Matthew Jagielski

Northeastern University
Graduate Student
Email: (my last name)
Google Scholar
About Me
I am currently a fourth year PhD student advised by Alina Oprea and Cristina Nita-Rotaru, working as a member of the Network and Distributed Systems Security Lab (NDS2).

My research is broadly at the intersection between machine learning, security, and privacy. The goal of my research is to design training and deployment of machine learning that is secure from real world adversaries. I also study the design of machine learning algorithms that preserve the privacy of individuals in the training set. I rely on techniques drawn from machine learning, theoretical computer science, and security.

During summer '19, I was at Google Brain Privacy and Security, working with Nicolas Papernot on model extraction attacks. In summer '18, I worked at DoS and Abuse at Google, using machine learning to protect Google Cloud customers from DoS attacks.

In other news, I enjoy running, swimming, biking, and weightlifting. I'm also a retired Super Smash Brothers tournament competitor.

  • Subpopulation Data Poisoning Attacks
    Matthew Jagielski, Paul Hand, Alina Oprea
    Preliminary version - NeurIPS 2019 Workshop on Robust AI in Financial Services
  • High-Fidelity Extraction of Neural Network Models
    Matthew Jagielski, Nicholas Carlini, David Berthelot, Alex Kurakin, and Nicolas Papernot
  • Secure Communication Channel Establishment: TLS 1.3 (over TCP Fast Open) vs. QUIC
    Shan Chen, Samuel Jero, Matthew Jagielski, Alexandra Boldyreva, Cristina Nita-Rotaru
    ESORICS 2019
  • Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks
    Ambra Demontis, Marco Melis, Maura Pintor, Matthew Jagielski, Battista Biggio, Alina Oprea, Cristina Nita-Rotaru, Fabio Roli
    USENIX Security 2019
  • Differentially private fair learning
    Matthew Jagielski, Michael Kearns, Jieming Mao, Alina Oprea, Aaron Roth, Saeed Sharifi-Malvajerdi, Jonathan Ullman (alphabetical)
    ICML 2019
    [Code] [Paper]
  • Network and system level security in connected vehicle applications
    Hengyi Liang, Matthew Jagielski, Bowen Zheng, Chung-Wei Lin, Eunsuk Kang, Shinichi Shiraishi, Cristina Nita-Rotaru, Qi Zhu
    ICCAD 2018
  • Threat Detection for Collaborative Adaptive Cruise Control in Connected Cars
    Matthew Jagielski, Nicholas Jones, Chung-Wei Lin, Cristina Nita-Rotaru, and Shinichi Shiraishi
    ACM WiSec 2018
  • Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning
    Matthew Jagielski, Alina Oprea, Chang Liu, Cristina Nita-Rotaru, and Bo Li
    IEEE S&P (Oakland) 2018
    [Code] [Paper]