Poster Session

The following posters were presented at the HealthTech '13 Poster Session on Monday, August 19, 2013, 5:30 p.m.–7:00 p.m.

Privacy-Enhancing Technologies for Disease Risk Tests Based on Genomic and Non-Genomic Data
Erman Ayday, Jean Louis Raisaro, Paul J. McLaren, Jacques Fellay and Jean-Pierre Hubaux, École Polytechnique Fédérale de Lausanne
Poster PDF

Towards Privacy Compliance in the Management of Raw Genomic Data
Erman Ayday and Jean Louis Raisaro, École Polytechnique Fédérale de Lausanne; Urs Hengartner, University of Waterloo; Zhicong Huang, Sophia Genetics; Adam Molyneaux and Jean-Pierre Hubaux, École Polytechnique Fédérale de Lausanne
Poster PDF

Medical Data Segmentation for Privacy
Ellick Chan, Peifung E. Lam, and John C. Mitchell, Stanford University
Poster PDF

Forensically-aware Insulin Pump Systems
Nathan L. Henry, University of Tennessee; Nathanael R. Paul, University of South Florida; Nicole McFarlane, University of Tennessee
Poster PDF

Measuring the Forensic-ability of Audit Logs for Nonrepudiation
Jason King and Laurie Williams, North Carolina State University
Poster PDF

Maude Miner Mining: FDA’s MAUDE Dataset for Security Events
Thomas Lovett, Denis Foo Kune, and Kevin Fu, University of Michigan
Poster PDF

A Home and Assisted Living Monitoring System for Large-Scale Patient Populations
Norka B. Lucena, Grzegorz Lewandowski, Paul Roman, Roman Markowski, Marek Podgorny, and George Mazevski, VITAL Telehealth
Poster PDF

Advanced Auditing Electronic Medical Record Access Logs
Steve Nyemba and Bradley Malin, Vanderbilt University; David Liebovitz, Northwestern University; Eric Duffy and Carl Gunter, University of Illinois at Urbana-Champaign
Poster PDF

WattsUpDoc: Data Collection — Using Power Side Channels to Discover Malware on Embedded Medical Devices
Katarzyna Olejnik, Shane S. Clark, and Kevin Fu, University of Michigan
Poster PDF

Access Control Policy Extraction from Natural Language Text
John Slankas and Laurie Williams, North Carolina State University
Poster PDF

Making the Invisible Visible: Analyzing the 510(k) Device Dependencies
Tingyi Wei, Denis Foo Kune, and Kevin Fu, University of Michigan
Poster PDF