Backdoor Attack on Deep Learning Models in Mobile Apps
Date: 2021-01-18
Affected: ML-based Android Apps
Attack vector: adversarial-input
Category: research
Severity: Critical

Deep learning models are increasingly used in mobile applications as critical components. Researchers from Microsoft Research demonstrated that many deep learning models deployed in mobile apps are vulnerable to backdoor attacks via "neural payload injection." They conducted an empirical study on real-world mobile deep learning apps collected from Google Play. They identified 54 apps that were vulnerable to attack, including popular security and safety critical applications used for cash recognition, parental control, face authentication, and financial services.


Mitigations:

Architectural layers (MAESTRO):