A Study of Android Application Security

By William Enck, Damien Octeau, Patrick Drew McDaniel, Swarat Chaudhuri. USENIX Security Symposium, 2011

1,070 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/78e5045f45fe1fd71cf7dad52ff214931f538cb0

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Citations in the corpus

Semantics-Aware Android Malware Classification Using Weighted Contextual API Dependency Graphs (2014, background): “Ded [14], CHEX [23], AppSealer [33], Capper [34], PEG [10], and FlowDroid [7] exercised static dataflow analysis to identify dangerous code in Android apps.”
Apposcopy: semantics-based detection of Android malware through static analysis (2014, background): “The work described in [18] performs various static analyses, including taint analysis, to better understand smartphone application security in over 1,000 popular Android apps.”
The Evolution of Android Malware and Android Analysis Techniques (2017, methodology): “Both PScout [Au et al. 2012] and AppSealer [Zhang and Yin 2013] use Soot directly on the dex, see Figure 3(a), to acquire Java bytecode, while [Enck et al. 2011] uses ded/DARE , and Pegasus created its own “translation tool” [Chen et al. 2013].”
Uranine: Real-time Privacy Leakage Monitoring without System Modification for Android (2015, background): “Static analysis systems [14, 2] fail on the real-time requirement—inputs from the user or from the remote server may affect what is sent out of the device and thus the leak may or may not be considered legitimate.”
RiskRanker: scalable and accurate zero-day android malware detection (2012, background): “[39] studied the 1100 top free apps from the official Android Market to understand their general security and privacy characteristics.”
Privacy Protection for Preventing Data Over-Collection in Smart City (2016, background): “Researcher have been studying mobile phone security for several years [2], [3], [4], especially malware [5], [6].”
AccelPrint: Imperfections of Accelerometers Make Smartphones Trackable (2014, background): “Nevertheless, research [28] shows that stealing of various IDs, such as the IMEI (device ID), IMSI (subscriber ID), or ICC-ID (SIM card serial number), is still rampant in apps.”
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].”
FM 99.9, Radio Virus: Exploiting FM Radio Broadcasts for Malware Deployment (2013, background): “ded is a dalvik decompiler [25] for dalvik classes.”
WHYPER: Towards Automating Risk Assessment of Mobile Applications (2013, background): “Recent work [7, 11] has shown that many applications leak geographic location and phone identiﬁers without the users knowledge.”
Analyzing inter-application communication in Android (2011, background): “Broadcast Receivers have the ability to set their priority level for receiving ordered broadcasts.”
Modeling Users' Mobile App Privacy Preferences: Restoring Usability in a Sea of Permission Settings (2014, background): “A great deal of past work analyzing smartphone apps has focused on developing useful techniques and tools to detect and manage leakage of sensitive personal information [8-10, 14-26] or studying how users react to these usages [6, 13, 27, 28].”
Unsafe exposure analysis of mobile in-app advertisements (2012, unknown): “[14]”
Reliable Third-Party Library Detection in Android and its Security Applications (2016, background): “A number of prior studies [10, 14, 4, 30, 34] has demonstrated that such libraries exhibit questionable privacy practices.”
Android permissions: a perspective combining risks and benefits (2012, methodology): “For example, a dataset of 311 apps was used in [7], 940 was used in [11], and 1,100 was used in [6].”
You Get Where You're Looking for: The Impact of Information Sources on Code Security (2016, background): “tion), and transmitting device and location in plaintext [14].”