https://hdl.handle.net/20.500.12761/1 2026-05-12T00:25:44Z 2026-05-12T00:25:44Z Arevalillo, Jorge M. Ramírez, Juan Marcos Díaz-Aranda, Sergio Aguilar, Jose Fernández Anta, Antonio Lillo, Rosa E. https://hdl.handle.net/20.500.12761/2034 2026-05-09T00:00:15Z 2026-07-01T00:00:00Z

Network Scale-up Methods on Aggregated Relational Data to Estimate the Outcome of Elections Arevalillo, Jorge M.; Ramírez, Juan Marcos; Díaz-Aranda, Sergio; Aguilar, Jose; Fernández Anta, Antonio; Lillo, Rosa E. The Network Scale-Up Method (NSUM) is an estimation framework that aims to determine the size of hidden or hard-to-reach populations from questions such as ``How many people do you know who belong to the target population?'' The information collected from these questions is commonly referred to as aggregated relational data (ARD), and the estimation of hidden population sizes using NSUM in ARD has been widely applied to key problems in sociology and public health. Note that this approach has been widely used to estimate the size of populations subject to legal or social restrictions, such as sex workers and drug users, who are typically excluded from the formal census. Although voting intention is not a social stigma, this information has become a privacy-sensitive issue, particularly in polarized political contexts, and thus poses a challenge to determining the share of party support. In this work, we introduce a methodology for estimating vote-intention shares using NSUM techniques on ARD. The methodology involves the design of the indirect survey to collect ARD regarding the voting intention of the survey participant's contacts, jointly with other control questions, the processing of the data with appropriate filters to eliminate outliers, the study of sample stratification strategies, and finally, the support share estimation for each political group by using different NSUM techniques. The methodology is applied to estimate voting outcomes in the 2023 Spanish general elections, using the Madrid, Andalusia, and Valencia regions as experimental scenarios. Overall, the resulting estimates \cambios{are competitive with} those published by leading private and public survey institutes, despite using a significantly smaller number of participants.

2026-07-01T00:00:00Z Gentile, Vincenzo Giustiniano, Domenico Frómeta Fonseca, Dayrene https://hdl.handle.net/20.500.12761/2033 2026-05-05T00:00:14Z 2026-06-16T00:00:00Z

Soil Moisture Sensing through Phase Measurements in Analog Backscatter Systems Gentile, Vincenzo; Giustiniano, Domenico; Frómeta Fonseca, Dayrene Conventional low-cost soil moisture sensors consume milliwatts of power, limiting their scalability for battery free agricultural IoT. To bridge this gap, we propose a narrow band phase-difference approach for soil moisture estimation using ultra-low-power analog backscatter at 868MHz. We develop a geometric electromagnetic model relating spatial phase shifts to soil permittivity, proving differential phase remains a valid observable despite refraction across the layered soil–air interface. We further characterize non-ideal hardware effects, establishing how antenna impedance mismatches and other impairments introduce systematic phase biases that require calibration. Our experiments demonstrate reliable discrimination between dry and wet soils, validating a battery-free sensing architecture that offers a scalable solution for sustainable water management.

2026-06-16T00:00:00Z Attiya, Hagit Fernández Anta, Antonio Milani, Alessia Rapetti, Alexandre Travers, Corentin https://hdl.handle.net/20.500.12761/2032 2026-05-01T00:00:18Z 2025-10-01T00:00:00Z

Auditable Shared Objects: From Registers to Synchronization Primitives Attiya, Hagit; Fernández Anta, Antonio; Milani, Alessia; Rapetti, Alexandre; Travers, Corentin Auditability allows to track operations performed on a shared object, recording who accessed which information. This gives data owners more control on their data. Initially studied in the context of single-writer registers, this work extends the notion of auditability to other shared objects, and studies their properties. We start by moving from single-writer to multi-writer registers, and provide an implementation of an auditable n-writer m-reader read / write register, with O(n+m) step complexity. This implementation uses (m+n)-sliding registers, which have consensus number m+n. We show that this consensus number is necessary. The implementation extends naturally to support an auditable load-linked / store-conditional (LL/SC) shared object. LL/SC is a primitive that supports efficient implementation of many shared objects. Finally, we relate auditable registers to other access control objects, by implementing an anti-flickering deny list from auditable registers.

2025-10-01T00:00:00Z Attiya, Hagit Fernández Anta, Antonio Milani, Alessia Rapetti, Alexandre Travers, Corentin https://hdl.handle.net/20.500.12761/2031 2026-05-01T00:00:14Z 2025-06-01T00:00:00Z

Auditing without Leaks Despite Curiosity Attiya, Hagit; Fernández Anta, Antonio; Milani, Alessia; Rapetti, Alexandre; Travers, Corentin Auditing data accesses helps preserve privacy and ensures accountability by allowing one to determine who accessed (potentially sensitive) information. A prior formal definition of register auditability was based on the values returned by read operations, without accounting for cases where a reader might learn a value without explicitly reading it or gain knowledge of data access without being an auditor. This paper introduces a refined definition of auditability that focuses on when a read operation is effective, rather than relying on its completion and return of a value. Furthermore, we formally specify the constraints that prevent readers from learning values they did not explicitly read or from auditing other readers' accesses. Our primary algorithmic contribution is a wait-free implementation of a multi-writer, multi-reader register that tracks effective reads while preventing unauthorized audits. The key challenge is ensuring that a read is auditable as soon as it becomes effective, which we achieve by combining value access and access logging into a single atomic operation. Another challenge is recording accesses without exposing them to readers, which we address using a simple encryption technique (one-time pad). We extend this implementation to an auditable max register that tracks the largest value ever written. The implementation deals with the additional challenge posed by the max register semantics, which allows readers to learn prior values without reading them. The max register, in turn, serves as the foundation for implementing an auditable snapshot object and, more generally, versioned types. These extensions maintain the strengthened notion of auditability, appropriately adapted from multi-writer, multi-reader registers.

2025-06-01T00:00:00Z