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Quantifying and Prioritizing Stealthy Source-Manipulation Threats Against Multi-Source Anomaly Detectors

Chebolu, Indraveni et al.
arXiv (All) · Papers
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cryptography-and-securitymachine-learning
Security pipelines often fuse several data sources and protect a downstream model with a cross-source anomaly detector. Such detectors are usually judged by their clean false-positive rate and by how well they catch random corruption. Neither metric captures an adversary who controls some sources an
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