Robust and Transferable Backdoor Attacks Against Deep Image Compression
With Selective Frequency Prior
Robust and Transferable Backdoor Attacks Against Deep Image Compression
With Selective Frequency Prior
Recent advancements in deep learning-based compression techniques have surpassed traditional methods. However, deep neural networks remain vulnerable to backdoor attacks, where pre-defined triggers induce malicious behaviors. This paper introduces a novel frequency-based trigger injection model for launching backdoor attacks with multiple triggers on learned image compression models. Inspired by the …