DIMACS Workshop on Outsourcing Computation Securely

July 6 - 7, 2017
DIMACS Center, CoRE Building, Rutgers University

Marina Blanton, University at Buffalo, mblanton at buffalo.edu
Guy Rothblum, Weizmann Institute of Science, rothblum at alum.mit.edu
Michael Walfish, New York University, mwalfish at cs.nyu.edu
Presented under the auspices of the DIMACS Special Focus on Cryptography as part of the DIMACS/Simons Collaboration in Cryptography and the DIMACS Special Focus on Cybersecurity.
Workshop Announcement

In modern computing, sensitive computations are routinely outsourced to remote providers. This paradigm comes with tremendous promise. For example, weak individuals and devices can be empowered by access to vast computation resources, fine-grained data about individuals can be tracked and analyzed to improve services and quality of life, and small organizations and individuals can benefit from pricing that economies of scale provide. Applications span the commercial, government, and military domains. However, with this promise also comes risk. An untrusted provider might knowingly (or unwittingly) corrupt a computation. Outsourcing a sensitive computation might result in breaches of privacy. Security considerations such as these prevent enterprises and individuals from outsourcing their computations and reaping the full benefits of cloud computing.

These topical concerns touch on core foundational problems in theory and cryptography. They also present fascinating challenges for security and systems research. This workshop will bring together these diverse communities to explore the state of the art research developments from theoretical cryptography and complexity theory, as well as state-of-the-art systems and security research, to facilitate a mutually-beneficial exchange between theory and practice, and to propel research on secure outsourcing and proofs of correct computation toward greater impact.

The topics of this interdisciplinary workshop will span security concerns for outsourced computations. A particular focus will be applications of probabilistic proofs, such as verifiable computing (wherein a client can verify the correctness of an untrusted computation without re-executing it).

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Document last modified on February 27, 2017.