Reza SHOKRI

Assistant Professor
Computer Science Department
National University of Singapore (NUS)


Email: firstname@comp.nus.edu.sg
Twitter: @rzshokri
Phone: +65-651-64464
Office: COM2-03-60
Mailing Address: Dept. of Computer Science,
NUS School of Computing, 13 Computing Drive,
Computing 1, #03-27, Singapore 117417.

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.

Selected Publications (see also Google Scholar)

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.

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.

Teaching

CS4257: Algorithmic Foundations of Privacy

CS6101: Privacy and Security in Machine Learning

Professional Activities

Program co-chair of Hot Topics in Privacy Enhancing Technologies (HotPETs): 2013 and 2014

Program committee member of
  • ACM CCS Workshop on Theory and Practice of Differential Privacy (TPDP): 2018
  • IEEE Symposium on Security and Privacy (Oakland): 2019
  • ACM Conference on Computer and Communications Security (CCS): 2017
  • USENIX Security Symposium: 2015, 2016
  • Network and Distributed System Security Symposium (NDSS): 2016, 2017
  • IEEE European Symposium on Security and Privacy (Euro S&P): 2017
  • Privacy-Enhancing Technologies Symposium (PETS): 2013, 2014, 2015, 2017, 2019
  • ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec): 2014, 2015, 2016, 2018
  • Conference on Decision and Game Theory for Security (GameSec): 2015, 2016, 2018
  • International World Wide Web Conference (WWW): 2016
  • ACM Workshop on Privacy in the Electronic Society (WPES): 2012, 2015
  • ASIACCS Workshop on IoT Privacy, Trust, and Security (IoTPTS): 2015, 2016
  • Workshop on Understanding and Enhancing Online Privacy (UEOP): 2016
  • International Workshop on Obfuscation: Science, Technology, and Theory: 2017
  • International Conference on Privacy, Security and Trust (PST): 2014

Open Positions

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.