arXiv subjects

Roman Müller

Publications and source records attributed to Roman Müller.

4 recordsLinked to original sources

arXiv2026

Agentic AI-Powered Re-Identification: An Emerging, Scalable Threat to Mobility Microdata Privacy

The widespread collection of fine-grained location data by commercial data brokers creates a re-identification risk that is not widely recognised by the public. While prior research has established that mobility traces are highly unique and that individuals can, in principle, be identified from a handful of spatio-temporal points, such attacks have historically required significant manual effort from skilled analysts, limiting their practical scale. In this feasibility study, we demonstrate in a real world setting that agentic AI fundamentally changes this threat model. We present an end-to-end pipeline in which large language model agents autonomously search the open web, cross-reference public records and social media, and resolve raw coordinate sequences to candidate identities - without human intervention. We evaluate the pipeline on a spatio-temporal dataset containing simulated location points anchored at and around true home and work addresses, focusing on a high-risk disclosure scenario. Our results demonstrate that, from spatio-temporal data and public sources alone, our agentic AI successfully re-identified 18 of the 25 re-identifiable individuals (72%) and 18 of 43 cases overall (41.9%). We discuss implications for Statistical Disclosure Control (SDC) practice and outline the near-future escalation that data custodians and regulators must anticipate. De facto anonymity - an implicit foundation of SDC practice - is shifting. Agentic AI strengthens the case that re-identification is reasonably likely by any means under the GDPR Recital-26 standard, at costs of minutes-and-dollars per target.

cs.CR↗

arXiv2026

RAPID: Risk of Attribute Prediction-Induced Disclosure in Synthetic Microdata

Statistical data anonymization increasingly relies on fully synthetic microdata, for which classical identity disclosure measures are less informative than an adversary's ability to infer sensitive attributes from released data. We introduce RAPID (Risk of Attribute Prediction--Induced Disclosure), a disclosure risk measure that directly quantifies inferential vulnerability under a realistic attack model. An adversary trains a predictive model solely on the released synthetic data and applies it to real individuals' quasi-identifiers. For continuous sensitive attributes, RAPID reports the proportion of records whose predicted values fall within a specified relative error tolerance. For categorical attributes, we propose a baseline-normalized confidence score that measures how much more confident the attacker is about the true class than would be expected from class prevalence alone, and we summarize risk as the fraction of records exceeding a policy-defined threshold. This construction yields an interpretable, bounded risk metric that is robust to class imbalance, independent of any specific synthesizer, and applicable with arbitrary learning algorithms. We illustrate threshold calibration, uncertainty quantification, and comparative evaluation of synthetic data generators using simulations and real data. Our results show that RAPID provides a practical, attacker-realistic upper bound on attribute-inference disclosure risk that complements existing utility diagnostics and disclosure control frameworks.

cs.LG↗

arXiv2025

Beyond the Trade-off Curve: Multivariate and Advanced Risk-Utility Maps for Evaluating Anonymized and Synthetic Data

Anonymizing microdata requires balancing the reduction of disclosure risk with the preservation of data utility. Traditional evaluations often rely on single measures or two-dimensional risk-utility (R-U) maps, but real-world assessments involve multiple, often correlated, indicators of both risk and utility. Pairwise comparisons of these measures can be inefficient and incomplete. We therefore systematically compare six visualization approaches for simultaneous evaluation of multiple risk and utility measures: heatmaps, dot plots, composite scatterplots, parallel coordinate plots, radial profile charts, and PCA-based biplots. We introduce blockwise PCA for composite scatterplots and joint PCA for biplots that simultaneously reveal method performance and measure interrelationships. Through systematic identification of Pareto-optimal methods in all approaches, we demonstrate how multivariate visualization supports a more informed selection of anonymization methods.

stat.AP↗

arXiv2022

A facility for radiation hardness studies based on a medical cyclotron

The development of instrumentation for operation in high-radiation environments represents a challenge in various research fields, particularly in particle physics experiments and space missions, and drives an ever-increasing demand for irradiation facilities dedicated to radiation hardness studies. Depending on the application, different needs arise in terms of particle type, energy and dose rate. In this article, we present a versatile installation based on a medical cyclotron located at the Bern University Hospital (Inselspital), which is used as a controlled 18-MeV proton source. This accelerator is used for daily production of medical radioisotopes, as well as for multidisciplinary research, thanks to a 6.5-meter long beam transfer line that terminates in an independent bunker, dedicated only to scientific activities. The facility offers a wide range of proton fluxes, due to an adjustable beam current from approximately 10 pA to the micro-ampere range, together with a series of steering and focusing magnets along the beamline that allow for the beam spot to be focused down to a few mm^2. The beamline can be instrumented with a variety of beam monitoring detectors, collimators, and beam current measurement devices to precisely control the irradiation conditions. The facility also hosts a well equipped laboratory dedicated to the characterisation of samples after irradiation. An experimental validation of the irradiation setup, with proton fluxes ranging from $5\times10^9$ cm$^{-2}$s$^{-1}$ to $4\times10^{11}$ cm$^{-2}$s$^{-1}$, is reported in this article.

physics.ins-det↗