Student Assistant Positions - Implementing and Testing a Novel Intrusion Detection System for IoT

We are offering an exciting opportunity for several student assistants to contribute to the development and testing of a groundbreaking Intrusion Detection System (IDS) tailored for the Internet of Things (IoT). As IoT devices become ubiquitous in various domains, robust security measures are needed to prevent that billions of deployed IoT devices are abused. Our project, DÏoT, leverages innovative techniques, including state-of-the-art deep learning algorithms and Federated Learning, to empower users in quickly identifying and mitigating malicious activities and device malfunctions.

Responsibilities

Depending on your background and interests, you will work on one or several of the following key tasks:

Position 1- Deep Learning Model Implementation and Testing: Participate in the design, implementation, and testing of a novel deep learning-based anomaly detection model.

Position 2- Experimentation and Evaluation: Set up and conduct experiments, collect and process IoT network traffic data, test and evaluate our anomaly detection systems.

Position 3- Web-based Dashboard and User Interface Implementation:  Implement an intuitive and easy-to-use web-based dashboard and user interface for the intrusion detection system.

If you are intrigued by this cutting-edge subject, please get in touch with us at info@trust.tu-darmstadt.de to obtain further information. To facilitate the process, please include a summary of your academic background and a copy of your transcripts.