Data Anonymization for LLM-based Automotive Requirements Processing

05.02.2025, Diplomarbeiten, Bachelor- und Masterarbeiten

This thesis will focus on developing methods to protect privacy while using Large Language Models (LLMs) in automotive requirements processing. As LLMs process sensitive data, such as customer information and design specifications, ensuring that this data remains private is crucial. The research will explore anonymization techniques like data masking and pseudonymization, which hide sensitive details while keeping the data useful for LLM tasks. It will also focus on ensuring that anonymized data retains its meaning and effectiveness in the context of automotive requirements processing. For application please send me an email with title "Master Thesis Application: Data Anonymization LLM ". Please also attach your resume and transcript of records in the email. A motivation letter is NOT required.

Kontakt: f.pan@tum.de