Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
Explores the challenges of protecting location privacy and various techniques to mitigate location-related inferences, highlighting the importance of trust assumptions and practical issues.
Explores Privacy Pass, a method to bypass internet challenges anonymously, discussing key concepts and addressing performance and scalability concerns.
Explores privacy-preserving data publishing mechanisms, including k-anonymity and differential privacy, and their practical applications and challenges.
Covers privacy mechanisms, their pros and cons, and their application in various scenarios, emphasizing privacy as a security property and its significance in society.
Explores the intersection of machine learning and privacy, discussing confidentiality, attacks, differential privacy, and trade-offs in federated learning.
Explores the SwissCovid app, a proximity-tracing solution against COVID-19, covering technical aspects, building trust, privacy, security, and collaboration with Google and Apple.
