Michal Shlapentokh-Rothman

Michal  Shlapentokh-Rothman
MIT EECS | Lincoln Laboratory Undergraduate Research and Innovation Scholar
Advisor: Una-May O'Reilly
Department: EECS
Areas of Research: Computer Systems
Years: 2018-2019
Research Project Title:

Using Machine Learning to Co-Optimize Cybersecurity

abstract:Cybersecurity is a growing threat can have profound impacts on people’s lives. The ALFA group at MIT has been working on developing algorithms to proactively thwart the threat of attackers on networks. My SuperUROP project would involve using machine learning algorithms to help create robust network system configurations that are better able to withstand attacks. The end goal would be to create a deployable configuration that can be transferred to existing systems. Ideally, our system would be able to help network administrators best determine how to set up their network.
About:

After taking Intro to Artificial Intelligence (6.034), and Computer Systems Engineering (6.033) I became interested in both machine learning and security. Through participating in SuperUROP, I am excited to learn more about research in both of these fields and how machine learning can help make more secure systems. Additionally, I am looking forward to gaining experience in working on a long term research project.