Student Assistant Positions - Implementing and Testing a Novel Intrusion Detection System for IoT
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.
We are seeking candidates with the following qualifications:
- Good knowledge in one or several of the following domains: IT security, privacy, computer networks, and machine learning
- Motivation and capability to work collaboratively as part of a team
- Proficiency in at least one of the following areas:
- Python and C++ programming; familiarity with ML libraries like PyTorch and Tensorflow
- Network traffic analysis and programming; familiarity with network OSes, tools, and libraries such as OpenWrt, TCPdump, and Scapy
- Familiarity with smart home systems and open sources such as Amazon Alexa, IFTTT, Home Assistant, and openHAB
- Web programming and frontend development