Publications associées à Securing Every Bit: Authenticated Broadcast in Radio Networks

Publications associées (29)

Teacher-Mediated and Student-Led Interaction with a Physics Simulation: Effects on the Learning Experience

Denis Gillet, Juan Carlos Farah, Jérémy Alain La Scala-Jayet

Computer simulations are often used as support material for science education, as they can engage students through inquiry-based learning, promote their active interaction in the experimentation phase, and help them visualize abstract concepts. For instanc ...

2024

On the Theory and Practice of Modern Secure Messaging

Daniel Patrick Collins

Billions of people now have conversations daily over the Internet. A large portion of this communication takes place via secure messaging protocols that offer "end-to-end encryption'" guarantees and resilience to compromise like the widely-used Double Ratc ...

EPFL2024

Traversing Time Dependent Light Fields for Daylight Glare Evaluation

Stephen William Wasilewski

To understand how daylight gives shape and life to architectural spaces, whether existing or imagined, requires quantifying its dynamism and energy. Maintaining these details presents a challenge to simulation and analysis methods that flatten data into di ...

EPFL2023

RaFSIP: Parameterizing ice multiplication in models using a machine learning approach

Athanasios Nenes, Paraskevi Georgakaki

Accurately representing mixed-phase clouds (MPCs) in global climate models (GCMs) is critical for capturing climate sensitivity and Arctic amplification. Secondary ice production (SIP), can significantly increase ice crystal number concentration (ICNC) in ...

2024

A Study on Gradient-based Meta-learning for Robust Deep Digital Twins

Olga Fink, Raffael Pascal Theiler, Michele Viscione

Deep-learning-based digital twins (DDT) are a promising tool for data-driven system health management because they can be trained directly on operational data. A major challenge for efficient training however is that industrial datasets remain unlabeled. T ...

Research Publishing2023

Byzantine-Resilient Learning Beyond Gradients: Distributing Evolutionary Search

Rachid Guerraoui, Matteo Monti, Andrei Kucharavy

Modern machine learning (ML) models are capable of impressive performances. However, their prowess is not due only to the improvements in their architecture and training algorithms but also to a drastic increase in computational power used to train them.|S ...

Assoc Computing Machinery2023

The DESI N-body Simulation Project - II. Suppressing sample variance with fast simulations

Cheng Zhao, Yu Yu, Andrei Variu

Dark Energy Spectroscopic Instrument (DESI) will construct a large and precise three-dimensional map of our Universe. The survey effective volume reaches similar to 20 h(-3) Gpc(3). It is a great challenge to prepare high-resolution simulations with a much ...

OXFORD UNIV PRESS2022

Toward Mobile Distributed Ledgers

Boi Faltings, Sujit Prakash Gujar

Advances in mobile computing have paved the way for new types of distributed applications that can be executed solely by mobile devices on Device-to-Device (D2D) ecosystems (e.g., crowdsensing). Sophisticated applications, like cryptocurrencies, need distr ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Electronic Structure of InAs and InSb Surfaces: Density Functional Theory and Angle-Resolved Photoemission Spectroscopy

Gabriel Aeppli

The electronic structure of surfaces plays a key role in the properties of quantum devices. However, surfaces are also the most challenging to simulate and engineer. Here, the electronic structure of InAs(001), InAs(111), and InSb(110) surfaces is studied ...

WILEY2022

A machine learning approach to correct for mass resolution effects in simulated halo clustering statistics

Cheng Zhao, Daniel Felipe Forero Sanchez

The increase in the observed volume in cosmological surveys imposes various challenges on simulation preparations. First, the volume of the simulations required increases proportionally to the observations. However, large-volume simulations are quickly bec ...

OXFORD UNIV PRESS2022

High-order geometric integrators for nonadiabatic molecular quantum dynamics and their applications to explore conical intersections

Seonghoon Choi

Accurate simulations of molecular quantum dynamics are crucial for understanding numerous natural processes and experimental results. Yet, such high-accuracy simulations are challenging even for relatively simple systems where the Born-Oppenheimer approxim ...

EPFL2022

Detrainment and braking of snow avalanches interacting with forests

Johan Alexandre Philippe Gaume, Xingyue Li

Mountain forests provide natural protection against avalanches. They can both prevent avalanche formation in release zones and reduce avalanche mobility in runout areas. Although the braking effect of forests has been previously explored through global sta ...

COPERNICUS GESELLSCHAFT MBH2022

Minimum Cost Intervention Design for Causal Effect Identification

Negar Kiyavash, Seyed Jalal Etesami, Sina Akbari

Pearl's do calculus is a complete axiomatic approach to learn the identifiable causal effects from observational data. When such an effect is not identifiable, it is necessary to perform a collection of often costly interventions in the system to learn the ...

PMLR2022

Simulation and experimental study of proton bunch self-modulation in plasma with linear density gradients

Ambrogio Fasoli, Sun Hee Kim, Ivo Furno, Patrick Blanchard, Yanis Andrebe, Riccardo Agnello, Alban Sublet, Falk Hans Braunmüller, Christine Stollberg

We present numerical simulations and experimental results of the self-modulation of a long proton bunch in a plasma with linear density gradients along the beam path. Simulation results agree with the experimental results reported [F. Braunmller, T. Nechae ...

2021

Planning for a Changing Climate without Accurate Predictions

Parag Rastogi, Mohammad Emtiyaz Khan

Simulation is an informative tool to plan the design and renovation of engineering systems, but its use requires accurate inputs from the users. Inputs such as the unknown future operating conditions might be expected in a system’s lifetime, e.g., the futu ...

Taylor & Francis Group2021

Increasing Superstructure Optimization Capacity Through Self-Learning Surrogate Models

François Maréchal, Ivan Daniel Kantor, Julia Granacher

Simulation-based optimization models are widely applied to find optimal operating conditions of processes. Often, computational challenges arise from model complexity, making the generation of reliable design solutions difficult. We propose an algorithm fo ...

2021

Over-the-Air Computation via Reconfigurable Intelligent Surface

Wei Chen, Yuning Jiang

Over-the-air computation (AirComp) is a disruptive technique for fast wireless data aggregation in Internet of Things (IoT) networks via exploiting the waveform superposition property of multiple-access channels. However, the performance of AirComp is bott ...

2021

Integrity and Metadata Protection in Data Retrieval

Kirill Nikitin

Secure retrieval of data requires integrity, confidentially, transparency, and metadata-privacy of the process. Existing protection mechanisms, however, provide only partially these properties: encryption schemes still expose cleartext metadata, protocols ...

EPFL2021

Networks of Coupled VO2 Oscillators for Neuromorphic Computing

Elisabetta Corti

Neuromorphic computing is a wide research field aimed to the realization of brain-inspired hardware, apt to tackle computation of unstructured data more efficiently than currently done with standard computational units. Oscillatory neural networks are know ...

EPFL2021

Exploring policy change through agent-based simulation

Raphaël Klein

Policymaking is a complex process that has been studied using policy process theories almost exclusively. These theories have been built using a large number of qualitative cases. Such methods are useful for theory building but remain limited for theory ex ...

EPFL2021