Broad and Efficient PII Detection with Unified Labels
A unified-label PII detection framework targets low false-positive rates at scale — directly applicable to GDPR data-flow scanning in high-throughput European enterprise environments.
Summary written by editorial AI · Source link below
arXiv:2610.22597v1 Announce Type: cross Abstract: Personally Identifiable Information (PII) detection models must efficiently find identifiers across diverse contexts while maintaining a low false-positive rate (FPR) on high-volume traffic. Recent detectors increasingly rely on complex architectures that raise deployment cost, yet many are fine-tuned on only a few synthetic datasets that limit their coverage. Combining public datasets is challenging because their taxonomies differ, and even aft
Editorial Analysis
High false-positive rates in PII detection tools create alert fatigue and compliance gaps; a more accurate unified approach could improve both efficiency and GDPR adherence.
Benchmark this unified-label PII detector against your existing DLP tooling to assess accuracy improvements on European data types.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
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