Masterand (m/w/d) AI-based spoofing detection

Masterand (m/w/d) AI-based spoofing detection

Master Thesis for “Development and Evaluation of AI-based GNSS Spoofing Detection Methods for Railway Applications”

Responsibilities

• Literature review of classical methods to detect Spoofing at different levels within GNSS receiver processing chain.
• Literature review of suitable AI based methods to detect Spoofing.
• Creation of a set of “synthetically” generated GNSS authentic and overlayed Spoofing signals with a GNSS Simulator.
• Investigation of the Spoofing effect on the GNSS receiver (Software receiver) output level (Observation of the output signals at different stages, PVT level, Post-correlation level, Pre-correlation level).
• Implementation of 2 or 3 suitable AI based Spoofing detection algorithms with an adapted set of configuration parameters and train the algorithms based on the synthetically generated data set with and without Spoofing.
• Evaluation of the detection performance of each individual method in terms of detection probability for a given false alarm rate.
• Apply the most suitable method/s on real signal with overlayed spoofing signals obtained from a train measurement Campaign.
• Compare the detection performance based on real-world signals with the detection performance based on synthetically generated data.
• Evaluate the results and give recommendations for further improvements / tuning of AI based Spoofing Methods.

Qualifications

• Technical field of study with an interest in satellite navigation.
• Initial insights into communications technology, digital signal processing or data analysis, for example, are an advantage.
• Programming experience or basics in IT security procedures are welcome.
• Initial experience with AI desirable.
• First experiences with jamming / spoofing of satellite signals.

Detailed Analysis of Spoofing Events by using suitable means of AI.