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Action-Manipulation Attacks Against Stochastic Bandits: Attacks and Defense
[article]
2020
arXiv
pre-print
Due to the broad range of applications of stochastic multi-armed bandit model, understanding the effects of adversarial attacks and designing bandit algorithms robust to attacks are essential for the safe applications of this model. In this paper, we introduce a new class of attack named action-manipulation attack. In this attack, an adversary can change the action signal selected by the user. We show that without knowledge of mean rewards of arms, our proposed attack can manipulate Upper
arXiv:2002.08000v2
fatcat:ywgcxdifwnck3mpxxjsln5zsk4