Machine Learning Algorithms over Encrypted Data for Cloud-based Clinical Decision Support

Speaker: Jim Basilakis

Affiliation: University of Western Sydney

Time: Monday 04/08/2014 from 14:00 to 15:00

Venue: Access Grid UWS. Presented from Campbelltown (26.1.50), accessible from Parramatta (EB.1.32) and Penrith (Y239).

Abstract:

In an effort to reduce the risk of sensitive data exposure in untrusted networks such as the public cloud, increased attention has recently been given to encryption schemes that allow specific computations to occur on encrypted data, without the need for decryption. In this situation, secret keys need never be exposed outside a trusted network. This relies on the fact that some encryption algorithms display the property of homomorphism, which allows them to manipulate data in a meaningful way while still in encrypted form.

Such a framework would find particular relevance in clinical decision support applications deployed in the public cloud. CDS applications have an important computational and analytical role over confidential healthcare information with the aim of supporting decision-making in clinical practice.

Biography: Jim is a Senior Lecturer in Health Informatics in the School of Computing, Engineering and Mathematics