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papersTODAY 04:00 UTC

Study Reexamines How Effective Targeted Data Poisoning Attacks Really Are

A new arXiv paper argues that common evaluations of targeted data poisoning attacks are misleading because they average success rates across randomly chosen test targets, which masks worst-case outcomes. The author(s) suggest that this averaging can overstate or understate the practical threat depending on the specific samples an adversary cares about. The work calls for evaluation protocols that account for per-target variation rather than relying on aggregate scores.

arXivAdversarial machine learningai-securitydata poisoningmodel evaluation

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