· 2014
FlowDroid
- 1,393citations
- 2014year
Short summary
FlowDroid precisely tracks data flow in Android apps to detect leaks, achieving 95% precision and 88% recall in tests, significantly outperforming prior methods.
AI-generated from the title and abstract; the full text is not read.
Key points
- FlowDroid offers a precise static taint-analysis for Android apps.
- It significantly reduces false alarms and missed leaks compared to existing approaches.
- Achieved 95% precision and 88% recall in detecting data leaks.
- Addresses the problem of careless and malicious apps leaking private smartphone data.
AI-generated from the title and abstract; the full text is not read.
Abstract
Today's smartphones are a ubiquitous source of private and confidential data. At the same time, smartphone users are plagued by carelessly programmed apps that leak important data by accident, and by malicious apps that exploit their given privileges to copy such data intentionally. While existing static taint-analysis approaches have the potential of detecting such data leaks ahead of time, all approaches for Android use a number of coarse-grain approximations that can yield high numbers of missed leaks and false alarms.
The authors' abstract, as published at the source., 2014 · DOI ↗
Continue with a free account
Ask the paper: 3 free questions a day about this paper; save it, get its citation, new summaries every day for your field. Takeaways are Premium.
Continue free on the webSign in with Google or Apple; no card needed. You come back to this paper.
On your phone:
Field: Signal Processing
Signal ProcessingComputer Science