Towards Informed Watermarking of Personal Health Sensor Data for Data Leakage Detection

Activity: Talk or presentationContributed talkscience-to-science

Description

Users of personal health devices want an easy way to permanently store their personal health sensor data and to share them with physicians and other authorized users, trusting that the data will not be disclosed to third parties. Digital watermarking for data leakage detection aims to prevent the unauthorized disclosure of data by imperceptibly marking the data for each authorized user, so that the authorized user can be identified as the data leaker and be held accountable. In this paper we present an approach for digital watermarking conceived as part of a personal health sensor data management platform. The approach comprises techniques for informed watermark embedding and non-blind watermark detection. Based on a proof-of-concept prototype, the approach is evaluated regarding configurability, robustness, and performance. Keywords: Medical Sensor Data, Digital Fingerprinting, Time Series Data
Period25 Nov 2020
Event title19th International Workshop on Digital-forensics and Watermarking (IWDW 2020), Melbourne Australia, November 25-27, 2020 (Online Event)
Event typeConference
LocationAustriaShow on map

Fields of science

  • 102028 Knowledge engineering
  • 102016 IT security
  • 102027 Web engineering
  • 502050 Business informatics
  • 503008 E-learning
  • 102 Computer Sciences
  • 102030 Semantic technologies
  • 102033 Data mining
  • 102010 Database systems
  • 102035 Data science
  • 102015 Information systems
  • 102025 Distributed systems

JKU Focus areas

  • Digital Transformation