Faculty
Dr. Lea Schönherr is a tenure-track faculty at CISPA Helmholtz Center for Information Security interested in information security with a focus on adversarial machine learning. She received her Ph.D. in 2021 from Ruhr University Bochum, where she was advised by Prof. Dr.-Ing. Dorothea Kolossa at the Cognitive Signal Processing group at Ruhr University Bochum (RUB), Germany. She received two scholarships from UbiCrypt (DFG Research Training Group) and CASA (DFG Cluster of Excellence).
Usenix Security Symposium (USENIX-Security)
Prompt Obfuscation for Large Language Models
GI International Conference on Detection of Intrusions and Malware and Vulnerability Assessment (DIMVA)
Exploring the Potential of LLMs for Code Deobfuscation
International Conference on Learning Representations (ICLR)
σ -zero: Gradient-based Optimization of ℓ0-norm Adversarial Examples
Conference on Neural Information Processing Systems (NeurIPS)
Cooperation, Competition, and Maliciousness: LLM-Stakeholders Interactive Negotiation
Conference on Neural Information Processing Systems (NeurIPS)
Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition
Usenix Security Symposium (USENIX-Security)
The Imitation Game: Exploring Brand Impersonation Attacks on Social Media Platforms
International Conference on Machine Learning (ICML)
BUILD: Buffer-free Incremental Learning with OOD Detection for the Wild
International Conference on Machine Learning (ICML)
Generated Audio Detectors are Not Robust in Real-World Conditions
IEEE Symposium on Security and Privacy (S&P)
A Representative Study on Human Detection of Artificially Generated Media Across Countries
IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)
CodeLMSec Benchmark: Systematically Evaluating and Finding Security Vulnerabilities in Black-Box Code Language Models