Evaluating the Effectiveness of Attacks and Defenses on Machine Learning Through Adversarial Samples. - Viraj Rohit Gala; Martin A. Schneider (ICSTW, 2023)

Towards an Empirical Robustness Assessment Through Measuring Adversarial Subspaces. - Viraj Rohit Gala; Martin A. Schneider; Marvin Vogt (AST@ICSE, 2024)

Towards an Evaluation Methodology of ML Systems from the Perspective of Robustness and Data Quality. - Viraj Rohit Gala; Martin A. Schneider; Marvin Vogt (QRS Companion, 2024)