Welcome to the PATRON research project
Privacy in Stream Processing
What is this about?


The Internet of Things (IoT) envisions a world equipped with a huge number of embedded sensors. Often, the information inferred by stream processing is privacy sensitive.

Wearable Sensors and E-Health

Wearable (fitness-/health-)devices monitor different types of data. E.G. heart rate, body temperature, glucose level and location. Combining these information gives useful insights about the health and other aspects. The severity depends on the combination and what is derivable from that.

Smart Energy Grid

Smart meters measure power consumption and stream data to cloud for processing. That enables useful functions. E.g. optimizing energy consumption or planning of power supply. Contrary this reveals private information like the used electronic devices and all kinds of details about user activity.

Car Sensor Data

There are hundreds of sensors in a modern automobile. The manufacturer, leasing- and insurance-companies are all interested in a lot of the gathered information. For the user it is beneficial if the manufacturer tells him there is a problem with this car, but the customer might not want to be tracked all the time.


Technical concepts and methods for secure, privacy-aware data stream processing

With PATRON we want to reach two goals at the same time:

1. Hide private information from unauthorized parties.

2. Ensure quality of service/data to implement IoT services.


Publications regarding the research topic of Privacy in Stream Processing (PATRON).

Der Secure Data Container (SDC)

Sicheres Datenmanagement für mobile Anwendungen

The Secure Data Container

An Approach to Harmonize Data Sharing with Information Security

Datenschutzmechanismen für Gesundheitsspiele am Beispiel von Secure Candy Castle

Exploratory Study of the Privacy Extension for System Theoretic Process Analysis (STPA-Priv) to Elicit Privacy Risks in eHealth


Datenschutz in Datenstromverarbeitungssystemen

The Privacy Management Platform

An Enabler for Device Interoperability and Information Security in mHealth Applications


A Data-Centric Permission Model for the Internet of Things

Big Brother is Smart Watching You

Privacy Concerns about Health and Fitness Applications

How a Pattern-based Privacy System Contributes to Improve Context Recognition

CURATOR - A Secure Shared Object Store

Design, Implementation, and Evaluation of a Manageable, Secure, and Performant Data Exchange Mechanism for Smart Devices

Preserving Privacy and Quality of Service in Complex Event Processing through Event Reordering


A Hybrid Processing Architecture for Big Data


A Holistic Privacy Approach for the Internet of Things

THOR - Ein Datenschutzkonzept für die Industrie 4.0

Datenschutzsysteme für die Smart Factory zur Realisierung der DSGVO

Zuverlässige Verspätungsvorhersagen mithilfe von TAROT

Recommender-based Privacy Requirements Elicitation - EPICUREAN

An Approach to Simplify Privacy Settings in IoT Applications with Respect to the GDPR

PSSST! The Privacy System for Smart Service Platforms

An Enabler for Confidable Smart Environments

Our Team and Partners

Kai Mindermann M.Sc.

Research Assistant

Saravana Murthy Palanisamy M.Sc.

Research Assistant

Dr. rer. nat. Christoph Stach

Research Assistant

Dr. rer. nat. Muhammad Adnan Tariq

Senior Researcher

Dr. rer. nat. Frank Dürr

Senior Researcher

Prof. Dr. rer. nat. Kurt Rothermel

Supervising Partner (IPVS / VS)

Prof. Dr.-Ing. habil. Bernhard Mitschang

Supervising Partner (IPVS / AS)

Prof. Dr. rer. nat. Stefan Wagner

Supervising Partner (ISTE)

Contact Us via info[at]patronresearch.de

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