A novel backdoor attack approach named BARWM on real-world deep learning models deployed in mobile applications utilizes DNN-based steganography to generate imperceptible, sample-specific backdoor triggers, achieving high attack effectiveness and stealthiness.  The authors collected 38,387 mobile apps and extracted 89 real-world models to evaluate the effectiveness of BARWM, as compared to the baseline methods, BARWM … Continue reading Stealthy Backdoor Attacks: Android Apps Targeted with Steganography