Information Flow Analysis of Android Applications in DroidSafe
By Michael I. Gordon, Deokhwan Kim, Jeff H. Perkins, Limei Gilham, Nguyen Nguyen, Martin C. Rinard. Network and Distributed System Security Symposium, 2015
533 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Networks and Communications, Signal Processing
View Paper: https://www.semanticscholar.org/paper/5aec33d09e7d8fcee795c2ce6b70cab89665c519
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Giorgio Giacinto
- Davide Maiorca
- Michael Backes
- Sven Bugiel
- Damien Octeau
- Thorsten Holz
- Patrick Traynor
- William Enck
In Computer Networks and Communications
- Giorgio Giacinto
- Davide Maiorca
- Sven Bugiel
- Thorsten Holz
- Michael Backes
- Patrick Traynor
- William Enck
- Evangelos P. Markatos
In Signal Processing
- Giorgio Giacinto
- Davide Maiorca
- Sven Bugiel
- Damien Octeau
- Xinming Ou
- Fengguo Wei
- Sankardas Roy
- Robby
Citations in the corpus
- Reliable Third-Party Library Detection in Android and its Security Applications (2016, background): “For instance, a wide range of security-related analyses studied apps for privacy and security issues and raised awareness for various problem areas, including privacy leaks [12, 2, 42, 13, 3], permission usage [43], dynamic code loading [28], SSL/TLS”
- *droid (2016, methodology): “This ultimately leads to tools like FlowDroid [Fritz et al. 2014], Amandroid [Wei et al. 2014], and DroidSafe [Gordon et al. 2015], which are precise but not necessarily scalable to large, complex applications or will not run on standard desktop hardware.”
- MaMaDroid: Detecting Android Malware by Building Markov Chains of Behavioral Models (2016, background): “Due to its popularity, cyber-criminals have increasingly targeted this ecosystem [17], as malware running on mobile devices can be particularly lucrative – e.g., allowing attackers to defeat two factor authentication [51], [53] or trigger leakage of sensitive information [27].”
- Amandroid: A Precise and General Inter-component Data Flow Analysis Framework for Security Vetting of Android Apps (2014, methodology): “We then experimentally compare Amandroid with two state-of-the-art static analyzers for Android apps: IccTA [34] and DroidSafe [26], and show that Amandroid can address a wider range of security problems due to inter-component communications.”
- The Long-Standing Privacy Debate: Mobile Websites vs Mobile Apps (2017, background): “Towards a different direction, in [21] Gordon et al.”
- Static analysis of android apps: A systematic literature review (2017, background): “Amandroid [68] 3 3 3 3 DroidSafe [58] 3 3 3 3”
- Evaluating Analysis Tools for Android Apps: Status Quo and Robustness Against Obfuscation (2016, background): “DroidSafe [20] improves the analysis of the static source-”
- Following Devil's Footprints: Cross-Platform Analysis of Potentially Harmful Libraries on Android and iOS (2016, background): “…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.g., stealing the user’s sensitive information), and protecting the Android system from various…”