Publications associées à Privacy concerns with social networking services

ProGAP: Progressive Graph Neural Networks with Differential Privacy Guarantees

Graph Neural Networks (GNNs) have become a popular tool for learning on graphs, but their widespread use raises privacy concerns as graph data can contain personal or sensitive information. Differentially private GNN models have been recently proposed to p ...

Assoc Computing Machinery2024

PRO-Face C: Privacy-Preserving Recognition of Obfuscated Face via Feature Compensation

Touradj Ebrahimi, Lin Yuan, Xiao Pu, Yao Zhang, Hongbo Li

The advancement of face recognition technology has delivered substantial societal advantages. However, it has also raised global privacy concerns due to the ubiquitous collection and potential misuse of individuals' facial data. This presents a notable par ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Challenging the Assumptions: Rethinking Privacy, Bias, and Security in Machine Learning

Bogdan Kulynych

Predictive models based on machine learning (ML) offer a compelling promise: bringing clarity and structure to complex natural and social environments. However, the use of ML poses substantial risks related to the privacy of their training data as well as ...

EPFL2023

Privacy-Preserving Machine Learning on Graphs

Sina Sajadmanesh

Graph Neural Networks (GNNs) have emerged as a powerful tool for learning on graphs, demonstrating exceptional performance in various domains. However, as GNNs become increasingly popular, new challenges arise. One of the most pressing is the need to ensur ...

EPFL2023

P3LI5: Practical and confidEntial Lawful Interception on the 5G core

Apostolos Pyrgelis, Francesco Intoci

Lawful Interception (LI) is a legal obligation of Communication Service Providers (CSPs) to provide interception capabilities to Law Enforcement Agencies (LEAs) in order to gain insightful data from network communications for criminal proceedings, e.g., ne ...

IEEE2023

Referencing in YouTube Knowledge Communication Videos

Daniel Gatica-Perez, Haeeun Kim

In recent years, there has been widespread concern about misinformation and hateful content on social media that are damaging societies. Being one of the most influential social media that practically serves as a newsearch engine, YouTube has accepted crit ...

Assoc Computing Machinery2023

TEEzz: Fuzzing Trusted Applications on COTS Android Devices

Mathias Josef Payer, Marcel Busch

Security and privacy-sensitive smartphone applications use trusted execution environments (TEEs) to protect sensitive operations from malicious code. By design, TEEs have privileged access to the entire system but expose little to no insight into their inn ...

IEEE COMPUTER SOC2023

Data Privacy Concerns as a Source of Resistance to Complete Mobile Data Collection Tasks Via a Smartphone App

Daniel Gatica-Perez

Smartphones present many interesting opportunities for survey research, particularly through the use of mobile data collection applications (apps). There is still much to learn, however, about how to integrate apps in general population surveys. Recent stu ...

OXFORD UNIV PRESS INC2022

The impact of NFT profile pictures within social network communities

Marco Mattavelli, Simone Casale Brunet

This paper presents an analysis of the role of social media, specifically Twitter, in the context of non-fungible tokens, better known as NFTs. Such emerging technology framing the creation and exchange of digital object, started years ago with early proje ...

ACM2022

The Role of Compromised Accounts in Social Media Manipulation

Tugrulcan Elmas

In recent years we have seen a marked increase in disinformation including as part of a strategy of so-called hybrid warfare. Adversaries not only directly spread misleading content but manipulate social media by employing sophisticated techniques that exp ...

EPFL2022

Differentially Private Multi-Agent Constraint Optimization

Boi Faltings, Sujit Prakash Gujar, Sankarshan Damle, Aleksei Triastcyn

Several optimization scenarios involve multiple agents that desire to protect the privacy of their preferences. There are distributed algorithms for constraint optimization that provide improved privacy protection through secure multiparty computation. How ...

ACM2022

A Modular Multimodal Architecture for Gaze Target Prediction: Application to Privacy-Sensitive Settings

Jean-Marc Odobez, Anshul Gupta, Samy Tafasca

Predicting where a person is looking is a complex task, requiring to understand not only the person's gaze and scene content, but also the 3D scene structure and the person's situation (are they manipulating? interacting or observing others? attentive?) to ...

IEEE2022

Explainability and Graph Learning From Social Interactions

Ali H. Sayed, Stefan Vlaski, Konstantinos Ntemos, Valentina Shumovskaia

Social learning algorithms provide models for the formation of opinions over social networks resulting from local reasoning and peer-to-peer exchanges. Interactions occur over an underlying graph topology, which describes the flow of information among the ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Preliminary metadata paper. Data Domotopia: a web-based survey about home-making in a moving world

Vincent Kaufmann, Luca Giovanni Pattaroni, Guillaume Simon Joseph Drevon, Marc-Edouard Baptiste Grégoire Schultheiss, Garance Clément, Fiona Ines Del Puppo

This questionnaire Data Domotopia is a 100+ multi-purpose items about home-making and stillness in a moving world. The survey covers most of the contemporary issues related to home-making. This includes the domestic space and gender issues; the socio-spati ...

2022

Flying in Private Mode: Understanding and Improving the Privacy ICAO Address Program

Guillaume Michel Le Bars

Location privacy of aircraft has recently gained attention as air traffic management was modernized using novel surveillance technologies. Business aviation circles and various military and government entities voiced serious concerns about automated and ub ...

AMER INST AERONAUTICS ASTRONAUTICS2021

Analyzing and Protecting Communication Metadata

Ludovic Barman

Most communication systems (e.g., e-mails, instant messengers, VPNs) use encryption to prevent third parties from learning sensitive information. However, encrypted communications protect the contents but often leak metadata: the amount of data sent and th ...

EPFL2021

Privacy-preserving photo sharing based on blockchain

Touradj Ebrahimi, Pablo Pfister

Sharing photos online has become an extremely popular activity, raising a wide concern on privacy issues related to the shared content. ProShare, a photo-sharing solution developed by Multimedia Signal Processing Group of EPFL addresses some of these priva ...

SPIE-INT SOC OPTICAL ENGINEERING2020

High dynamic range image sharing with privacy protection

Touradj Ebrahimi, Evgeniy Upenik, Pol Fernandez Marti

Sharing pictures has become a very popular practice among consumers. Most recent cameras, displays, and smartphones can capture and display images in high dynamic range and wide colour gamut, contributing to an increase of this type of content. It is a wel ...

SPIE2020

Dynamic pattern recognition in large-scale graphs with applications to social networks

Volodymyr Miz

A graph is a versatile data structure facilitating representation of interactions among objects in various complex systems. Very often these objects have attributes whose measurements change over time, reflecting the dynamics of the system. This general da ...

EPFL2020

DELF: Safeguarding deletion correctness in Online Social Networks

Georgios Damaskinos

Deletion is a core facet of Online Social Networks (OSNs). For users, deletion is a tool to remove what they have shared and control their data. For OSNs, robust deletion is both an obligation to their users and a risk when developer mistakes inevitably oc ...

USENIX ASSOC2020