|
|
Vorlesungsverzeichnis >> Medizinische Fakultät (Med) >>
|
Encryption of Audio Data for Context Recognition- Dozentinnen/Dozenten
- Prof. Dr. Oliver Amft, David Kopyto, M. Sc.
- Angaben
- Seminar
Online
4 SWS, benoteter Schein, Anwesenheitspflicht, ECTS-Studium, ECTS-Credits: 5, Sprache Deutsch und Englisch
Zeit:
- Voraussetzungen / Organisatorisches
- Link to the online introduction/Vorbesprechung April 12, 16:15-17:45, https://fau.zoom.us/j/97705596817?pwd=QlFjRlErMEJXWWlqVkFid01tUGJDdz09
- ECTS-Informationen:
- Credits: 5
- Prerequisites
- Useful knowledge:
Signal processing, especially audio, cryptography.
- Contents
- Background:
The increased use of audio data coming from microphones in ubiquitous systems offers new possibilites for context recognition, but causes severe privacy concerns at the same time. This problem is particularly relevant in digital health contexts, as privacy is a top priority in medical data. The goal of this seminar is to give students an overview of signal properties in audio signal which could be crucial for data protection. Afterwards, students research current literature to get an overview of state-of-the-art architectures in the field of audio encryption. Furthermore, students record exemplary audio data and visualise different artifacts. From data investigation, the participants develop a signal processing pipeline that separates relevant health context information from privacy threatening components, such as speech.
Aim:
Develop cryptographic signal processing pipelines for audio data encryption.
Learning Objectives:
Understand privacy threats caused by the usage of audio data. Understand signal properties that can be exploited for audio privacy protection. Develop signal processing pipelines for audio data protection.
Examination:
Final presentation and final report.
- Literature
- Up-to-date literature recommendations are provided during the meetings.
- Zusätzliche Informationen
- Schlagwörter: ACR
Erwartete Teilnehmerzahl: 20, Maximale Teilnehmerzahl: 20
www: https://www.cdh.med.fau.de/2021/03/29/seminar-encryption-of-audio-data-for-context-recognition/
Für diese Lehrveranstaltung ist eine Anmeldung erforderlich.
Die Anmeldung erfolgt von Montag, 29.3.2021, 08:00 Uhr bis Freitag, 23.4.2021, 18:00 Uhr über: StudOn.
- Institution: Lehrstuhl für Digital Health
|
 |
|
|
UnivIS ist ein Produkt der Config eG, Buckenhof |
|
|