The Velado Bound: A Geometric Lower Bound on Adversarial Detectability via Fisher-Rao Information Geometry

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Authors: Rafael Velado
Cited by: 0

Abstract

We prove a fundamental lower bound on adversarial perturbations in conservation-constrained probability systems. For states x, x' on the probability simplex S_n lying in different entropy bands, the product of Fisher-Rao geodesic distance D and semantic impact I satisfies D·I ≥ κ, where κ = (ΔH)²/M emerges from simplex geometry. The bound is derived via Cauchy-Schwarz inequality on the Fisher-Rao manifold and establishes a geometrically forbidden region where high-impact, low-detectability attacks cannot exist. We call this the Adversarial Uncertainty Principle. Empirical validation on H100 GPU confirms the forbidden quadrant {D0.5} remains empty across 10⁵ trials. Priority: U.S. Provisional Application No. 63/958,306, filed January 12, 2026.

Fields of Study & Subjects

Adversarial Robustness in Machine Learning Privacy-Preserving Technologies in Data Security and Verification in Computing

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
12 January 2026
Language
EN