Concept

Data breach

Related publications (22)

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Boi Faltings, Ljubomir Rokvic, Panayiotis Danassis

Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...

2023

Learning from the Ethics of AI-A Research Proposal on Soft Law and Ethics of AI

This contribution outlines a research proposal combining ethical guidelines on AI and a law-as-data approach. Building upon the definitions of soft law discussed in legal scholarship, it proposes a way of structuring the regulatory landscape on AI and of a ...

UBIQUITY PRESS LTD2022

Privacy Laws and Value of Personal Data

Ilja Kantorovitch

We analyze how the adoption of the California Consumer Protection Act (CCPA), which limits buying or selling consumer data, heterogeneously affects firms with and without previously gathered data on consumers. Exploiting a novel and hand-collected data set ...

EPFL2022

Artificial intelligence across company borders

Olga Fink

Enabling effective cross-company AI without data disclosure. ...

2022

Safeguarding the IoT From Malware Epidemics: A Percolation Theory Approach

Ainur Zhaikhan

The upcoming Internet of Things (IoT) is foreseen to encompass massive numbers of connected devices, smart objects, and cyber-physical systems. Due to the large scale and massive deployment of devices, it is deemed infeasible to safeguard 100% of the devic ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Crypt4GH: a file format standard enabling native access to encrypted data

Juan Ramón Troncoso-Pastoriza

Motivation: The majority of genome analysis tools and pipelines require data to be decrypted for access. This potentially leaves sensitive genetic data exposed, either because the unencrypted data is not removed after analysis, or because the data leaves t ...

OXFORD UNIV PRESS2021

Private and Secure Distributed Learning

Georgios Damaskinos

The ever-growing number of edge devices (e.g., smartphones) and the exploding volume of sensitive data they produce, call for distributed machine learning techniques that are privacy-preserving. Given the increasing computing capabilities of modern edge de ...

EPFL2020

MedCo: Enabling Secure and Privacy-Preserving Exploration of Distributed Clinical and Genomic Data

Jean-Pierre Hubaux, Bryan Alexander Ford, Juan Ramón Troncoso-Pastoriza, Jean Louis Raisaro, Joao André Gomes de Sá e Sousa, Mickaël Misbach, Olivier Michielin

The increasing number of health-data breaches is creating a complicated environment for medical-data sharing and, consequently, for medical progress. Therefore, the development of new solutions that can reassure clinical sites by enabling privacy-preservin ...

2019

MedChain: Accountable and Auditable Data Sharing in Distributed Medical Scenarios

Jean-Pierre Hubaux, Bryan Alexander Ford, Juan Ramón Troncoso-Pastoriza, Linus Gasser, Jean Louis Raisaro

The current trend towards personalized medicine creates an urgent need to share data among different hospitals and health institutions, which endangers the privacy of the data subjects if not done with the appropriate precautions. Conversely, the frequency ...

2019

Privacy-Enhancing Technologies for Medical and Genomic Data: From Theory to Practice

Jean Louis Raisaro

The impressive technological advances in genomic analysis and the significant drop in the cost of genome sequencing are paving the way to a variety of revolutionary applications in modern healthcare. In particular, the increasing understanding of the human ...

EPFL2018

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