On the Insecurity of Peer-to-Peer Decentralized Machine Learning
Offered By: IEEE via YouTube
Course Description
Overview
Explore the security challenges of peer-to-peer decentralized machine learning in this 17-minute IEEE conference talk. Delve into the research findings presented by Dario Pasquini, Mathilde Raynal, and Carmela Troncoso from the SPRING Lab at EPFL, Switzerland. Gain insights into the potential vulnerabilities and risks associated with this emerging field of machine learning, and understand the implications for future developments in decentralized AI systems.
Syllabus
On the (In)security of Peer-to-Peer Decentralized Machine Learning
Taught by
IEEE Symposium on Security and Privacy
Tags
Related Courses
Sensor SecurityIEEE via YouTube Tracking Ransomware End-to-end
IEEE via YouTube Cinderella - Turning Shabby X.509 Certificates into Elegant Anonymous Credentials with the Magic of Verifiable Computation
IEEE via YouTube Algorithmic Transparency via Quantitative Input Influence - Theory and Experiments with Learning Systems
IEEE via YouTube Bitcoin Over Tor Isn't a Good Idea
IEEE via YouTube