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Publications associées (56)

The success of deep learning may be attributed in large part to remarkable growth in the size and complexity of deep neural networks. However, present learning systems raise significant efficiency concerns and privacy: (1) currently, training systems are l ...

EPFL2022

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

The COVID-19 pandemic created a noticeable challenge to the cryptographic community with the development of contact tracing applications. The media reported a dispute between designers proposing a centralized or a decentralized solution (namely, the PEPP-P ...

2020

We present the design and implementation of SafetyPin, a system for encrypted mobile-device backups. Like existing cloud-based mobile-backup systems, including those of Apple and Google, SafetyPin requires users to remember only a short PIN and defends aga ...

USENIX Association2020

SafetyPin: Encrypted Backups with Human-Memorable Secrets

Henry Nathaniel Corrigan-Gibbs

USENIX ASSOC2020

Walkman: A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization

Ali H. Sayed, Kun Yuan

This paper introduces a new algorithm for consensus optimization in a multi-agent network, where all agents collaboratively find a minimizer for the sum of their private functions. All decentralized algorithms rely on communications between adjacent nodes. ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Rethinking General-Purpose Decentralized Computing

Bryan Alexander Ford, Eleftherios Kokoris Kogias, Georgia Fragkouli, Enis Ceyhun Alp

While showing great promise, smart contracts are difficult to program correctly, as they need a deep understanding of cryptography and distributed algorithms, and offer limited functionality, as they have to be deterministic and cannot operate on secret da ...

ASSOC COMPUTING MACHINERY2019

On the Security of Two-Round Multi-Signatures

Bryan Alexander Ford, Manu Drijvers

A multi-signature scheme allows a group of signers to collaboratively sign a message, creating a single signature that convinces a verifier that every individual signer approved the message. The increased interest in technologies to decentralize trust has ...

IEEE COMPUTER SOC2019

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Data storage and retrieval systems, methods, and computer-readable media utilize a cryptographically verifiable data structure that facilitates verification of a transaction in a decentralized peer-to-peer environment using multi-hop backwards and forwards ...

2018

Decentralized machine learning is a promising emerging paradigm in view of global challenges of data ownership and privacy. We consider learning of linear classification and regression models, in the setting where the training data is decentralized over ma ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018

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