Unbounded HIBE and Attribute-Based Encryption

We present HIBE and ABE schemes which are “unbounded” in the sense that the public parameters do not impose additional limitations on the functionality of the systems. In all previous constructions of HIBE in the standard model, a maximum hierarchy depth had to be fixed at setup. In all previous constructions of ABE in the standard model, either a small universe size or a bound on the size of attribute sets had to be fixed at setup.

Our constructions avoid these limitations. We use a nested dual system encryption argument to prove full security for our HIBE scheme and selective security for our ABE scheme, both in the standard model and relying on static assumptions. Our ABE scheme supports LSSS matrices as access structures and also provides delegation capabilities to users.

This is joint work with Allison Lewko

Speaker Details

Dr. Brent Waters received his Ph.D. in Computer Science from Princeton University in 2004. From 2004-2005, he was a post-doctoral at Stanford University then worked at SRI as a Computer Scientist in the Principled Systems group. In 2008 he joined the faculty at The University of Texas at Austin as an assistant professor. Dr. Waters’
research interests are in the areas of computer security and applied cryptography. His work has focused on Identity-Based Cryptography, security of broadcast systems, and authentication of remote systems.
He has award and invited papers. He is noted as a founder of functional encryption. Dr. Waters both publishes and has served on the program committees of the top technical security venues (CRYPTO, Eurocrypt, the ACM Conference on Computer and Communications Security (CCS), Usenix Security and the IEEE Conference on Security and Privacy).
Dr. Waters has been an invited speaker in industry and at research Universities, including MIT, CMU, and Stanford. He was the keynote speaker on functional encryption at the2008 NIST workshop on Identity-Based Encryption. Dr. Waters is a National Academy of Sciences Kavli Fellow and recipient of the NSF CAREER award, a Microsoft Faculty Fellow, and a Sloan Research Fellowship.

Brent Waters
The University of Texas at Austin