Rethinking the Reverse-engineering of Trojan Triggers

Neural Information Processing Systems 

Deep Neural Networks are vulnerable to Trojan (or backdoor) attacks. Reverse-engineering methods can reconstruct the trigger and thus identify affected models. Existing reverse-engineering methods only consider input space constraints, e.g.,

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