AppIntent: analyzing sensitive data transmission in android for privacy leakage detection
By Zhemin Yang, Min Yang, Guofei Gu, Peng Ning, X. Wang. Conference on Computer and Communications Security, 2013
433 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems, Signal Processing
View Paper: https://www.semanticscholar.org/paper/9e1bcd6414fc6fdd3b63aab48cc3732dc761f538
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
- Bernt Schiele
- Marcus Rohrbach
- Mario Fritz
- Trevor Darrell
- Lisa Anne Hendricks
- Kate Saenko
- Zeynep Akata
- Devi Parikh
In Information Systems
- Davide Maiorca
- Giorgio Giacinto
- Giovanni Vigna
- Christopher Krügel
- Battista Biggio
- Yves Le Traon
- Jacques Klein
- Damien Octeau
In Signal Processing
- Giorgio Giacinto
- Davide Maiorca
- Battista Biggio
- Christopher Krügel
- Giovanni Vigna
- Mario Fritz
- Bernt Schiele
- Thorsten Holz
Citations in the corpus
- Static analysis of android apps: A systematic literature review (2017, methodology): “As an example, AppIntent [90] uses symbolic execution to generate a sequence of GUI manipulations that lead to data transmission.”
- Free for All! Assessing User Data Exposure to Advertising Libraries on Android (2016, background): “Those works mainly fall into three general categories: (1) static scanning [18], [17], [31], [5], [8], (2) dynamic monitoring [43], [52], [48], [14], and (3) hybrid techniques using both [33].”
- Obfuscation-Resilient Privacy Leak Detection for Mobile Apps Through Differential Analysis (2017, background): “AppIntent [48] proposes to distinguish between user-intended and covert data leaks and uses symbolic execution to determine if a privacy leak is a result of user interaction.”
- IoT Security: Ongoing Challenges and Research Opportunities (2014, background): “Deeper apps analysis such combining static and symbolic [18] is desirable.”
- Evaluating Analysis Tools for Android Apps: Status Quo and Robustness Against Obfuscation (2016, background): “AppIntent [60] X X X ded, Soot, JavaPathfinder DroidMiner [59] X X X AndroGuard AsDroid [24] X X X dex2jar, WALA”
- Towards a Visual Privacy Advisor: Understanding and Predicting Privacy Risks in Images (2017, positive): “[47] explore this case in Android applications.”
- ReCon: Revealing and Controlling PII Leaks in Mobile Network Traffic (2015, background): “tion) to determine a priori whether an app will leak privacy information [11, 16, 27, 44].”