CyLab seminar: Neil Gong

March 14, 2022

12:00 p.m. ET

Panther Hollow (4th Floor in CIC) or Zoom

Neil Gong

Source: CyLab

Please note that CyLab seminars are closed to the public and open to CyLab partners and Carnegie Mellon University faculty, students and staff.

Speaker: Neil Gong, assistant professor at Duke University

Title: Secure Federated Learning

Federated learning is an emerging machine learning paradigm to enable many clients (e.g., smartphones, IoT devices, and edge devices) to collaboratively learn a model, with help of a server, without sharing their raw local data. Due to its communication efficiency and potential promise of protecting private or proprietary user data, and in light of emerging privacy regulations such as GDPR, federated learning has become a central playground for innovation. However, due to its distributed nature, federated learning is vulnerable to malicious clients. In this talk, Gong will discuss local model poisoning attacks to federated learning, in which malicious clients send carefully crafted local models or their updates to the server to corrupt the global model. Moreover, Gong will discuss his work on building federated learning methods that are secure against a bounded number of malicious clients.

Neil Gong is an assistant professor in the Department of Electrical and Computer Engineering and Department of Computer Science (secondary appointment) at Duke University. He is interested in cybersecurity and privacy with a recent focus on the intersections between security, privacy, and machine learning. He received an NSF CAREER award, ARO Young Investigator Program (YIP) award, Rising Star award from the Association of Chinese Scholars in Computing, IBM Faculty award, Facebook Research award, and multiple best paper or best paper honorable mention awards. Gong received a Ph.D. in computer science from the University of California, Berkeley in 2015 under the supervision of Dawn Song.

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