Seminar: Encryption of audio data for context recognition

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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.


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


Project type Seminar
ECTS 2.5, 5, 7.5
Language English and/or German
Period Summer term 2021
Presence time Virtual seminar, working from remote
Useful knowledge Signal processing, especially audio, cryptography
Work distribution Literature research, data investigation and visualisation, algorithm development
Med. Eng. designation Advanced Context Recognition (ACR)
StudOn link Link will follow shortly.
First meeting Online introduction/Vorbesprechung
Registration Via StudOn, obligatory after introduction.



Up-to-date literature recommendations are provided during the meetings.


Final presentation and final report.


David Kopyto

  • Job title: Researcher
  • Address:
    Henkestraße 91, Haus 7, 1. OG
    91052 Erlangen
  • Phone number: +49 9131 85-23608
  • Email:

Friedrich-Alexander-Universität Erlangen-Nürnberg