BARWM, a novel backdoor attack approach for real-world deep learning (DL) models deployed on mobile devices. Existing backdoor attacks often suffer from limitations such as altering the model structure or relying on easily detectable, sample-agnostic triggers. By utilizing DNN-based steganography to generate sample-specific backdoor triggers that are imperceptible, it is able to circumvent these limitations. […]
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