Kathrin Grosse

Title: Kathrin Grosse: Innovator in Machine Learning Security

Introduction

Kathrin Grosse is a prominent inventor based in Clausthal-Zellerfeld, Germany. She has made significant contributions to the field of machine learning, particularly in enhancing the security of trained models against cybersecurity threats. Her innovative approach addresses critical vulnerabilities in machine learning applications.

Latest Patents

Kathrin Grosse holds a patent for a groundbreaking invention titled "Measuring overfitting of machine learning computer model and susceptibility to security threats." This patent outlines mechanisms to assess the susceptibility of a trained machine learning model to cybersecurity threats. The mechanisms execute the model on a test dataset to generate output data, determining an overfit measure that quantifies the model's overfitting to specific portions of the dataset. By applying analytics to this measure, the invention calculates a susceptibility probability, indicating the likelihood of the model being vulnerable to threats. Furthermore, corrective actions can be performed based on this probability, enhancing the model's security.

Career Highlights

Kathrin Grosse is associated with the International Business Machines Corporation (IBM), where she continues to develop innovative solutions in the realm of machine learning and cybersecurity. Her work is pivotal in advancing the understanding of how machine learning models can be made more robust against potential security risks.

Collaborations

Kathrin has collaborated with notable colleagues, including Taesung Lee and Youngja Park, to further her research and development efforts in machine learning security.

Conclusion

Kathrin Grosse's contributions to the field of machine learning security are invaluable. Her innovative patent addresses critical vulnerabilities, paving the way for more secure machine learning applications.