My research is in computer security and privacy. More specifically, I am interested in designing inference algorithms to quantify information leakage of a system about its sensitive inputs. I also design privacy-preserving mechanisms to mitigate the risks of such inference attacks. My current focus is on machine learning and data privacy.
I have multiple open positions for postdocs, PhD students, and interns.
Milad Nasr, Reza Shokri, and Amir Houmansadr
➙ Machine Learning with Membership Privacy using Adversarial Regularization
To appear at the ACM Conference on Computer and Communications Security (CCS), 2018.
Kun Ouyang, Reza Shokri, David S Rosenblum, and Wenzhuo Yang
➙ A Non-Parametric Generative Model for Human Trajectories
In The International Joint Conference on Artificial Intelligence (IJCAI), 2018.
Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov
➙ Membership Inference Attacks against Machine Learning Models ➙ [code] ➙ [talk]
In IEEE Symposium on Security and Privacy (S&P) -- Oakland, 2017.
The Caspar Bowden Award for Outstanding Research in Privacy Enhancing Technologies 2018.
Vincent Bindschaedler, Reza Shokri, and Carl Gunter
➙ Plausible Deniability for Privacy-Preserving Data Synthesis ➙ [code]
In the Proceedings of the VLDB Endowment International Conference on Very Large Data Bases (PVLDB), 2017.
Vincent Bindschaedler and Reza Shokri.
➙ Synthesizing Plausible Privacy-Preserving Location Traces ➙ [code] ➙ [talk by V. Bindschaedler]
In IEEE Symposium on Security and Privacy (S&P) -- Oakland, 2016.
Reza Shokri, George Theodorakopoulos, and Carmela Troncoso
➙ Privacy Games along Location Traces: A Game-Theoretic Framework for Optimizing Location Privacy
In the ACM Transactions on Privacy and Security (TOPS), 2016.
Reza Shokri and Vitaly Shmatikov.
➙ Privacy-Preserving Deep Learning ➙ [code]
In ACM Conference on Computer and Communications Security (CCS), 2015.
(Invited to) Annual Allerton Conference on Communication, Control, and Computing (Allerton) 2015
Media: MIT Technology Review
➙ Privacy Games: Optimal User-Centric Data Obfuscation
In Privacy Enhancing Technologies Symposium (PETS), 2015
Igor Bilogrevic, Kevin Huguenin, Stephan Mihaila, Reza Shokri, and Jean-Pierre Hubaux.
➙ Predicting Users' Motivations behind Location Check-Ins and Utility Implications of Privacy Protection Mechanisms
In Network and Distributed System Security (NDSS) Symposium, 2015.
Reza Shokri, George Theodorakopoulos, Panos Papadimitratos, Ehsan Kazemi, and Jean-Pierre Hubaux.
➙ Hiding in the Mobile Crowd: Location Privacy through Collaboration
In IEEE Transactions on Dependable and Secure Computing (TDSC), 2014.
Reza Shokri, George Theodorakopoulos, Carmela Troncoso, Jean-Pierre Hubaux, and Jean-Yves Le Boudec.
➙ Protecting Location Privacy: Optimal Strategy against Localization Attacks ➙ [code]
In the 19th ACM Conference on Computer and Communications Security (CCS), 2012.
Reza Shokri, George Theodorakopoulos, Jean-Yves Le Boudec, and Jean-Pierre Hubaux.
➙ Quantifying Location Privacy ➙ [code]
In IEEE Symposium on Security and Privacy (S&P) -- Oakland, 2011.
Runner-up for the Outstanding Research in Privacy Enhancing Technologies 2012.
CS4257: Algorithmic Foundations of Privacy
CS6101: Privacy and Security in Machine Learning
➙ One open position for a postdoc. Candidates need to have strong analytical skills (statistics, probabilistic models, and machine learning). The project is about designing privacy-preserving mechanisms for machine-learning and data analytics. The exact starting date and the duration are negotiable.
➙ Multiple open positions for PhD students. Candidates need to get admission from the computer science department. (deadlines: 15 June and 15 December). International students can also apply for the SINGA award (deadlines: 1 June and 1 January).
➙ Multiple open positions for (senior undergraduate, and graduate students as) interns and research assistants. Students need to have strong analytical skills.
If you are interested, please fill in this form.