Masahiro Kaneko · 2026 · arXiv
DOI: 10.48550/arXiv.2610.28045 · open-access PDF
为了防御神经网络的后门攻击,防御者必须识别确定输入是否是触发器的验证函数,而不是孤立地拒绝个别触发器,因为攻击者可以更快地生成满足同一个验证器的新的触发器,而不是阻止它们。
Machine translation (Meta M2M100); the English original follows.
To defend against backdoor attacks on neural networks, the defender must identify the verifier function that determines whether an input is a trigger, rather than rejecting individual triggers in isolation, since an attacker can generate new triggers satisfying the same verifier faster than they can be blocked. If a backdoor verifier could be installed with the asymmetry of a cryptographic authentication scheme, in which only the attacker can produce trigger inputs while the defender cannot reverse-engineer the verifier from observations, learning-based defense would be impossible in principle
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