Crypto Café at FAU Department of Mathematics and Statistics

Speaker: Dung Bui, LIP6, Sorbonne Université, France

Title: FOLEAGE: F4OLE-Based Multi-Party Computation for Boolean Circuits        FLYER

Abstract:  Secure Multi-party Computation (MPC) allows two or more parties to compute any public function over their privately-held inputs, without revealing any information beyond the result of the computation. Modern protocols for MPC generate a large amount of input-independent preprocessing material called multiplication triples, in an offline phase. This preprocessing can later be used by the parties to efficiently instantiate an input-dependent online phase computing the function. 

To date, the state-of-the-art secure multi-party computation protocols in the preprocessing model are tailored to secure computation of arithmetic circuits over large fields and require little communication in the preprocessing phase, typically O(N · m) to generate m triples among N parties. In contrast, when it comes to computing preprocessing for computations that are naturally represented as Boolean circuits, the state-of-the-art techniques have not evolved since the 1980s, and in particular, require every pair of parties to execute a large number of oblivious transfers before interacting to convert them to N-party triples, which induces an Ω(N^2 · m) communication overhead.

In this paper, we introduce FOLEAGE, which addresses this gap by introducing an efficient preprocessing protocol tailored to Boolean circuits. FOLEAGE exhibits excellent performance: It generates m multiplication triples over F2 using only N · m + O(N^2 · log m) bits of communication for N-parties, and can concretely produce over 12 million triples per second in the 2-party setting on one core of a commodity machine. Our result builds upon an efficient Pseudorandom Correlation Generator (PCG) for multiplication triples over the field F4. Roughly speaking, a PCG enables parties to stretch a short seed into a large number of pseudorandom correlations non-interactively, which greatly improves the efficiency of the offline phase in MPC protocols. Our construction significantly outperforms the state-of-the-art, which we demonstrate via a prototype implementation. This is achieved by introducing a number of protocol-level, algorithmic-level, and implementation-level optimizations on the recent PCG construction of Bombar et al. (Crypto 2023) from the Quasi-Abelian Syndrome Decoding assumption.

Bio: Dung Bui is a postdoctoral researcher at LIP6, Sorbonne Université, France. She completed her PhD at IRIF, Université Paris Cité.  Her research interests are in various aspects of both practical and theoretical cryptography, including secure multiparty computation, zero-knowledge proofs, and post-quantum cryptography.

Contact email:  dung.bui@lip6.fr

https://researchseminars.org/seminar/CryptoCafe

September 30, 2025, 10:00 am  Science Building (SE-43), room 215

Speaker:  Anil Kumar Pradhan, Founding Cryptographer and Cryptography Research Lead, Vaultree

Title: Beyond Theory: Industry Challenges in Adopting Homomorphic Encryption

Abstract: Fully Homomorphic Encryption (FHE) promises quantum-resilient, privacy-preserving computation for sensitive data across industries. However, despite academic breakthroughs, the leap from laboratory models to enterprise-scale adoption remains daunting. Industry faces formidable obstacles, including computational resource demands, implementation complexity, slow processing speeds, and high costs, aggravated by a shortage of FHE talent and lack of standardized practices. Integrating FHE into legacy and cloud systems requires extensive technical overhaul, often with questionable ROI. The disconnect between academic solutions and practical business needs, especially regarding scalability, cost, and integration continues to deter widespread implementation. Emerging technologies and optimization strategies, such as hardware acceleration and real-world application benchmarking, may help bridge the gap, but genuine adoption will require collaborative efforts and a shift in focus from theoretical promise to operational feasibility. Bio

Anil Kumar Pradhan is a cryptographer specializing in practical privacy-enhancing technologies and their deployment in real-world systems. At Vaultree, he works at the intersection of advanced cryptography and industry adoption, focusing on fully homomorphic encryption (FHE), encrypted machine learning, and secure computation at scale. With a background spanning both academic research and enterprise engineering, he bridges the gap between theoretical innovation and operational feasibility. Anil has contributed to projects that bring cutting-edge cryptographic methods into production environments, with particular attention to performance optimization, compliance, and developer experience. He is passionate about making strong cryptography usable, scalable, and impactful across industries that handle sensitive data.

Anil Kumar Pradhan is the Founding Cryptographer and Cryptography Research Lead at Vaultree Ireland, and has over a decade of experience in applied cryptography. He holds an M.Sc. in Mathematics from the Indian Institute of Technology, Delhi, and a B.Sc. (Hons) in Mathematics and Computing from the Institute of Mathematics and Applications, Bhubaneswar.