March 18, 2024, 4:11 a.m. | Ka-Ho Chow, Wenqi Wei, Lei Yu

cs.CR updates on arXiv.org arxiv.org

arXiv:2401.01085v2 Announce Type: replace
Abstract: Natural language processing (NLP) has received unprecedented attention. While advancements in NLP models have led to extensive research into their backdoor vulnerabilities, the potential for these advancements to introduce new backdoor threats remains unexplored. This paper proposes Imperio, which harnesses the language understanding capabilities of NLP models to enrich backdoor attacks. Imperio provides a new model control experience. Demonstrated through controlling image classifiers, it empowers the adversary to manipulate the victim model with arbitrary output …

arxiv attacks attention backdoor backdoor attacks capabilities control cs.cr cs.lg language led natural natural language natural language processing nlp research threats understanding unprecedented vulnerabilities

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