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Publications associées (24)

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The Privacy Power of Correlated Noise in Decentralized Learning

Rachid Guerraoui, Martin Jaggi, Youssef Allouah, Anastasiia Koloskova, Aymane El Firdoussi

Decentralized learning is appealing as it enables the scalable usage of large amounts of distributed data and resources (without resorting to any central entity), while promoting privacy since every user minimizes the direct exposure of their data. Yet, wi ...

PMLR2024

Building Strongly-Consistent Systems Resilient to Failures, Partitions, and Slowdowns

Cristina Basescu

Distributed systems designers typically strive to improve performance and preserve availability despite failures or attacks; but, when strong consistency is also needed, they encounter fundamental limitations. The bottleneck is in replica coordination, whi ...

EPFL2023

DIABLO: A Benchmark Suite for Blockchains

Rachid Guerraoui, Gauthier Jérôme Timothée Voron, Vincent Gramoli, Andrei Lebedev

With the recent advent of blockchains, we have witnessed a plethora of blockchain proposals. These proposals range from using work to using time, storage or stake in order to select blocks to be appended to the chain. As a drawback it makes it difficult fo ...

ASSOC COMPUTING MACHINERY2023

Scalable and Privacy-Preserving Federated Principal Component Analysis

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, Apostolos Pyrgelis, David Jules Froelicher, Joao André Gomes de Sá e Sousa, Jean-Philippe Léonard Bossuat

Principal component analysis (PCA) is an essential algorithm for dimensionality reduction in many data science domains. We address the problem of performing a federated PCA on private data distributed among multiple data providers while ensuring data confi ...

IEEE COMPUTER SOC2023

Health data privacy through homomorphic encryption and distributed ledger computing: an ethical-legal qualitative expert assessment study

Marcello Ienca

Background: Increasingly, hospitals and research institutes are developing technical solutions for sharing patient data in a privacy preserving manner. Two of these technical solutions are homomorphic encryption and distributed ledger technology. Homomorph ...

BMC2022

Toward Mobile Distributed Ledgers

Boi Faltings, Sujit Prakash Gujar, Dimitrios Chatzopoulos, Anurag Jain

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

The Universal Gossip Fighter

Rachid Guerraoui, Anne-Marie Kermarrec, Anastasiia Kucherenko, Rafaël Benjamin Pinot

The notion of adversary is a staple of distributed computing. An adversary typically models “hostile” assumptions about the underlying distributed environment, e.g., a network that can drop messages, an operating system that can delay processes or an attac ...

IEEE2022

CALYPSO: Private Data Management for Decentralized Ledgers

Bryan Alexander Ford, Linus Gasser, Eleftherios Kokoris Kogias, Philipp Svetolik Jovanovic, Enis Ceyhun Alp

Distributed ledgers provide high availability and integrity, making them a key enabler for practical and secure computation of distributed workloads among mutually distrustful parties. Many practical applications also require strong confidentiality, howeve ...

2021

Decentralising the patent system

Gaétan Jean A de Rassenfosse, Kyle William Higham

Modern patent systems are slow, inefficient, expensive, and may result in outcomes that actively harm technological progress. This paper proposes a substantive re-think of these systems and lays a foundation upon which practical solutions can be built. Man ...

ELSEVIER INC2021

Learning from History for Byzantine Robust Optimization

Martin Jaggi, Sai Praneeth Reddy Karimireddy, Lie He

Byzantine robustness has received significant attention recently given its importance for distributed and federated learning. In spite of this, we identify severe flaws in existing algorithms even when the data across the participants is identically distri ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

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Health data privacy through homomorphic encryption and distributed ledger computing: an ethical-legal qualitative expert assessment study

Marcello Ienca

BMC2022