My research is in computer security and privacy. My current focus is on machine learning and data privacy, adversarial machine learning, interpretable machine learning, and privacy-preserving data synthesis.
➙ I have open positions for PhD students, postdoctoral researchers, and long-term interns. PhD candidates need to first get admission from the computer science department. Please feel free to email me after you get the admission, and I will be happy to talk to you about our current projects. International students can also apply for the SINGA award. Postdoc candidates need to have strong analytical skills in statistics, probability, and machine learning. Knowledge in cryptography is a plus. Please send me your CV and research statement. Undergraduate students (of other universities) who are exceptionally good in algorithms and are interested in working with me as an intern need to fill out this form. I am also open to working with talented NUS undergraduate students who are interested in working on research projects. Please feel free to email me.
Milad Nasr, Reza Shokri, and Amir Houmansadr
➙ Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning
To appear: IEEE Symposium on Security and Privacy (S&P) -- Oakland, 2019.
Milad Nasr, Reza Shokri, and Amir Houmansadr
➙ Machine Learning with Membership Privacy using Adversarial Regularization
➙ [code]
ACM Conference on Computer and Communications Security (CCS), 2018.
Tyler Hunt, Congzheng Song, Reza Shokri, Vitaly Shmatikov, and Emmett Witchel
➙ Chiron: Privacy-preserving Machine Learning as a Service
arXiv:1803.05961, 2018
Media:
ZDNet
Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov
➙ Membership Inference Attacks against Machine Learning Models
➙ [code]
➙ [data]
➙ [talk]
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]
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]
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
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]
ACM Conference on Computer and Communications Security (CCS), 2015.
(Invited to) Conference on Communication, Control, and Computing (Allerton), 2015.
Media: MIT Technology Review
Reza Shokri.
➙ Privacy Games: Optimal User-Centric Data Obfuscation
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
Network and Distributed System Security (NDSS) Symposium, 2015.
Arthur Gervais, Reza Shokri, Adish Singla, Srdjan Capkun, and Vincent Lenders.
➙ Quantifying Web-Search Privacy
➙ [code]
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
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]
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]
IEEE Symposium on Security and Privacy (S&P) -- Oakland, 2011.
Runner-up for the Outstanding Research Award in Privacy Enhancing Technologies 2012.
CS4257 (Sem 2: 2017-18, 2018-19): Algorithmic Foundations of Privacy (anonymous communication, data privacy, private computation)
CS6231 (Sem 1: 2018-19): An Adversarial View of Privacy (inference attacks)
CS6101 (Sem 1: 20**): Privacy and Security in Machine Learning (adversarial machine learning)