadcasts for Malware Deployment (2013, background): “While a significant research effort has been put to limit the effect of malicious mobile applications (in Android, as well as for other systems for mobile devices [28], [33]), little effort has been concentrated on investigating actual attack vectors.”
I've got 99 problems, but vibration ain't one: a survey of smartphone users' concerns (2012, background): “We then asked 41 smartphone users to discuss the risks in their own words; their responses con.rmed that people .nd the lowest-ranked risks merely annoying but might seek legal or .nancial retribution for the highest-ranked risks.”
FlowDroid: precise context, flow, field, object-sensitive and lifecycle-aware taint analysis for Android apps (2014, background): “classified different kinds of Android malware [12] and found that one of the main threats posed by malicious Android applications are privacy violations which leak sensitive information such as location information, contact data, pictures, SMS messages, etc.”
IccTA: Detecting Inter-Component Privacy Leaks in Android Apps (2015, background): “Except privacy leaks detection, there has been a rich body of work on other Android security issues [9], [12], [18], [20], [23], [51] such as energy bugs [15], [32] and SSL”
Structural detection of android malware using embedded call graphs (2013, neutral): “[15] and Zhou and Jiang [43].”
A measurement study of google play (2014, background): “Much work has focused on the security of Android applications and the presence of malware in Google Play, but this work has focused on possible compromises of user data and privacy on the Android devices themselves [20, 22, 25, 44].”
Amandroid: A Precise and General Inter-component Data Flow Analysis Framework for Security Vetting of Android Apps (2014, background): “However, there have been widely reported security problems due to malicious or vulnerable applications running on Android devices [15, 19, 34, 36, 37].”
Hey, You, Get Off of My Market: Detecting Malicious Apps in Official and Alternative Android Markets (2012, background): “Malware detection onmobile devices The second area of related work includes systems [29, 30, 33, 43, 45, 49, 52] to detect malware on mobile devices.”
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources (2020, neutral): “growth and increasing sophistication of Android malware call for new defensive techniques that are capable of protecting mobile users against novel threats [132].”