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Andreea Georgescu

Publications and source records attributed to Andreea Georgescu.

5 recordsLinked to original sources

The Data Enclave Advantage: A New Paradigm for Least-Privileged Data Access in a Zero-Trust World

As cloud infrastructure evolves to support dynamic and distributed workflows, accelerated now by AI-driven processes, the outdated model of standing permissions has become a critical vulnerability. Based on the Cloud Security Alliance (CSA) Top Threats to Cloud Computing Deep Dive 2025 Report, our analysis details how standing permissions cause catastrophic cloud breaches. While current security tools are addressing network and API security, the challenge of securing granular data access remains. Removing standing permissions at the data level is as critical as it is at the network level, especially for companies handling valuable data at scale. In this white paper, we introduce an innovative architecture based on on-demand data enclaves to address this gap directly. Our approach enables Zero Standing Privilege (ZSP) and Just-in-Time (JIT) principles at the data level. We replace static permissions with temporary data contracts that enforce proactive protection. This means separation is built around the data requested on-demand, providing precise access and real time monitoring for individual records instead of datasets. This solution drastically reduces the attack surface, prevents privilege creep, and simplifies auditing, offering a vital path for enterprises to transition to a more secure and resilient data environment.

cs.CR

The Limits to Learning a Diffusion Model

This paper provides the first sample complexity lower bounds for the estimation of simple diffusion models, including the Bass model (used in modeling consumer adoption) and the SIR model (used in modeling epidemics). We show that one cannot hope to learn such models until quite late in the diffusion. Specifically, we show that the time required to collect a number of observations that exceeds our sample complexity lower bounds is large. For Bass models with low innovation rates, our results imply that one cannot hope to predict the eventual number of adopting customers until one is at least two-thirds of the way to the time at which the rate of new adopters is at its peak. In a similar vein, our results imply that in the case of an SIR model, one cannot hope to predict the eventual number of infections until one is approximately two-thirds of the way to the time at which the infection rate has peaked. This lower bound in estimation further translates into a lower bound in regret for decision-making in epidemic interventions. Our results formalize the challenge of accurate forecasting and highlight the importance of incorporating additional data sources. To this end, we analyze the benefit of a seroprevalence study in an epidemic, where we characterize the size of the study needed to improve SIR model estimation. Extensive empirical analyses on product adoption and epidemic data support our theoretical findings.

stat.ME

Extended Maximum Likelihood Halo-independent Analysis of Dark Matter Direct Detection Data

We extend and correct a recently proposed maximum-likelihood halo-independent method to analyze unbinned direct dark matter detection data. Instead of the recoil energy as independent variable we use the minimum speed a dark matter particle must have to impart a given recoil energy to a nucleus. This has the advantage of allowing us to apply the method to any type of target composition and interaction, e.g. with general momentum and velocity dependence, and with elastic or inelastic scattering. We prove the method and provide a rigorous statistical interpretation of the results. As first applications, we find that for dark matter particles with elastic spin-independent interactions and neutron to proton coupling ratio $f_n/f_p=-0.7$, the WIMP interpretation of the signal observed by CDMS-II-Si is compatible with the constraints imposed by all other experiments with null results. We also find a similar compatibility for exothermic inelastic spin-independent interactions with $f_n/f_p=-0.8$.

hep-ph

Reevaluation of spin-dependent WIMP-proton interactions as an explanation of the DAMA data

We reexamine the interpretation of the annual modulation signal observed by the DAMA experiment as due to WIMPs with a spin-dependent coupling mostly to protons. We consider both axial-vector and pseudo-scalar couplings, and elastic as well as endothermic and exothermic inelastic scattering. We conclude that the DAMA signal is in strong tension with null results of other direct detection experiments, particularly PICASSO and KIMS.

hep-ph

Direct Detection of Light "Ge-phobic" Exothermic Dark Matter

We present comparisons of direct dark matter (DM) detection data for light WIMPs with exothermic scattering with nuclei (exoDM), both assuming the Standard Halo Model (SHM) and in a halo model - independent manner. Exothermic interactions favor light targets, thus reducing the importance of upper limits derived from xenon targets, the most restrictive of which is at present the LUX limit. In our SHM analysis the CDMS-II-Si and CoGeNT regions become allowed by these bounds, however the recent SuperCDMS limit rejects both regions for exoDM with isospin-conserving couplings. An isospin-violating coupling of the exoDM, in particular one with a neutron to proton coupling ratio of $-0.8$ (which we call "Ge-phobic"), maximally reduces the DM coupling to germanium and allows the CDMS-II-Si region to become compatible with all bounds. This is also clearly shown in our halo-independent analysis.

hep-ph