EFFICIENT PRIVACY-PRESERVING CLASSIFICATION OF ECG SIGNALS

被引:14
作者
Barni, Mauro [1 ]
Failla, Pierluigi [1 ]
Lazzereni, Riccardo [1 ]
Paus, Annika [2 ]
Sadeghi, Ahmad-Reza [2 ]
Schneider, Thomas [2 ]
Kolesnikov, Vladimir [3 ]
机构
[1] Univ Siena, I-53100 Siena, Italy
[2] Ruhr Univ Bochum, Bochum, Germany
[3] Bell Lab, Murray Hill, NJ USA
来源
2009 FIRST IEEE INTERNATIONAL WORKSHOP ON INFORMATION FORENSICS AND SECURITY (WIFS) | 2009年
关键词
Secure signal processing; privacy preserving; secure two-party computation; ECG classification; SECURE EVALUATION;
D O I
10.1109/WIFS.2009.5386475
中图分类号
TP301 [理论、方法];
学科分类号
080201 [机械制造及其自动化];
摘要
We describe a privacy-preserving system where a server can classify an ElectroCardioGram (ECG) signal without learning any information about the ECG signal and the client is prevented from gaining knowledge about the classification algorithm used by the server. The system relies on the concept of Linear Branching Programs (LBP) and a recently proposed cryptographic protocol for secure evaluation of private LBPs. We study the trade-off between signal representation accuracy and system complexity both from practical and theoretical perspective. As a result, the inputs to the system are represented with the minimum number of bits ensuring the same classification accuracy of a plain implementation. We show how the overall system complexity can be strongly reduced by modifying the original ECG classification algorithm. Two alternatives of the underlying cryptographic protocol are implemented and their corresponding complexities are analyzed to show suitability of our system in real-life applications for current and future security levels.
引用
收藏
页码:91 / +
页数:2
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