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 ...
2023Learning 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 LTD2022Privacy Laws and Value of Personal Data
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 ...
EPFL2022Artificial intelligence across company borders
Enabling effective cross-company AI without data disclosure. ...
2022Safeguarding the IoT From Malware Epidemics: A Percolation Theory Approach
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 INC2021Crypt4GH: a file format standard enabling native access to encrypted data
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 PRESS2021Private and Secure Distributed Learning
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 ...
EPFL2020MedCo: 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 ...
2019Privacy-Enhancing Technologies for Medical and Genomic Data: From Theory to Practice
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