SOURCE-LINKED INTELLIGENCE

OASIS: Optimizing Attacker Sequences for Hard-Label Black-Box Text Attacks

arXiv · AI, language, vision and robotics · article · Aug 30, 2026 · UTC

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 mod

Read original source ↗ Open in workspace

recordType

paper

region

Global