Obfuscation-Resilient Privacy Leak Detection for Mobile Apps Through Differential Analysis
By Andrea Continella, Yanick Fratantonio, Martina Lindorfer, Alessandro Puccetti, Ali Zand, Christopher Krügel, Giovanni Vigna. 2017
135 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems, Safety, Robustness & Interpretability, Signal Processing
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
- Florian Tramèr
- Nicholas Carlini
- Eric Wallace
- Dawn Song
- Colin Raffel
- Luke S. Zettlemoyer
- Percy Liang
- Hannaneh Hajishirzi
In Information Systems
- Florian Tramèr
- Nicholas Carlini
- Matthew Jagielski
- Katherine Lee
- Alina Oprea
- Eric Wallace
- Dawn Song
- Ú. Erlingsson
In Safety, Robustness & Interpretability
- Florian Tramèr
- Nicholas Carlini
- Dawn Song
- Eric Wallace
- Matthew Jagielski
- Katherine Lee
- Colin Raffel
- Tom B. Brown
In Signal Processing
- Dawn Song
- Florian Tramèr
- Adam Roberts
- Nicholas Carlini
- Colin Raffel
- Tom B. Brown
- Eric Wallace
- Ú. Erlingsson
Citations in the corpus
- Extracting Training Data from Large Language Models (2020, background): “, by identifying and filtering personal information or content with restrictive terms of use [9, 54].”
- FlowPrint: Semi-Supervised Mobile-App Fingerprinting on Encrypted Network Traffic (2020, background): “[24] already observed this as a limitation when dealing with unknown traffic.”
- Security and Privacy Challenges of Large Language Models: A Survey (2024, unknown): “However, methods such as personal information or content identifying and filtering with restrictive terms of use can limit sensitive content [184], [185].”
- Enterprise data breach: causes, challenges, prevention, and future directions (2017, background): “For example, researchers recently leveraged differential analysis technique to achieve obfuscation resilient privacy leak detection on smartphone platforms.(64) String matching on encrypted data(65) has been one of the hot research areas in the last decade.”