Benny Pinkas

Benny Pinkas is a cryptographer whose work applies secure computation and privacy to machine learning. He earned a PhD at the Weizmann Institute of Science in 2000, coauthored the Fairplay secure-computation system in 2004, and took a sabbatical at Google Research during the 2011–2012 academic year. From 2019 to 2022, he directed Bar-Ilan's applied cryptography and cyber security center; his 2021 research tested machine-learning fairness, and ScionFL added secure aggregation to federated learning in 2024. Named an IACR Fellow in 2022, he worked at Aptos Labs from September 2022 to October 2024 and is a professor at Bar-Ilan and a research scientist at Apple, where he works on machine-learning privacy.

Now at: Bar-Ilan University and Apple
Works: 169
Citations: 20,219
h-index: 64
Badges: Bridge
Wayfarer

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

2000

A PhD at Weizmann

He completes a PhD at the Weizmann Institute of Science in 2000, where he studies with Moni Naor.
2004

Fairplay secure computation

In 2004, he coauthors Fairplay, a system that lets non-cryptographers use generic secure computation. The system implements secure function evaluation between two parties.
2011–2012

Google Research sabbatical

During the 2011–2012 academic year, he takes a sabbatical at Google Research. Earlier work includes roles at the University of Haifa, HP Labs in Haifa, Princeton, STAR Labs, and Intertrust Technologies.
2019–2022

Center director and model fairness

From 2019 to 2022, he directs the BIU Center for Research in Applied Cryptography and Cyber Security. In 2021, he coauthors “Fairness in the Eyes of the Data,” a framework that lets a tester assess a trained machine-learning model's fairness through a privacy-preserving interactive test.
2022

An IACR Fellowship

In 2022, the IACR names him a Fellow for research in secure multi-party computation, educational leadership, and service to the association.
September 2022–October 2024

Working at Aptos Labs

He works at Aptos Labs from September 2022 to October 2024.
2024

ScionFL for federated learning

In 2024, ScionFL appears at SaTML as his coauthored framework for secure federated-learning aggregation. It uses quantized inputs and provides robustness against malicious clients.
As of October 2026

Professor and Apple researcher

As of October 2026, he is a professor at Bar-Ilan University and a research scientist at Apple, where he works on privacy for machine learning. He serves on the IEEE S&P 2026 Cycle 2 program committee.