Research Areas: Cryptography, Privacy Enhancing Technologies, Distributed Computing
Peter Rindal joined the advanced cryptography group at Visa Research as a Research Scientist in September 2018. In the same year Peter earned his Ph.D. in cryptography from Oregon State University where he specialized in secure multi-party computation. His dissertation is on the topic of private set intersection which allows two parties to compare sets of encrypted data, e.g. identifying common friends in encrypted contact lists. Peter has also held several internships at MSR Redmond and Visa Research where he worked on projects involving fully homomorphic encryption, threshold cryptography, and privacy preserving machine learning. He now continues to explore these topics as a research scientist at Visa Research.
Payman Mohassel and Peter Rindal. ABY3: A Mixed Protocol Framework for Machine Learning. CCS: ACM Conference on Computer and Communications Security. 2018.
Hao Chen, Zhicong Huang, Kim Laine, Peter Rindal. Labeled PSI from Fully Homomorphic Encryption with Malicious Security. CCS: ACM Conference on Computer and Communications Security. 2018.
Shashank Agrawal, Payman Mohassel, Pratyay Mukherjee and Peter Rindal, DiSE: Distributed Symmetric-key Encryption. CCS: ACM Conference on Computer and Communications Security. 2018.
Daniel Demmler, Peter Rindal, Mike Rosulek and Ni Trieu. PIR-PSI: Scaling Private Contact Discovery. PETS: The 18th Privacy Enhancing Technologies Symposium. 2018.
Peter Rindal and Mike Rosulek. Malicious-Secure Private Set Intersection via Dual Execution. CCS: ACM Conference on Computer and Communications Security. 2017.
Hao Chen, Kim Laine and Peter Rindal. Fast Private Set Intersection from Homomorphic Encryption. CCS: ACM Conference on Computer and Communications Security. 2017.
Peter Rindal and Mike Rosulek. Improved Private Set Intersection Against Malicious Adversaries. Eurocrypt. 2017.
Gizem S. Cetin, Hao Chen, Kim Laine, Kristin E. Lauter, Peter Rindal and Yuhou Xia. Private Queries on Encrypted Genomic Data. BMC Medical Genomics. 2017.
Melissa Chase, Ran Gilad-Bachrach, Kim Laine, Kristin E. Lauter and Peter Rindal. Private Collaborative Neural Network Learning. IACR Cryptology ePrint Archive. 2017.
Peter Rindal and Mike Rosulek. Faster Malicious 2-Party Secure Computation with Online/Offline Dual Execution. USENIX Security Symposium. 2016.
Ran Gilad-Bachrach, Kim Laine, Kristin E. Lauter, Peter Rindal and Mike Rosulek. Secure Data Exchange: A Marketplace in the Cloud. IACR Cryptology ePrint Archive. 2016.