University of Minnesota
Security and Privacy in Computing

Readings on: Differential privacy

Optional background reading: Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith. “Calibrating Noise to Sensitivity in Private Data Analysis”. In Theory of Cryptography Conference (TCC), pages 265–284, New York, NY, USA, March 2006.

Main reading for Tuesday, February 6th: Úlfar Erlingsson, Vasyl Pihur, and Aleksandra Korolova. “RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response”. In ACM Conference on Computer and Communications Security (CCS), pages 1054–1067, Scottsdale, AZ, USA, November 2014.

Candidate main reading: Tianhao Wang, Jeremiah Blocki, Ninghui Li, and Somesh Jha. “Locally Differentially Private Protocols for Frequency Estimation”. In USENIX Security Symposium, pages 729–745, Vancouver, BC, Canada, August 2017.

Main reading for Thursday, February 8th: Matthew Fredrikson, Eric Lantz, Somesh Jha, Simon Lin, David Page, and Thomas Ristenpart. “Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing”. In USENIX Security Symposium, pages 17–32, San Diego, CA, USA, August 2014.

Candidate main reading: Ilya Mironov. “On significance of the least significant bits for differential privacy”. In ACM Conference on Computer and Communications Security, pages 650–661, Raleigh, NC, USA, November 2012.

Candidate main reading: Christopher T. Kenny, Shiro Kuriwaki, Cory McCartan, Evan Rosenman, Tyler Simko, and Kosuke Imai. “The Use of Differential Privacy for Census Data and its Impact on Redistricting: The Case of the 2020 U.S. Census”. In Science Advances, Vol. 7, No. 7 (October 2021), pages 1-17.
[AAAS] [Author's version]

Candidate main reading: Miranda Christ, Sarah Radway, and Steven M. Bellovin. “Differential Privacy and Swapping: Examining De-Identification's Impact on Minority Representation and Privacy Preservation in the U.S. Census”. In IEEE Security and Privacy, May 2022.
[IEEE Xplore]