Kathrin Grosse

IBM Research - Zurich — Switzerland

Computer Science · Physical Sciences

13h-index1.7kcitations52works4.22yr avg
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Research Topics

Adversarial Robustness in Machine Learning(33), Advanced Malware Detection Techniques(17), Anomaly Detection Techniques and Applications(9), Ethics and Social Impacts of AI(7), Semantic Web and Ontologies(4)

Publications52 total

Manipulating Trajectory Prediction Models With Backdoors
IEEE Transactions on Intelligent Transportation Systems·2025· 1 cited
Prevalence of Security and Privacy Risk-Inducing Usage of AI-based Conversational Agents
arXiv (Cornell University)·2025Open Access
Gen-Review: A Large-scale Dataset of AI-Generated (and Human-written) Peer Reviews
arXiv (Cornell University)·2025Open Access
Security of Deep Reinforcement Learning for Autonomous Driving: A Survey
2025Open Access
I Stolenly Swear That I Am Up to (No) Good: Design and Evaluation of Model Stealing Attacks
arXiv (Cornell University)·2025Open Access
Testing autonomous vehicles and AI: perspectives and challenges from cybersecurity, transparency, robustness and fairness
European Transport Research Review·2025· 6 citedOpen Access
Position: Mind the Gap-the Growing Disconnect Between Established Vulnerability Disclosure and AI Security
arXiv (Cornell University)·2024Open Access
Backdoor learning curves: explaining backdoor poisoning beyond influence functions
International Journal of Machine Learning and Cybernetics·2024· 3 citedOpen Access
A qualitative AI security risk assessment of autonomous vehicles
Transportation Research Part C Emerging Technologies·2024· 11 citedOpen Access
When Your AI Becomes a Target: AI Security Incidents and Best Practices
Proceedings of the AAAI Conference on Artificial Intelligence·2024· 2 citedOpen Access
Machine Learning Security Against Data Poisoning: Are We There Yet?
Computer·2024· 27 citedOpen Access
Testing autonomous vehicles and AI: perspectives and challenges from cybersecurity, transparency, robustness and fairness
arXiv (Cornell University)·2024· 1 citedOpen Access
Voices from the Frontline: Revealing the AI Practitioners' viewpoint on the European AI Act
Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences·2024· 4 citedOpen Access
Manipulating Trajectory Prediction with Backdoors
arXiv (Cornell University)·2023· 2 citedOpen Access
Towards more Practical Threat Models in Artificial Intelligence Security
arXiv (Cornell University)·2023· 3 citedOpen Access
Rethinking data augmentation for adversarial robustness
Information Sciences·2023· 13 citedOpen Access
Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning
ACM Computing Surveys·2023· 118 citedOpen Access
Machine Learning Security in Industry: A Quantitative Survey
IEEE Transactions on Information Forensics and Security·2023· 36 citedOpen Access
Introduction to the Minitrack on Emerging Topics in Digital Government
Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences·2023· 1 citedOpen Access
Security of Deep Reinforcement Learning for Autonomous Driving: A Survey
arXiv (Cornell University)·2022· 3 citedOpen Access
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Frequent Co-authors

Michael Backes(19), Battista Biggio(14), Ambra Demontis(8), Fabio Roli(8), Alexandre Alahi(7), Antonio Emanuele Ciná(6), Marcello Pelillo(6), Carlos Iván Chesñevar(5), Lukas Bieringer(5), Sebastiano Vascon(4), Ana Gabriela Maguitman(4), Tarek R. Besold(4), Ian Molloy(4), Nicolas Papernot(3), Praveen Manoharan(3), Patrick McDaniel(3), Werner Zellinger(3), Katharina Krombholz(3), Michael Thomas Smith(3), Taesung Lee(3)