My research is in computer security and privacy. More specifically, I am interested in designing inference algorithms to quantify information leakage of computational systems about their 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.
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.
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.
Richard McPherson, Reza Shokri, and Vitaly Shmatikov
➙ Defeating Image Obfuscation with Deep Learning
arXiv:1609.00408, 2016
Media:
The Register,
WIRED,
The Telegraph,
BBC,
and more
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
Reza Shokri.
➙ 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.
Arthur Gervais, Reza Shokri, Adish Singla, Srdjan Capkun, and Vincent Lenders.
➙ Quantifying Web-Search Privacy
➙ [code]
In ACM Conference on Computer and Communications Security (CCS), 2014.
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 (Sem 2: 2017, 2018): Algorithmic Foundations of Privacy
CS6231 (Sem 1: 2018): An Adversarial View of Privacy (in Machine Learning)
CS6101: Privacy and Security in Machine Learning
If you are interested in working with me, please fill in this form. PhD candidates need to first get admission from the computer science department (Due dates: 15 June and 15 December). International students can also apply for the SINGA award (Due dates: 1 June and 1 January). Postdoc candidates need to have strong analytical skills in statistics, probability, and machine learning. Knowledge in cryptography is a plus.