Launching a Robust Backdoor Attack under Capability Constrained Scenarios. (arXiv:2304.10985v1 [cs.CR])

As deep neural networks continue to be used in critical domains, concerns
over their security have emerged. Deep learning models are vulnerable to
backdoor attacks due to the lack of transparency. A poisoned backdoor model may
perform normally in routine environments, but exhibit malicious behavior when
the input contains a trigger. Current research on backdoor attacks focuses on
improving the stealthiness of triggers, and most approaches require strong
attacker capabilities, such as knowledge of the model structure or control over …

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