Minimizing Compute Costs: When Should We Run More Expensive Malware Analysis? - André T. Nguyen; Richard Zak; Luke E. Richards; Maya Fuchs; Fred Lu; Robert Brandon; Gary Lopez Munoz; Edward Raff; Charles Nicholas; James Holt (CAMLIS, 2022)

A General Framework for Auditing Differentially Private Machine Learning. - Fred Lu; Joseph Munoz; Maya Fuchs; Tyler LeBlond; Elliott Zaresky-Williams; Edward Raff; Francis Ferraro; Brian Testa (NeurIPS, 2022)

Probing the Transition to Dataset-Level Privacy in ML Models Using an Output-Specific and Data-Resolved Privacy Profile. - Tyler LeBlond; Joseph Munoz; Fred Lu; Maya Fuchs; Elliott Zaresky-Williams; Edward Raff; Brian Testa (AISec@CCS, 2023)

Assemblage: Automatic Binary Dataset Construction for Machine Learning. - Chang Liu; Rebecca Saul; Yihao Sun; Edward Raff; Maya Fuchs; Townsend Southard Pantano; James Holt; Kristopher K. Micinski (NeurIPS, 2024)

ClarAVy: A Tool for Scalable and Accurate Malware Family Labeling. - Robert J. Joyce; Derek Everett; Maya Fuchs; Edward Raff; James Holt (WWW (Companion Volume), 2025)