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cs.CR2025
An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline
Tyler Shumaker, Jessica Carpenter, David Saranchak +1
Machine learning (ML) models have the potential to transform military battlefields, presenting a large external pressure to rapidly incorporate them into operational settings. Howe…
cs.CR2020
Class Clown: Data Redaction in Machine Unlearning at Enterprise Scale
Daniel L. Felps, Amelia D. Schwickerath, Joyce D. Williams +6
Individuals are gaining more control of their personal data through recent data privacy laws such the General Data Protection Regulation and the California Consumer Privacy Act. On…
cs.CR2020
Bootstrap Aggregation for Point-based Generalized Membership Inference Attacks
Daniel L. Felps, Amelia D. Schwickerath, Joyce D. Williams +6
An efficient scheme is introduced that extends the generalized membership inference attack to every point in a model's training data set. Our approach leverages data partitioning t…