TaintDroid

By William Enck, P. Gilbert, Byung-Gon Chun, Landon P. Cox, Jaeyeon Jung, Patrick Drew McDaniel, Anmol Sheth. USENIX Symposium on Operating Systems Design and Implementation, 2010

2,871 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Signal Processing

View Paper: https://www.semanticscholar.org/paper/f7c69271951842a2be9f3126d2ef16ce949df58f

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Citations in the corpus

Following Devil's Footprints: Cross-Platform Analysis of Potentially Harmful Libraries on Android and iOS (2016, background): “A lot of effort has been made to analyze and detect Android PHAs, most of which aims at detecting the code [37], [38], [39], [40], [41], [42], [43], [44], [45] for performing potentially harmful behaviors (e.”
Unsafe exposure analysis of mobile in-app advertisements (2012, background): “TaintDroid [13] takes a different tack to expose and identify privacy leaks in apps as a whole.”
Privacy in the Internet of Things: threats and challenges (2014, background): “Extensive privacy research has been conducted focussing mostly on location-based services [52, 53, 54], detection of privacy breaches [55, 56] and privacy aware architectures for participatory sensing [57, 58].”
Towards Statistical Queries over Distributed Private User Data (2012, background): “But often users are unaware that their data is being exposed, for instance by third party trackers [34] or smart phone applications [19].”
Significant Permission Identification for Machine-Learning-Based Android Malware Detection (2018, methodology): “For example, TAINTDROID [8] dynamically tracks multiple sensitive data source simultaneously using tainting analysis.”
MockDroid: trading privacy for application functionality on smartphones (2011, methodology): “communication along with permission to access either location, camera or audio data [6].”
ANDRUBIS -- 1,000,000 Apps Later: A View on Current Android Malware Behaviors (2014, background): “TaintDroid [28] was the first work to propose taint tracking for monitoring data flow dependencies and data leakage in Android apps and is now at the core of many sandboxes, such as ours, to track data leaks.”
Amandroid: A Precise and General Inter-component Data Flow Analysis Framework for Security Vetting of Android Apps (2014, background): “TaintDroid [12] is a dynamic (runtime) taint-tracking and analysis system to find potential misuse of the user’s private information.”
Enabling Fine-Grained Permissions for Augmented Reality Applications with Recognizers (2013, methodology): “Once an application obtains access to sensors, information flow control approaches can be used to control or monitor an application’s usage of the sensitive data as in TaintDroid [10] and AppFence [14].”
Why eve and mallory love android: an analysis of android SSL (in)security (2012, background): “introduced TaintDroid [7] to track privacy-related information flows to discover such (semi-)malicious apps.”
Checking app behavior against app descriptions (2014, background): “The TAINTDROID system [6] tracks dynamic information flow within Android apps and thus can detect usages of sensitive information.”
Systematic Detection of Capability Leaks in Stock Android Smartphones (2012, background): “The type and the volume of information kept in the phone naturally lead to various concerns [13, 14, 27, 42] about the safety of this private information, including the way it is managed and accessed.”
Android permissions: a perspective combining risks and benefits (2012, methodology): “[5] perform dynamic taint tracking of data in Android, and reveal to a user when an application may be trying to send sensitive data off the phone.”
Apposcopy: semantics-based detection of Android malware through static analysis (2014, background): “For example, TaintDroid [17] and VetDroid [37] are dynamic taint analyses that track information flow by instrumenting the Dalvik VM, and examples of static taint analyses include [20, 21, 23, 16].”
ReCon: Revealing and Controlling PII Leaks in Mobile Network Traffic (2015, background): “Likewise, custom Android extensions that are often integrated in dynamic analysis tools provide control over network ﬂows but measurement visibility is limited to the devices running these custom OSes or apps [24], often requiring warranty-voiding “jailbreaking.””
Droid-Sec (2014, background): “DroidBox is a kind of sandbox that is developed based on TaintDroid [2].”