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Publications associées (32)

Assessment of the Electromagnetic Field Exposure due to 5G Base Stations using a Monte-Carlo Method: Initial Results

The realistic assessment of the Electromagnetic Field exposure due to wireless telecommunication base stations is critical to protect the population from harm due to excessive exposure, and allow wireless service providers to use the available technology i ...

IEEE2021

Drynx: Decentralized, Secure, Verifiable System for Statistical Queries and Machine Learning on Distributed Datasets

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, David Jules Froelicher, Joao André Gomes de Sá e Sousa

Data sharing has become of primary importance in many domains such as big-data analytics, economics and medical research, but remains difficult to achieve when the data are sensitive. In fact, sharing personal information requires individuals' unconditiona ...

2020

Encrypted DNS double right arrow Privacy? A Traffic Analysis Perspective

Carmela González Troncoso, Sandra Deepthy Siby, Narseo Vallina Rodriguez

Virtually every connection to an Internet service is preceded by a DNS lookup. Lookups are performed without any traffic-level protection, thus enabling manipulation, redirection, surveillance, and censorship. To address these issues, large organizations s ...

INTERNET SOC2020

Understanding and Mitigating Latency Variability of Latency-Critical Applications

Mia Primorac

A major theme of IT in the past decade has been the shift from on-premise hardware to cloud computing. Running a service in the public cloud is practical, because a large number of resources can be bought on-demand, but this shift comes with its own set of ...

EPFL2020

Estimation of regional trip length distributions for the calibration of the aggregated network traffic models

Nikolaos Geroliminis, Sérgio Filipe Assunção Batista

The calibration of trip lengths is an important challenge for multi-regional MFD-based applications, as it can influence the dynamics of regional densities (and speeds). Existing research has not paid significant attention in the topic, giving opportunitie ...

PERGAMON-ELSEVIER SCIENCE LTD2019

Inferring Accurate Bus Trajectories from Noisy Estimated Arrival Time Records

Lakmal Buddika Meegahapola

Urban commuting data has long been a vital source of understanding population mobility behaviour and has been widely adopted for various applications such as transport infrastructure planning and urban anomaly detection. While individual-specific transacti ...

IEEE2019

Multi-Objective System-Level Management of Modern Green Data Centers

Ali Pahlevan

In our modern society, the average citizen has turned into a daily cloud user. Despite being virtually transparent for the user, internet services require data centers behind the scenes. Data centers burn several megawatts of power and their electricity bi ...

EPFL2019

Traffic Receipts for Network Transparency

Pavlos Nikolopoulos

Today's Internet is not transparent: when packets get lost or delayed, there is typically no information about where the problem occurred, hence no information about who is responsible. This results in Internet service providers (ISPs) offering service lev ...

EPFL2018

Information Gathering with Peers: Submodular Optimization with Peer-Prediction Constraints

Boi Faltings, Andreas Krause, Goran Radanovic

We study a problem of optimal information gathering from multiple data providers that need to be incentivized to provide accurate information. This problem arises in many real world applications that rely on crowdsourced data sets, but where the process of ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2018

Network Neutrality Inference using Network Tomography

Ovidiu Sebastian Mara

Our work studies network neutrality, a property of communication networks which means that they treat all traffic the same, regardless of application, content provider or communication protocol. This is an important problem, because sometimes users suspect ...

EPFL2018

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