A Study of the Attention Abnormality in Trojaned BERTsDownload PDF

Anonymous

16 Jan 2022 (modified: 05 May 2023)ACL ARR 2022 January Blind SubmissionReaders: Everyone
Abstract: Trojan attacks raise serious security concerns. In this paper, we investigate the underlying mechanism of Trojaned BERT models. We observe the attention focus drifting behavior of Trojaned models, i.e., when encountering an poisoned input, the trigger token hijacks the attention focus regardless of the context. We provide a thorough qualitative and quantitative analysis of this phenomenon, revealing insights into the Trojan mechanism. Based on the observation, we propose an attention-based Trojan detector to distinguish Trojaned models from clean ones. To the best of our knowledge, we are the first to analyze the Trojan mechanism and develop a Trojan detector based on the transformer's attention.
Paper Type: long
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