Concept
Privacy engineering
Publications associées (139)
When Your AI Becomes a Target: AI Security Incidents and Best Practices
Alexandre Massoud Alahi, Kathrin Grosse
In contrast to vast academic efforts to study AI security, few real-world reports of AI security incidents exist. Released incidents prevent a thorough investigation of the attackers' motives, as crucial information about the company and AI application is ...
AAAI Press2024PRO-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 Inc2024A Privacy-Preserving Querying Mechanism with High Utility for Electric Vehicles
Electric vehicles (EVs) are becoming more popular due to environmental consciousness. The limited availability of charging stations (CSs), compared to the number of EVs on the road, has led to increased range anxiety and a higher frequency of CS queries du ...
Piscataway2024Challenging the Assumptions: Rethinking Privacy, Bias, and Security in Machine Learning
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 ...
EPFL2023P3LI5: 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 ...
New York2023Private Message Franking with After Opening Privacy
Serge Vaudenay, Iraklis Leontiadis
Recently Grubbs et al. [GLR17] initiated the formal study of message franking protocols. This new type of service launched by Facebook, allows the receiver in a secure messaging application to verifiably report to a third party an abusive message some send ...
2023Bridging the gap between theoretical and practical privacy technologies for at-risk populations
With the pervasive digitalization of modern life, we benefit from efficient access to information and services. Yet, this digitalization poses severe privacy challenges, especially for special-needs individuals. Beyond being a fundamental human right, priv ...
EPFL2023Privacy-preserving federated neural network training and inference
Training accurate and robust machine learning models requires a large amount of data that is usually scattered across data silos. Sharing, transferring, and centralizing the data from silos, however, is difficult due to current privacy regulations (e.g., H ...
EPFL2023Utility/privacy trade-off as regularized optimal transport
Strategic information is valuable either by remaining private (for instance if it is sensitive) or, on the other hand, by being used publicly to increase some utility. These two objectives are antagonistic and leaking this information by taking full advant ...
SPRINGER HEIDELBERG2022Protecting privacy through metadata analysis
Although encryption hides the content of communications from third parties, metadata, i.e., the information attached to the content (such as the size or timing of communication) can be a rich source of details and context. In this dissertation, we demonstr ...
EPFL2022