Webinar Abstract

As AI systems become increasingly integrated into our daily lives, ensuring their trustworthiness, transparency, and privacy is essential. For instance, how can we verify that the output of a large language model (LLM) is authentic? How can a proprietary LLM be made publicly accessible without exposing its internal parameters? And how can model inferences be shared without compromising users’ personal information? Without robust mechanisms to address the security and privacy challenges inherent in AI decision-making, stakeholders face significant risks. In this talk, we will explore several application scenarios where cryptographic techniques can enhance AI security and privacy. We will also highlight our group’s work on developing customized and efficient cryptographic protocols designed to tackle these issues.

Speaker

Charalampos Papamanthou is an Associate Professor of Computer Science at Yale University, where he co-directs the Yale Applied Cryptography Laboratory. He also serves as Chief Scientist at Lagrange Labs, a startup advancing systems and applications for zero-knowledge proofs. Prior to joining Yale, he was Director of the Maryland Cybersecurity Center (MC2) and Associate Professor of Electrical and Computer Engineering at the University of Maryland, College Park, which he joined in 2013 after completing a postdoc at UC Berkeley. Papamanthou’s research focuses on applied cryptography and computer security, with a particular emphasis on systems, theory, and technologies for secure and private cloud computing. His contributions to the field have been widely recognized. In 2022, he received the ACM CCS Test-of-Time Award for his work on searchable encryption. He is also the recipient of numerous honors, including the NSF CAREER Award, the JP Morgan Faculty Research Award, the Google Faculty Research Award, the Yahoo! Faculty Engagement Award, two NetApp Faculty Fellowships, the UMD Invention of the Year Award, the Jimmy Lin Award for Invention, and the George Corcoran Award for Excellence in Teaching. He was a finalist for the 2020 Facebook Privacy Research Award. His research has been supported by both government agencies (NSF, NIST, NSA) and industry leaders (including JP Morgan, Google, Yahoo!, NetApp, VMware, Amazon, Algorand, Ergo, Ethereum, and Protocol Labs). Papamanthou holds a PhD in Computer Science from Brown University (2011) and an MSc from the University of Crete (2005), where he was affiliated with ICS-FORTH. His work, which spans applied and theoretical cryptography, systems and database security, graph algorithms, and operations research, has been cited close to 15,500 times.

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