Key figures in the history of Privacy-Enhancing Technology

Privacy-enhancing technology may not get the same number of headlines as cryptocurrency or blockchain technologies, but privacy-enhancing technologies have enabled countless scientific breakthroughs and groundbreaking business insights.

Now considered essential technology, examples of privacy-enhancing tech like secure multiparty computation are the result of decades of research from brilliant innovators. From Craig Gentry enabling the practical use of groundbreaking encryption theory, to Donald Beaver developing secure processing methods for sensitive data from multiple parties, a small group of luminaries have been essential in this area of technology.

Although there are many examples of effective privacy-enhancing technologies and the people behind them, the three figures below have played fundamental parts and we have decided to single them out for recognition in the second installment of our ongoing series.

Craig Gentry

With decades of experience in data privacy and cryptography, Craig Gentry has received many prestigious awards for his work related to privacy-enhancing technologies.

In 2009, Gentry published what would go on to be a seminal paper in the field of privacy-enhancing technology. Written as part of his Ph. D, the paper detailed a practical framework for a technology called fully homomorphic encryption. This technology provides the ability to both process encrypted data and produce encrypted results without secret keys or decryption. While the theory behind fully homomorphic encryption was first proposed in 1978, Gentry’s paper directly resulted in a vast range of practical applications. Many of these applications involve multiple parties sending sensitive, encrypted data to a server for secure processing.

In 2013, Gentry and a team of colleagues presented a concept known as cryptographic software obfuscation. This idea enables the encryption of entire programs without affecting their functionality, making it incredibly challenging to reverse engineer a valuable proprietary program.

Gentry’s work over the years has won him numerous accolades. His 2009 paper won the Association for Computing Machinery’s Doctoral Dissertation Award. In 2010, Gentry won the association’s coveted Grace Murray Hopper Award. An award also received by Apple inventor Steve Wozniak, this award is given to individuals who make a major technical or service contribution to computing before they turn 35 years old.

In June 2022, Gentry received the Gödel Prize, an annual award given by the European Association for Theoretical Computer Science and the Association for Computing Machinery. This award is given for outstanding theoretical computer science papers. Gentry in a team of co-authors received it for presenting completely new constructions of fully homomorphic encryption. That same month, Gentry joined TripleBlind as the company’s Chief Technology Officer.

Donald Beaver

Donald Beaver is a product-focused computer researcher and software engineer specializing in cryptography.

In 1991, Beaver published a paper that would revolutionize multiparty protocols for secure computations. In the paper, Beaver argued that existing methods included several rounds of unnecessary interactions that significantly drove up computing costs. Using an elegant device now widely known as Beaver Triples, the paper explained how a simple reconstruction of secretly shared values could reduce rounds of interactions among participants by an order of magnitude. The protocol currently enables machine learning software at Facebook and Google.

While Andrew Yao is credited with inventing a protocol for secure multiparty computing now known as garbled circuits, Beaver and two co-authors are credited with coining the term in a 1990 paper. The garbled circuits protocol allows multiple parties to jointly process secure data without revealing the data itself.

In addition to being a key figure in the area of privacy-enhancing computation techniques, Beaver has also made major contributions to other areas of technology. His code in Apple’s iBooks app allows users to highlight, bookmark, and navigate. From 2015 to 2019, Beaver worked at Uber to develop user interfaces for self-driving vehicles.

Claude Crepeau

While working on his doctorate and the computer lab at MIT, Claude Crepeau and two co-authors published a foundational paper on secure protocols for multiparty computation.

In their paper, Crepeau and colleagues established a general multiparty processing protocol that unconditionally secured any shared private data, assuming each pair of participants could establish authenticated secrecy channels. The research team established a reasonable multiparty protocol that could be unconditionally secure if at least one-third of the participants remain honest. This paper would go on to lay the foundations for the secure multiparty computing technology that we use today.

Crepeau has also made major contributions in the areas of zero-knowledge protocols and two-party secure function evaluation, both of which are essential data privacy technologies and tools.

In 2021, Crepeau and colleagues from the University of Geneva in Switzerland unveiled a groundbreaking technique for identity verification. While existing systems can be highly secure, the growing capabilities of quantum computing threaten to undo this level of security. Expanding on the concept of zero-knowledge proofs, the research team described a verification system based on the notion that information cannot travel faster than the speed of light.

Leveraging the latest in privacy-enhancing technology with TripleBlind

Don Beaver’s seminal 1991 paper began with a critical insight: “The difference between theory and practice often rests on one major factor: efficiency.”

Building on the foundational privacy-enhancing techniques from pioneers in our industry, the TripleBlind solution allows for more practical, more efficient secure multiparty computation.

Our privacy-enhancing software allows healthcare researchers, financial services companies, and organizations to engage in valuable collaborations while keeping possession of individual proprietary assets. Using our innovative advancements, participants can safely engage in a secure data collaboration without decryption keys. Data can also be safely processed, and participants can be confident that their results will be kept as private as their contributions.

If you would like to know more about the latest in data privacy-enhancing technologies, contact us today.