OASIS: Optimizing Attacker Sequences for Hard-Label Black-Box Text Attacks
Different attack methods follow different search trajectories, they succeed on different subsets of samples, whereas existing hard-label black-box text attacks mainly focus on improving individual attackers or manually combining them. We present OASIS, a method for optimizing attacker sequences in hard-label black-box text attacks. OASIS first performs a one-time bi-objective attack chain search over candidate sequences to balance attack success rate and perturbation, and then reuses the selected fixed global chain during attack chain execution. Experiments across multiple datasets, victim models, and large language models show that OASIS consistently outperforms strong standalone baselin...
| Authors | Qian Chen, Shiliang Xiao, Yuzhi Liang |
|---|---|
| Primary category | cs.CR |
| Published | 30 August 2026 |
| Last updated at source | 1 September 2026 |
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