Faculty
Dr. Lea Schönherr ist Tenure-Track-Faculty am CISPA Helmholtz-Zentrum für Informationssicherheit. Sie forscht zu Informationssicherheit mit einem Schwerpunkt auf Adversarial Machine Learning. Sie promovierte 2021 an der Ruhr-Universität Bochum, wo sie von Professor Dr.-Ing. Dorothea Kolossa in der Arbeitsgruppe Kognitive Signalverarbeitung betreut wurde. Sie erhielt zwei Stipendien von UbiCrypt (DFG-Graduiertenkolleg) und CASA (DFG-Exzellenzcluster).
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
IEEE Symposium on Security and Privacy (S&P)
Conning the Crypto Conman: End-to-End Analysis of Cryptocurrency-based Technical Support Scams
European Symposium on Artificial Neural Networks Computational Intelligence and Machine Learning (ESANN)