Federated Learning enables collaborative training of Deep Neural Network among distributed entities without necessitating the exchange of raw training data. While offering notable advantages, this decentralized approach introduces potential vulnerabilities, particularly in the form of poisoning attacks capable of manipulating models during collaborative training.
Plattform Lernende Systeme, Systems Security Lab and IBM Watson Center invite you to a AI Coding Workshop on 15 Feburary 2024 in Munich. The workshop will provide participants with an understanding of Federated Learning security challenges and equip them with practical skills to address these concerns. During the hands-on session, attendees will gain practical insights into the attack landscape for building secure and private Federated Learning systems.
Key Workshop Components
- Insights: Participants will gain comprehensive insights into the security and privacy challenges inherent in Federated Learning.
- Talks: The workshop includes several sessions covering various facets of poisoning attacks and state-of-the-art detection techniques.
- Hands-On Sessions: During the practical sessions participants will implement targeted and untargeted poisoning attacks. Additionally, attendees will explore defense mechanisms to understand their effectiveness.
- Target Audience: This workshop addresses beginners in Deep Learning as well as people already having experience, the only prerequisite being familiarity with an imperative programming language.
Besides basic programming skills in any imperative programming language, you only need to bring a passion for computer science and security aspects.
This AI Coding Workshop is designed for Bachelor's and Master's students, PhD-Candidates and Young Professionals.
You’re a Bachelor’s or Master’s student or a Young Professional eager to learn more about AI and Machine Learning? Apply now for the AI Coding Workshop! Application closing date is 31 January 2024. Due to limited availability, early registration is encouraged to ensure an intimate and focused learning environment.
Further information and registration