NewsThe Algorand Foundation partners with NYU to improve privacy in cloud-based application

The Algorand Foundation partners with NYU to improve privacy in cloud-based application


Algorand Foundation

February 22nd, 2022 - The Algorand Foundation is partnering with New York University (NYU) to conduct research on private verifiable databases and their applications to public blockchains. The team at NYU, led by Professor Yevgeniy Dodis, will design solutions using tools of modern cryptography to address basic questions such as the design of private blockchains on top of public blockchains, and building privacy-preserving, ordered verifiable databases.

“I am excited to partner with the Algorand Foundation on this project,” says Dodis. “We live in an age where massive amounts of data need to be stored and manipulated efficiently. This creates unprecedented challenges for privacy, security, integrity and availability. Modern cryptography can offer opportunities to address these challenges. Part of our research will focus on how distributed implementations for private verifiable databases could work for the Algorand Protocol.”

Dr. Yevgeni Dodis is a professor of computer science at NYU. He received his PhD from MIT in 2000. Dodis' research is primarily in cryptography and network security. In particular, he has worked in a variety of areas including random number generation, leakage-resilient cryptography, cryptography under weak randomness, cryptography with biometrics and other noisy data, hash function and block cipher design, protocol composition, and information-theoretic cryptography. Dodis is an IACR Fellow and leader of the NYU Cryptography group.

The Algorand Foundation is committed to building a truly global blockchain ecosystem and our Grant and Development Award funding mechanisms have supported other education and research projects in academia such as the UF Blockchain Lab - Powered by Algorand and the Algorand Fintech Innovation Hub at the University of Cape Town.

If you are interested in submitting a project for support from the Algorand Foundation Grant programme, please apply here.

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